US20140108540A1 - Method of conducting social network application operations - Google Patents

Method of conducting social network application operations Download PDF

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Publication number
US20140108540A1
US20140108540A1 US13/969,561 US201313969561A US2014108540A1 US 20140108540 A1 US20140108540 A1 US 20140108540A1 US 201313969561 A US201313969561 A US 201313969561A US 2014108540 A1 US2014108540 A1 US 2014108540A1
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user
subscriber
information
users
social network
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Abandoned
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US13/969,561
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C.S. Lee Crawford
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C.S. Lee Crawford
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Priority to US73625205P priority Critical
Priority to US75930306P priority
Priority to US77385206P priority
Priority to US86480706P priority
Priority to US11/559,438 priority patent/US20070112741A1/en
Priority to US62383207A priority
Priority to US91763807P priority
Priority to US11/747,286 priority patent/US20070214180A1/en
Priority to PCT/US2007/083987 priority patent/WO2008082794A2/en
Priority to US12/463,168 priority patent/US20100285818A1/en
Priority to US12/767,785 priority patent/US20100324994A1/en
Priority to US12/967,040 priority patent/US8260725B2/en
Priority to US13/586,839 priority patent/US8571999B2/en
Application filed by C.S. Lee Crawford filed Critical C.S. Lee Crawford
Priority to US13/969,561 priority patent/US20140108540A1/en
Publication of US20140108540A1 publication Critical patent/US20140108540A1/en
Application status is Abandoned legal-status Critical

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Abstract

In one embodiment, a method of sharing locations of users participating in a social networking service at a geographic location, the method executed by a computer system and comprises: receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device; associating the location information with the text descriptive information of the first user in a database; sending the text descriptive information and the location information of the first user to a second user for display.

Description

    RELATED APPLICATION
  • This application is a continuation of U.S. patent application Ser. No. 13/586,839, filed Aug. 15, 2012, which is incorporated by reference.
  • BACKGROUND
  • Location based services refer generally to services that provide information to a user in relation to the location of the user. Many prior location based services are relatively pedestrian in nature and provide relatively simple information. An example of a known location based service is a “weather” service in which the user's zip code is provided to the service (e.g., through a conventional HTML webpage, a WAP or other cellular phone interface, etc.) through a network and the service responds by communicating the current weather conditions and the forecast for several days. Other known location based services provide “social” applications such as allowing users to determine each other's locations, receive notification when a friend comes within a predetermined distance, and similar operations. Another type of location based services are generally referred to as “McDonalds finders” that provide search results in a map form (e.g., searching for specific locations of restaurants/stores within a given distance of the user). Other location based services have proposed delivering various types of “advertising” (e.g., when a user arrives at an airport, various ads can be delivered to the user's cellular phone). However, many such prior advertising location based services are quite simplistic and do not possess any appreciable intelligence for selecting advertisements beyond the location of the user.
  • SUMMARY
  • In one embodiment, a method of conducting operations for a social network application, comprises: generating a notification list of recent activities of users of the social network application, wherein the notification list includes (1) at least one activity within the social network application of a first user and (2) at least one hyperlink to an offer involving an activity that is directly related to at least one activity of the first user, wherein an account of the first user defines at least one notification rule for controlling visibility of the at least one activity to other users of the social network application; and providing the notification list to a second user, that is a friend of the first user within the social network application, according to the at least one notification rule of the first user.
  • In one embodiment, a method of providing a location based service (LBS), comprises: (i) receiving location information over a period of time by one or more software programs from a plurality of wireless devices belonging to a plurality of subscribers; (ii) processing the location information to detect that respective subscribers tend to spend time at one or more locations with one or more other specific subscribers; (iii) storing data indicative of a tendency of each such subscriber to spend time with the subscriber's one or more other specific subscribers; (iv) detecting whether subscribers are present at locations with one or more specific subscribers identified in the stored data subsequent to performance of (ii) and (iii); and (v) comparing ad parameters against subscriber data, to select ads for communication to subscribers, wherein the comparing differentiates in selection of ads for communication to subscribers in response to (iv).
  • In another embodiment, the activities identified in the logs are defined in a hierarchical manner. In another embodiment, the logs identify when an activity has been completed. In another embodiment, the logs indicate completion of financial transactions with merchants.
  • In one embodiment, the server for LBS services comprises: one or multiple databases storing information identifying subscribers of one or several LBS or other applications, wherein the one or multiple databases identifies groups of subscribers that have been detected to be located in close physical proximity on multiple occasions; one or multiple databases for storing advertisements to subscribers; code for determining whether subscribers are currently clustering based upon location information pertaining to subscribers; and code for selecting and communicating advertisements to subscribers based on locations of the subscribers, wherein the code for selecting and communicating determines selects ads for subscribers depending upon whether subscribers have been determined to be clustering.
  • In another embodiment, a method comprises the operations performed by the one or more first programs, by the one or more second programs, and/or the LBS applications.
  • In another embodiment, a method of providing a location based service (LBS), comprises: receiving location information by one or more software programs from a plurality of wireless devices belonging to a plurality of subscribers of one or more location based services; processing the location information, by one or more software programs, to identify activity of subscribers at merchant locations; maintaining a respective profile, by one or more software programs, for each of the plurality of subscribers that reflects norm shopping activity for the respective subscriber; comparing information pertaining to current or recent shopping activity, by one or more software programs, for each subscriber of the plurality of subscribers against information stored in the profile of the respective subscriber; selecting ads, by one or more software programs, for each subscriber of the plurality of subscribers in relation to the comparing; and communicating, by one or more software programs, the selected ads to plurality of wireless devices belonging to the plurality of subscribers.
  • The selects ads can be communicate to wireless devices while the plurality subscribers are conducting current shopping activity. In another embodiment, each profile comprises one or more activity norm parameters for a plurality of merchant types.
  • In another embodiment, a method communicates information to users of a social network application. The method comprising: operating at least one social network application server for interacting with users of the social network application, wherein at least some of the users of the social network application are users of wireless subscriber devices; providing a first mobile application for interacting with the social network application, wherein (i) the first mobile application is further operable to employ geolocation functions of a respective wireless device to communicate geolocation information to one or more servers of hardware and software of the social network application, (ii) the first mobile application is operable to automatically to upload photos to a respective user account with text-limited descriptive information manually entered by the respective user for posting on a webpage of the social network application for the respective user, and (iii) at least some entries of text-limited descriptive information communicated from the first mobile application and received by the one or more servers of the social network application are indicative of current activities of respective subscribers; logging activities of users of the social network application using at least information received from the first mobile application, wherein the logged activities include real-world activities of users of the social network application; receiving app usage information from a plurality of second mobile applications of different types by one or more servers of hardware and software, wherein (i) each of the plurality of second mobile applications is (a) different from a web browser application and (b) different from a social network application, (ii) the plurality of second mobile applications include at least mobile gaming applications, mobile digital content applications, and shopping-related mobile applications, and (iii) the second plurality of mobile applications are functionally integrated with the social network application to share subscriber activities across the first mobile application and the second plurality of applications; combining app usage information from the second plurality of mobile applications and social network application activities to create combined activity listings of user activities for respective users including information from the first mobile application and information related to usage of the plurality of second mobile applications; presenting the combined activity listings to viewing users in respective webpages by one or more web servers; selecting ads according to ad parameters for distribution to users of the social network application, wherein the selected ads are selected, at least in part, using app usage information; and communicating the selected ads to users of the social network application.
  • The foregoing has outlined rather broadly certain features and/or technical advantages in order that the detailed description that follows may be better understood. Additional features and/or advantages will be described hereinafter which form the subject of the claims. It should be appreciated by those skilled in the art that the conception and specific embodiment disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes. It should also be realized by those skilled in the art that such equivalent constructions do not depart from the spirit and scope of the appended claims. The novel features, both as to organization and method of operation, together with further objects and advantages will be better understood from the following description when considered in connection with the accompanying figures. It is to be expressly understood, however, that each of the figures is provided for the purpose of illustration and description only and is not intended as a definition of the limits of the appended claims.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • FIG. 1 depicts a system in which multiple LBS applications and other applications provide location based services to multiple subscribers and in which advertisements can be directed to the multiple subscribers using multiple types of information according to one representative embodiment.
  • FIG. 2 depicts a block diagram of a subscriber device adapted for delivery of advertisements according to one representative embodiment.
  • FIG. 3 depicts a flowchart for identifying clustering according to one representative embodiment.
  • FIG. 4 depicts a flowchart for processing cluster data according to one representative embodiment.
  • FIG. 5 depicts a flowchart for utilizing cluster information according to one representative embodiment.
  • FIG. 6 depicts a flowchart for utilizing cluster information according to another representative embodiment.
  • FIGS. 7-14 depict activity norm summary information that can be compiled or calculated for use in selecting ads to communicate to subscribers according to some representative embodiments.
  • FIGS. 15-17 depict respective flowcharts for processing activity information and/or financial transaction information to generate respective norm parameters for storage in subscriber profiles according to some representative embodiments.
  • FIGS. 18 and 19 depict activity norm profiles and for different merchant types according to some representative embodiments.
  • FIG. 20 depicts activity norm analysis that cross-correlates selected financial transaction behavior to other subscriber behavior.
  • FIG. 21 depicts activity norm analysis that cross-correlates selected activities and/or sub-activities to financial transactions according to one representative embodiment.
  • FIG. 22 depicts a system for supporting a social network application according to one representative embodiment.
  • FIG. 23 depicts a wireless, telephony subscriber device according to one representative embodiment.
  • FIG. 24 depicts a user interface for use in a social network application according to one representative embodiment.
  • FIG. 25 depicts a user interface for use in a social network application according to one representative embodiment.
  • FIG. 26 depicts a map interface for displaying mobile subscriber analytics according to one representative embodiment.
  • DETAILED DESCRIPTION
  • Some representative embodiments are directed to systems and methods for monitoring data associated with users of location based services and directing advertisements to the users. Some representative embodiments are directed to distribution of mobile applications. Some representative embodiments are directed to generating, processing, and/or using behavioral analytics. Some representative embodiments are directed to communicating ads for presentation to mobile devices and/or static processor based systems. Some representative embodiments are directed to social network applications.
  • Referring now to the drawings, FIG. 1 depicts a system in which multiple LBS applications and other application servers 101 (also referred to herein as “applications,” “mobile applications,” or “mobile apps” for convenience depending upon context) are provided for communication with multiple subscriber devices 104 and in which advertisements can be directed to the multiple subscribers 104 using multiple types of information. Applications 101 may include one or more social network applications such as the social network applications described in the APPENDICES of PCT Publication WO 2008/082794 A2. Applications 101 may include one or more search applications such as the search applications described in the APPENDICES of PCT Publication WO 2008/082794 A2.
  • As shown in FIG. 1, there are preferably a plurality of applications 101 that provide location based services or other services to subscriber devices 104. Applications 101 can provide conventional location based services such as map/navigation services, weather services, local merchant search services, etc. Applications 101 can further include financial or shopping location based services as described in U.S. Provisional Patent Application No. 60/736,252, filed Nov. 14, 2005, 60/759,303, filed Jan. 17, 2006 and 60/773,852, filed Feb. 16, 2006, which are all incorporated herein by reference in their entirety. Applications 101 can include “social” applications or gaming applications that facilitate different types of subscriber interaction. LBS applications 101 may receive location information that is indicative of the current location of subscribers 104 and communicate LBS information to the subscribers 104 according to the location information either upon request by the subscribers 104 or automatically depending upon the nature/purpose of the particular LBS application 101. The application data is possibly communicated through Internet 102 and a wireless network 103 (e.g., a cellular network) to subscribers 104. The subscriber devices 104 can be any type of suitable wireless device (e.g., cellular phones, “smartphones,” wireless e-mail devices, wireless capable PDAs, etc.) that possess the ability to determine their approximate current location or communicate through a network that enables the approximate location to be determined.
  • Applications 101 may also communicate with gateway/web service 105. In preferred embodiments, subscriber devices 104 communicate their current location to gateway/web service 105. Also, as subscriber devices 104 access various LBS applications 101, subscriber devices 104 communicate their activation of an LBS or other application to gateway/web service 105. Such location and device use data may be employed for the selection of ads for presentation to users of subscriber devices 104 as discussed herein. Gateway/web service 105 then may intermediate communication between the selected application(s) 101 and the respective subscriber devices 104. Thus, subscribers 104 may access multiple applications through the same source (or may coordinate selected communication through a common server or service). Also, subscribers 104 may only need to communicate their current location to the same destination which is then available to any application 101 as appropriate.
  • Although gateway/web service 105 provides such gateway services, the gateway services are not critical to all embodiments. In some embodiments, subscriber devices 104 and/or applications 101 can report to web service 105 (i) the current location of subscribers 104 to web service 105 as subscribers 104 utilize their respective applications and (ii) when a respective subscriber 104 accesses an application and ceases use of the application (if applicable).
  • Gateway/web service 105 updates and/or maintains a log of locations where subscribers 104 visited in DB 107. Also, gateway/web service 105 maintains a log of interaction with or access to particular LBS or other applications 101. Any suitable app usage information may be communicated to gateway/web service 105 such as transactions, app-specific actions, social interactions facilitated through one or more apps, etc. Additionally, gateway/web service 105 may maintain a log of financial transactions completed by various subscribers as identified by financial applications 101 (e.g., a budget application, a fraud monitoring LBS application, etc.) and communicated to gateway/web service 105.
  • Gateway/web service 105 utilizes the location information, application interaction information, and/or financial information to infer the activities performed by the subscribers and the current activity being performed by the subscribers. The logs of activities for subscribers and current activities being performed are stored in DB 107. The logs of activities enable more accurate selection of ads, incentives, offers, etc. to be directed to subscribers as will be discussed below. In some embodiments, the log activities are formed into one or more listings (possibility in sequential time order) for viewing by viewing users in webpages via one or more webserver. The viewing users may be advertisers. Alternatively, the viewing users may be “friends” of a given user in a social network application.
  • In some embodiments, the following activities and sub-activities are defined: (i) commuting; (ii) work; (iii) school; (iv) dining—(a) fast food; (b) casual; . . . fine dining; (v) entertainment—(a) movie; (b) music venue; . . . bar; (vi) sports/recreation—(a) health club; (b) golf; (c) athletic complex/fields; . . . gaming; (vii) shopping—(a) groceries; (b) gas; (c) clothing, shoes, accessories; (d) home decoration; (e) home improvement; . . . sports equipment; (viii) social; (ix) traveling/vacation, etc. Of course, these activities and sub-activities are by way of example and any other activities and/or sub-activities could be additionally or alternatively employed. Also, it shall be appreciated that the activities need not be mutually exclusive in that a single subscriber could be engaged in multiple activities at the same time. The information can be encoded in any suitable ontology. For example, a hierarchical classification of the types of locations could be formulated. In one embodiment, specific merchants are defined within the hierarchical framework within shopping related activities. An example branch in such a hierarchical framework could be RETAIL: shopping: big-box store: TARGET®: grocery section. In alternative embodiments, any such hierarchical descriptors assignable to locations that indicate the nature of the activity being undertaken by a subscriber may be employed. In some embodiments, many of the activities and sub-activities are related to activities at physical locations (e.g., specific locations, specific merchants, etc.).
  • In some embodiments, a current activity of a subscriber can be inferred from the type of application that the subscriber is accessing. For example, if a subscriber is utilizing a navigation LBS application and the subscriber has not reached their destination, it may be inferred that the subscriber is commuting. If a subscriber is utilizing a social application, certain activities (work, school, etc.) can be eliminated or considered less probably or relevant while other activities can possess a greater probability (e.g., dining, entertainment, etc.). Accordingly, when gateway/web service 105 attempts to infer the current activity of a subscriber, gateway/web service 105 identifies the applications that are currently active for the subscriber.
  • In some embodiments, gateway/web service 105 utilizes information in DB 106 to infer the activity of the user. In general, DB 106 correlates specific locations to one or several specific activities. For example, DB 106 can be constructed by “mapping” the addresses or coordinates of residential areas, retail districts, schools, health care facilities, sports/athletic facilities, etc. to the particular activities that are customary to those types of locations. Additionally, DB 106 includes information at several geospatial “resolution” levels. In some embodiments, DB 106 comprises geo-coordinates or other spatial information that define (i) various retail districts at a higher level, (ii) specific malls, strip-malls, stand-alone stores, etc. within a retail district, (iii) specific stores; and (iv) sub-store locations. In sub-store locations, the specific goods or specific service provided can be identified. By maintaining a log of the locations visited by a subscriber and the amount of time spent at the locations, the activities of a user can be estimated. Sub-store locations can be determined utilizing any number of mechanisms and/or algorithms. For example, a GPS receiver could be employed provided the GPS receiver possesses sufficient antenna gain and sufficient reception within the store. Alternatively, many retail locations utilize multiple WiFi access points. The particular ID's of the WiFi access points that are detectable and/or the relative signal strength of the WiFi access points can be utilized for an intra-store location determination. Also, sub-store locating functionality can be utilized to ascertain whether a subscriber has made a purchase at a particular merchant. For example, if a subscriber has spent an amount of time near a location where a cash-register is known to be present and the subscriber leaves the store after being at that location, it may be inferred that the subscriber has made a purchase at that store.
  • Financial information captured by financial related LBS applications 101 can be used to augment the identification of subscriber activities. In such financial related applications 101, the applications monitor user accounts for the completion of transactions (e.g., credit or debit card transactions). Using the merchant information (merchant ID, merchant name, merchant classification, etc.) in the transaction information, the activity can be more closely estimated. For example, if a user is located within a mall and the user previously purchased items at a clothing store, the specific current shopping activity can be inferred to include clothing shopping even though the user may temporarily depart from stores containing such items. Alternatively, transaction information may signal that a particular activity has been completed by the user. For example, if a user makes a purchase at a grocery store that is typical for their weekly grocery purchases, one can conclude that the user will not be conducting further significant grocery shopping for some amount of time. Transaction information can be obtained using the systems disclosed in APPENDIX A of PCT Publication WO 2008/082794 A2.
  • As an example of a user log could be given by: 6:00 am-8:30 am: undefined; 8:30 am-9:00 am: banking; 9:15 am-10:20 am: grocery shopping; 12:15 pm-1:00 pm; dining (fast food); 1:30 pm-2:00 pm: commuting: 2:00 pm: begin shopping (clothing): clothing purchase made at 2:35 at young women's depart. of dept. store retailer. In some representative embodiments, logs can be reviewed by advertisers. The viewing of activities or selected portions thereof may be conditioned upon subscriber privacy preferences. In alternative embodiments, the logs are not actually reviewable by advertisers. Instead, the logs are merely maintained in DB 107 and advertising parameters are compared against the information in the logs to direct advertisements.
  • By providing such a log of activities (previously performed and currently performed), a more intelligent selection of ads for communication to the subscriber can occur. For example, when the grocery shopping activity has been completed, selection of ads for specific grocery items will have relatively little value. Depending upon the purchasing behavior of the subscriber, it may be advantageous to send the subscriber clothing-related advertisements while the subscriber is clothing shopping (even after one or several purchases have been made). Alternatively, if the subscriber has already spent more than the subscriber usually spends as reflected in the prior purchases, it may not be advantageous to send more clothing advertisements since the subscriber may have already spent their limit and is only currently “browsing,” i.e. the probability of further purchases can be estimated as being low.
  • In some embodiments, activity norms and financial norms (e.g., selected behavioral analytics) are calculated by observing subscriber behavior over a period of time. For the purpose of this application, the term “norm” parameter refers to a parameter that is indicative of a general level or average for the particular subscriber. For example, for grocery shopping norms, the typical period between grocery shopping (e.g., in days), the typical day(s) for grocery shopping, the average amount spent, the range of amounts spent, the standard deviation of amounts spent, the type of stores in which grocery shopping occurs, etc. can be compiled from location information and financial information obtained by LBS applications. As another example, for clothing-type shopping norms, the typical day(s) for shopping, the average amount spent, the standard deviation of amounts spent, the number of transactions per shopping event, the average amount of time spent shopping at a particular retail location and/or per day, the types of stores visited, etc. can be compiled, the types of items purchases (if known), etc. can be compiled. Also, correlation between activities can be compiled. For example, it may be observed that a particular subscriber may routinely engage in a “dining (fast food)” activity after engaging in “recreation—sports complex” activity. Subscriber activity and/or financial norms are then compared against subscriber's more recent activities for the purpose of ad selection.
  • By compiling such information, intelligent selection of ads for subscribers may occur. In preferred embodiments, advertisers upload ads into ad DB 109 through ad server 108. Also, the advertisers specify any specific ad parameters for association with their various ads. The ad parameters are compared by ad server 108 against subscriber information and the activity information and norm information in DB 107. When the information in DB 107 satisfies the ad parameters for particular subscribers, the respective ad(s) are communicated to those subscribers by ad server 108. Any other ad selection criteria can be employed. For example, the ads of certain advertisers can be prioritized based upon purchased ad placements. The payment for placement of ads may include payments to prioritize ad placement according to any ad parameter discussed herein or in the APPENDICES of PCT Publication WO 2008/082794 A2. For example, payments for ad placements may occur according to purchasing norm parameters, clustering parameters, shopping timing parameters, etc. which are discussed below. The payments for ad placements may also utilize any such parameters in combination or in combination with other subscriber data. For example, an advertiser may pay for ad placements for subscribers that typically spend greater than $200 per shopping trip, shop at a specific type of retail establishment, and that fit a given demographic profile. All such combination of ad parameters are contemplated according to some representative embodiments.
  • Referring now to FIG. 2, subscriber device 200 is shown that is adapted for delivery of advertisements according to one representative embodiment. Subscriber device 200 can be any suitable wireless device, such as a cellular phone, that is capable of executing software instructions. The software instructions on subscriber device 200 preferably include multiple LBS or other mobile applications 203. The local applications 203 may contact remote LBS or other application servers 101 to deliver the application-based information to the subscriber. Subscriber device 200 further includes LBS agent 201. LBS agent 201 preferably manages or intermediates the communication of location LBS applications 203 with remote LBS applications 101 and/or gateway service 105. LBS agent 201 preferably forwards location information to the appropriate LBS applications 101 and/or gateway service 105 at times defined by the respective applications. Also, LBS agent 201 may receive messages from applications 101 and forwards the messages to the respective local applications 203. LBS agent 201 simplifies the implementation of LBS applications 203 and prevents conflict or difficulties in the execution of local LBS applications 203. Also, LBS agent 201 can manage updates to any LBS functionality that is common to all LBS applications 203 or one or several specific LBS applications 203.
  • Subscriber device 200 further comprises software for presenting ads to subscribers in an efficient manner. In one embodiment, subscriber device 200 comprises ticker software application 204 and ad detail menu application 205. In preferred embodiments, some ads are communicated to LBS agent 201 of subscriber device 200 using SMS messaging. The SMS messages preferably detail how the ad is to be presented to the subscriber. Preferably, the SMS messages detail whether the ad is to be placed into a ticker, for how long, and what particular text is to be displayed in the ticker. A ticker generally refers to a scrolling stream of characters on a screen of the wireless device (e.g., that mimics a “ticker-tape” in electronic form). LBS agent 201 provides the appropriate information to ticker software application 204 to display to the user when the user reviews the screen of subscriber device 200 (e.g., when the subscriber opens his/her phone). Also, the SMS messages preferably detail information to be placed in a menu type form that provides a more detailed presentation of ads for subscriber review. Also, should a subscriber desire to view additional detail for an ad or download a digital coupon, a hyperlink can be included for user selection that causes browser application 206 to download the corresponding content. In other embodiments, ads may be presented directly within mobile apps. The mobile apps may also permit a user to click on an ad to “click through” to more detailed ad presentation via a browser application as an example.
  • In some embodiments, “digital coupons” are communicated to subscriber devices 104 through the ad selection functionality of ad server 108 and ad DB 107. The digital coupons are preferably implemented by use of a digital image encoded according to a digital rights management (DRM) scheme. The digital image can display the “coupon” details, such as product/store/location/purchase conditions, the amount of the coupon, etc. Also, the digital image preferably includes a “code” (e.g., an alphanumeric string) that authenticates the validity of the coupon. When a subscriber wishes to use a digital coupon, the user can present the screen of the subscriber device 104 displaying the digital coupon to a clerk of a merchant. A merchant that has previously agreed to accept such digital coupons can enter the code into the merchant's POS device during a transaction. The merchant's system can then determine the validity of the coupon in real-time by communicating the code to a suitable server. Upon determining the validity of the coupon, the merchant's POS device can suitably adjust the transaction total. Also, the merchant's system can use the code to obtain settlement of the coupon amount at a later appropriate time using the code.
  • The DRM functionality can be used for several purposes in the digital coupon process. In some embodiments, the DRM functionality ties the digital coupon to a specific subscriber device 104, i.e., the digital image is not decrypted by other subscriber devices. Also, in some embodiments, location information can be encoded within the DRM rules. For example, spatial coordinates and a radius distance can be defined such that the digital image is only decrypted by the DRM software when the user is within the area defined by the spatial coordinates and the radius distance (to ensure that the coupon is only presented at desired retail locations/merchants, etc.). That is, the DRM software accesses the current location of the subscriber device 104 and selectively decrypts the digital image by comparing the current location to the location rules defined in the DRM license associated with the digital coupon.
  • In some embodiments, a short “ad” of several seconds (e.g., a promotional video) is incorporated with a digital coupon. When a subscriber initially reviews the digital coupon, the promotional video is played. After the promotional video is played, the digital image containing the coupon information is then displayed. The DRM license can contain a DRM rule that causes the video to be deleted upon review for the purpose of minimizing the memory usage of the digital coupon over time.
  • Some representative embodiments can provide a number of advantages. For example, by maintaining a database of sub-locations within specific stores and the types of goods at those sub-locations, intelligent selection of ads for delivery to subscribers can occur. For example, in ordinary e-advertising and LBS advertising, it is most likely never useful to communicate an advertisement for an inexpensive, somewhat common-place food item. That is, the ad will have a very low probability of affecting the subscriber's purchasing activities. However, if it is known that a subscriber is standing in a particular grocery aisle of a “big-box” retailer that contains that type of food item according to representative embodiments, communication of such an ad may make economic sense because the probability of the ad being successful in affecting the purchasing behavior is much higher than if the ad were communicated when the subscriber is at another type of location.
  • Additionally, by providing a log of activities, selection of ads for subscribers can occur in a much more efficient and effective manner that possible according to conventional LBS applications. That is, subscriber activities provide a more reasoned basis for estimating the appropriateness of an ad for a subscriber than the mere current location of the subscriber. Also, by aggregating data over time and data from multiple sources, the activities of a subscriber can be more accurately inferred. Also, by compiling historical norms, the effectiveness of an advertisement in affecting immediate purchasing behavior can be more readily determined.
  • FIGS. 7-14 depict activity norm summary information 700, 800, 900, 1000, 1100, 1200, 1300, and 1400 that can be compiled or calculated for use in selecting ads to communicate to subscribers according to some representative embodiments.
  • FIG. 7 depicts activity summary profile 700 according to one representative embodiment. Activity summary profile 700 stores information that indicates the amount of time spent by a subscriber for a plurality of activities. Also, the information is provided in a hierarchical manner. Specifically, the amount of time is shown for various sub-activities. As shown in FIG. 7, for ACTIVITY 1, the average amounts of time spent for ACTIVITY 1 per day of the week (Sunday through Saturday) are represented by parameters V1-V7. The standard deviations for the amounts of time spent for ACTIVITY 1 per each day of the week are represented by parameters s1-s7. The average amounts of time spent per week and per month for ACTIVITY 1 are represented by parameters V8 and V9 and the standard deviations for time spent per week and per month are represented by s8 and s9. In a similar manner, average amounts of time and standard deviations are shown for SUBACTIVITIES, i.e., (V′ 1-V′9, s′ 1-s′9) for a first sublevel activity and (V″1-V″9, s″1-s″9) for a second sublevel activity. Any suitable number of subactivities and levels of subactivities could be so provided. As shown in FIG. 7, this type of information is repeated for a plurality of activities (through “ACTIVITY N”).
  • FIG. 8 depicts activity probability profile 800 according to one representative embodiment. Activity probability profile 800 is defined for one day of the week (i.e., Sunday). Preferably, similar profiles (not shown) are defined for other days of the week. Profile 800 defines the probability that a subscriber will engage in a particular activity within a given time frame. For example, the probability that the subscriber will engage in ACTIVITY 1 between 5 am and 6 am is defined by the parameter P1. Likewise, the probabilities for the other hours of the day for ACTIVITY 1 are defined by parameters P2-P24. Probabilities for hierarchical subactivities are shown in parameters P25-P48 and P49-P72. Probabilities are preferably defined for a plurality of activities through ACTIVITY N.
  • FIG. 9 depicts shopping activity profile 900 according to one representative embodiment. Profile 900 comprises relatively high level shopping summary information. Profile 900 comprises the average amounts of time spent shopping per each day of the week, per week, and per month in parameters X1-X9. The standard deviations for these times are shown in parameters x1-x9. The shopping frequencies for these time periods are represented by parameters F1-F9. The shopping frequency represents the average number of discrete shopping trips taken by the subscriber for the respective time period. The standard deviations for the shopping frequency for these periods are represented by parameters f1-f9. The average amounts of time per shopping trip are represented by parameters T1-T9 for these time periods with the standard deviations represented by parameters t1-t9.
  • The average amounts of time spent shopping per shopping location (e.g., MALL X, MALL Y, . . . MALL Z, etc.) is shown for a plurality of locations for these time periods. The locations are preferably retail locations in which there are multiple merchant stores in relatively close proximity such as a mall or retail district. For LOCATION 1, the average amounts of time for the various time periods are represented by parameters L1-L9 with the standard deviations represented by parameters 11-19. Also, the average numbers of stores visited by retail location for the time periods for LOCATION 1 are represented by parameters SL1-SL9 with the standard deviations represented by parameters s11-s19. Similar parameters are defined for a plurality of locations (as shown through LOCATION Z).
  • FIG. 10 depicts merchant type shopping profile 1000 according to one representative embodiment. Profile 1000 preferably stores average amounts of time spent shopping for a plurality of merchant types (e.g., clothing retailers, electronics retailers, bookstores, big-box retailers, grocery retailers, etc.). Also, the standard deviations are defined (denoted by the “s” prefix). The amounts of time and standard deviations are preferably calculated or compiled for each day of the week, per week, and per month time periods. Also, average amounts of time and standard deviations are defined for sub-store locations or departments for various merchant types. Such information is preferably compiled or calculated for a plurality of merchant types (shown as MERCHANT TYPE 1 through MERCHANT TYPE X). FIG. 11 depicts merchant shopping profile 1100 according to one representative embodiment. Profile 1100 stores the same type of information as profile 1000 except the information pertains to specific merchants as opposed to types of merchants.
  • When financial transactions are monitored and logged, shopping activity norms in terms of purchases are preferably compiled or calculated. FIG. 12 depicts shopping purchase profile 1200 according to one representative embodiment. Profile 1200 stores average numbers of purchases per shopping trip (parameters NP1-1 through NP1-9) and average amounts spent per shopping trip (parameters DP1-1 through DP1-9) for each day of the week, per week, and per month time frames. The standard deviations for these values are also given (parameters sNP1-1 through sNP1-9 and sDP1-1 through sDP1-9). Average numbers and amounts of purchases for locations are defined (LOCATION 1 through LOCATION N) as shown in parameters NP-L1-1 through NP-L1-9 . . . NP-LN-1 through NP-LN-9 and DP-L1-1 through DP-L1-9 . . . DP-LN-1 through DP-LN-9. Standard deviations are also defined for the locations for these time frames as shown in parameters sNP-L1-1 through sNP-L1-9 . . . sNP-LN-1 through sNP-LN-9 and sDP-L1-1 through sDP-L1-9 . . . sDP-LN-1 through sDP-LN-9. Merchant type purchase profile 1300 (FIG. 13) and merchant purchase profile 1400 (FIG. 14) depict similar purchase information (number of purchases, dollar amounts, standard deviations) by merchant types and specific merchants.
  • FIG. 15 depicts a flowchart for processing shopping activity information for a respective subscriber to generate profile information according to one representative embodiment. In 1501, activity information is retrieved for the last 6 months in a preferred embodiment (although any other suitable length of time could be selected). The activity information is preferably retrieved from pre-existing activity logs according to one embodiment. Alternatively, location based information could be retrieved and correlated to activities in conjunction with the norm building process. In 1502, total time is calculated for each activity (and subactivity) per day of week, per week, per month. In 1503, the total amounts of time are divided by the numbers of each of days of the week, the number of weeks, and the number of months for the selected period of time. The values are stored in one or more profile(s).
  • In 1504, the number of times that each activity (subactivity) was performed in various time periods (e.g., each hour interval per day of week) is calculated. In 1505, the numbers of times for each activity/subactivity are divided by the total numbers of each of the days of the week in the selected period of time and the resulting values are stored in one or more profile(s).
  • In 1506, the number of times that the subscriber went shopping over the selected period and for each day of week are calculated. In 1507, the calculated numbers of times are divided by the number of months, the number of weeks, and the number of days, respectively. The resulting values are stored in one or more profile(s).
  • FIG. 16 depicts a flowchart for processing shopping activity information for a respective subscriber to generate profile information according to one representative embodiment. In 1601, activity log information is retrieved for last 6 months (or any other suitable period of time). In 1602, the total amount of time spent shopping over the selected period of time is calculated. Also, the total amount of time for the selected period for each day of the week is also calculated. In 1603, the calculated values are divided by the numbers of each day of the week, number of weeks, number of months in the selected period of time and the resulting values are stored in one or more profiles to generate the average amounts of time spent shopping per day of week, per week, and per month. In 1604, the standard deviations for the various time periods are calculated and stored in one or more profiles.
  • In 1605, the calculation of averages and standard deviations for the time is repeated for a plurality of shopping locations or respective retail locations in which multiple merchants are present. The calculated values are stored in one or more profile(s). In 1606, the calculation of averages and standard deviations are repeated for each merchant type and sub-store location. The calculated values are stored in one or more profile(s). In 1607, the calculation of averages and standard deviations are repeated for each merchant and sub-store location. The calculated values are stored in one or more profile(s).
  • In 1606, the calculation of averages and standard deviations is repeated for each discrete shopping trip. That is, an individual shopping trip refers to a period of time where a subscriber was substantially continuously engaged in a shopping activity. The average amounts of time spent shopping per shopping trip per each day of week, per week, and per month are calculated and the standard deviations are calculated.
  • In 1607, the numbers of times that the subscriber went shopping over the selected period and for each day of week over the selected period are calculated. In 1608, the calculated values are divided by the number of months, the number of weeks, the number of each day of the week in the selected period of time and the resulting values are stored in one or more store in one or more profiles.
  • FIG. 17 depicts a flowchart for processing financial activity information for a respective subscriber to generate profile information according to one representative embodiment. In 1701, transaction information is retrieved for last 6 months or any other suitable period of time. In 1702, the total numbers of purchases for each day of week and total number of purchases are calculated. In 1703, the total dollar amounts of purchases are calculated for each day of the week and total dollar amount of purchases over the selected period of time are calculated. In 1704, the calculated values (from 1702 and 1703) are divided by the numbers of each day of the week, the number of weeks, and the number of months within the selected period to calculate the average values to be stored in the one or more profile(s). In 1705, the standard deviations for respective time periods are calculated and stored in one or more profiles.
  • In 1706, the calculations are repeated to calculate the averages and standard deviations for the various time periods for each shopping trip. The calculated values are stored in one or more profile(s). In 1707, the calculations are repeated for each shopping location. The calculated values are stored in one or more profile(s). In 1708, the calculations are repeated for each merchant type. In 1709, the calculations are repeated for each merchant. The calculated values are stored in one or more profile(s).
  • FIGS. 18 and 19 depict example activity norm profiles 1800 and 1900 for different types of merchants according to some representative embodiments. Norm profiles 1800 and 1900 are preferably compiled by monitoring activity information as determined using LBS data and financial information for the respective subscriber. Any number of similar profiles can be defined for other types of shopping or spending activities. Preferably, some profiles are created and maintained for each subscriber, although not every profile need be created and maintained for each subscriber as some subscribers may not sufficiently engage in the respective activity for the information to be useful.
  • Norm profile 1800 depicts activity norm data for “FAST FOOD DINING.” Norm profile 1800 depicts the percentage of times that the subscriber engages in the activity at the respective times (by breakfast, lunch, and dinner) for each day of the week and the average amount spent at each respective time when the subscriber decides to engage in the activity. It may be observed that at certain times the subscriber dines with other parties, such as members of the subscriber's family, while at other times the subscriber dines alone (compare breakfast on Sunday with lunch on Wednesday). Profile 1800 further details percentages of purchases by restaurants and restaurants types. For example, profile 1800 indicates that the subscriber dines at restaurant A 35% of time when the subscriber decides to engage in fast food dining. Profile 1800 further indicates that the subscriber dines at a restaurant of type A 45% of the time when the subscriber decides to engage in fast food dining.
  • Norm profile 1800 preferably indicates other activities that are correlated to fast food dining. For example, norm profile 1800 indicates that when the subscriber is engaged in a “work—traveling” activity, the subscriber engages in fast food dining 76% of the time (during or shortly thereafter the work-traveling activity). Also, norm profile 1800 indicates that when the subscriber is or recently has engaging in a “shopping mall” activity, the subscriber engages in fast food dining 44% of the time (during or shortly thereafter the shopping mall activity). By providing such correlation information, specific ads can be directed to a subscriber at an appropriate time. Specifically, the ads might be able to reach the subscriber before the subscriber has made a decision to engage in a specific activity or to go to a specific merchant. That is, if only current location data is utilized, “fast food dining” ads might not be selected. Accordingly, the subscriber may make a decision to engage at a specific fast food restaurant before ads are ever communicated to the subscriber. Some embodiments potentially enable ads to be communicated to the subscriber at a relevant time but before the subscribers has made such a decision. Thereby, the “steering” ability of communicated ads according to some embodiments may be relatively high.
  • Norm profile 1900 is similar to norm profile 1800 except that norm profile 1900 includes norm parameters relevant to clothing shopping, clothing merchants, and clothing merchant types (e.g., young-women's retailer, designer retailer, discount retailer, etc.). Profile 1900 includes additional information. For example, norm profile 1900 preferably includes a parameter that indicates that the number of clothing-related purchases that the subscriber typically makes per shopping trip. Norm profile 1900 may also include information indicative of the typical goods or type of goods purchased by the subscriber (e.g., if the information is made available by the retailers in connection with coupon, discount, or payment settlement processes).
  • Profile 1900 also preferably includes information that relates a correlation between other financial considerations and the purchase of clothing. Profile 1900 indicates that there is an increased probability of 50% of clothing purchases immediately after deposits into a financial account of the subscriber (e.g., when a paycheck or other funds are deposited in the account). Also, there is an increase in the average amount of said purchases immediately after deposits of 70%. It is seen, for this subscriber, that clothing purchases are highly correlated to available funds and, accordingly, the selection of ads for this subscriber should also depend upon the deposit of funds into the subscribers account (e.g., in terms of timing of the deposits and the amounts of the deposits).
  • Profile 1900 indicates decreased probability of 20% immediately after out of budget expenses. Profile 1900 further indicates a decreased average amount of purchase immediately after out of budget expenses of 50%. In general, expenses may be categorized by analyzing the financial activity of a subscriber to assign expenses/payments to various categories. See APPENDIX A of PCT Publication WO 2008/082794 A2. Significant deviations (e.g., greater than 20%, 30%, . . . 50%, or any suitable dollar amount) from typical expenses for a significant budget category may indicate that the subscriber is currently experiencing financial difficulty or unexpected expenses. For some subscribers, such unexpected expenses may cause the subscribers to curtail certain other purchases. By correlating such unexpected expenses to purchasing behavior, subscriber reaction to subsequent unexpected expenses may be predicted and ad selection modified in response thereto. Accordingly, such information can be obtained and stored in subscriber profiles according to some representative embodiments for the purpose of ad selection for subscribers.
  • FIG. 20 depicts activity norm analysis that cross-correlates selected financial transaction behavior to other subscriber behavior. In 2001, deviations in typical expenditures (e.g., deviations exceeding 10%, 20%, 30%, and 40% of typical discretionary or other spending) are identified. Such deviations may be performed to identify unexpected expenses or significant purchases that may impact other purchasing decisions of the subscriber. In 2002, changes in purchasing behavior after identified deviations are identified for multiple shopping/spending categories in terms of probabilities of purchases and amounts of purchases. In 2003, changes in probabilities and amounts of purchases are stored in profiles for the various identified deviations (if any). In 2004, changes in purchasing behavior after deposits into subscriber account(s) in terms of probabilities of purchases and amounts of purchases are analyzed In 2005, changes in probabilities and amounts of purchases are stored in profiles for various deviations. In 2006, changes in purchasing behavior in relation to variation in amounts of deposits into subscriber account(s) in terms of probabilities of purchases and amounts of purchases are analyzed. In 2007, changes in probabilities and amounts of purchases are stored in profiles for various deviations.
  • FIG. 21 depicts a flowchart to identify correlations between purchasing behavior of a subscriber and various activities performed by the subscriber according to one representative embodiment. In 2101, an activity and/or subactivity of subscriber is selected for analysis. In 2102, occurrences of selected activity/subactivity in activity logs for a suitable time period (e.g., six months) are identified. In 2103, a logical comparison is made to determine whether the selected activity/subactivity has been performed greater than x number of times within the period of time. If so, the process flow proceeds to 2104. If not, the process flow proceeds to 2107.
  • In 2104, financial transactions within predetermined time period of each occurrence of activity/subactivity are retrieved (e.g., within one, two, or three hours, for example). In 2105, transaction types that have occurred at least y % of the time that the activity/subactivity was performed by subscriber are identified (e.g., clothing purchases, payments for dining, payments for various forms of entertainment, etc.). A suitable percentage of the time may be 50% according to one embodiment (although any other suitable percentage could be employed for other embodiments). In 2106, identified transaction types and % for each type of financial transaction are stored in one or more profile(s).
  • In 2107, a logical comparison is made to determine whether other activities/subactivities have been performed by the subscriber within the last six months or other selected time period. If so, the process flow returns to 2101 for selection of another activity/subactivity. If not, the process flow ends at 2108.
  • In some embodiments, the information stored in DB 107 is utilized to analyze and detect the collective activities of subscribers. In some embodiments, “clustering” of subscriber activity is detected. As used in this application, clustering refers to multiple subscribers engaging in a common activity or activities within the relatively same geographical location. Clustering of such individuals could be detected over time by repeatedly observing the close proximity in the locations of such individuals. That is, because the same subscribers are observed in very close physical proximity on multiple occasions, some type of relationship is believed to exist between such subscribers. Specifically, their repeated presence together is not a mere accident. Alternatively, the relationship between such subscribers could be known using a priori information (e.g., as provided by one or several of the subscribers when opening an account with some web or other application, as defined by a social networking application, etc.). It shall be appreciated that clustering is not limited to any particular type of relationship. Clustering may occur in many contexts, e.g., family activities, gatherings of friends, business meetings, etc.
  • Clustering provides valuable insight into the expected behavior of subscribers and especially commercial behavior. Thus, the detection of clustering provides a valuable mechanism to direct various types of advertising to such subscribers. The advertising may take the form of direct ads sent to wireless devices of the subscribers, e-mail advertisements, web page advertisements, etc. The communication of ads may occur while the clustering is taking place or may occur at a later time. The communication may occur before the clustering takes place. That is, it may be possible to predict a clustering event (e.g., the specific subscribers have been observed to cluster at the same approximate time/day, etc.) based on prior subscriber behavior. In such a case, delivery of the ads may occur immediately before the estimated time of the predicted clustering event as an example.
  • As an example, a family may decide to go to a mall on a weekend day. It is quite common for multiple members of the family to possess their own cellular phones. Perhaps, each parent and each teenager in the family would possess their own cellular phone or other wireless device. Assuming that each family members' wireless device possesses a suitable LBS application that reports the respective subscriber's location to an LBS application or LBS gateway, the clustering of the family members can be detected. For example, when the family members initially enter the mall, the family members' respective GPS data may be very similar. That is, the LBS applications of their wireless devices may report substantially similar location information. Also, as each family member enters the mall, the GPS reception may fade at substantially the same time (which can be communicated to an LBS application or gateway). Using such close GPS or other location information, their very close proximity to each other can be detected thereby indicating that a clustering event is occurring. Each member of the family may not necessarily be within very close proximity for the entire expedition to the mall. However, during the common activity, the activities of the family members will most likely be inter-dependent in many ways even though the members are not necessarily in very close proximity the entire time.
  • For example, the family members may initially separate to frequent each family member's favorite stores. However, the family members may gather back together to eat lunch or dinner together. Also, the purchases of the family members may be quite different when the family members are together as opposed to when the family members go shopping individually. For example, when a family is found to be clustering, purchasing may be skewed towards the children or teenagers of the family. If the parents are found to cluster without the children, a different set of purchasing behavior could be expected. Likewise, if each individual were determined to be shopping alone, the purchasing behavior again may be different. Further, shopping in the context of peers or friends can exhibit another set of purchasing norms. Additionally, the individual making the purchases may be different depending upon the presence of other individuals. For example, a parent may decide to go to a particular establishment for a meal for the family which would not be chosen by any individual on their own. Hence, in such a situation, the type of ads for meals should depend upon whether the clustering is taking place and the members of the current cluster. Also, it would be beneficial to identify the party that is most likely to make the purchasing decision.
  • FIG. 3 depicts a flowchart according to one representative embodiment. In step 301, LBS information is accessed from one or several databases for prior locations of a selected subscriber as logged in the database(s). In step 302, the database(s) is/are queried for other subscribers that were present at substantially the same location as the selected subscriber at substantially the same time. In step 303, a logical comparison is made to determine whether there are one or more subscribers that were repeatedly present at the same location as the selected subscriber.
  • If not, the selected subscriber has not been observed to exhibit clustering behavior and the process flow proceeds to step 304 where another logical determination is made. In step 304, it is determined whether there are additional subscribers to analyze. If not, the process flow proceeds to step 305 to quit. If there are, the process flow returns to step 301 to select another subscriber.
  • If the logical comparison of step 303 determines that there are one or more subscribers that were repeatedly present at the same location as the selected subscriber, the process flow proceeds from step 303 to step 306. In step 306, a suitable database update is completed to indicate that the selected subscriber exhibits clustering activity. The database update may include indicating the identifiers of other subscribers with which the subscriber tends to cluster.
  • In step 307, the activities, associated financial transactions, etc. associated with the common locations are identified for the selected subscriber are identified. In step 308, one or more databases are updated to indicate the type(s) of locations, type(s) of common activities and transaction data associated with the selected subscriber's clusters. The process flow proceeds from step 308 to step 304 to determine whether there are additional subscribers for the cluster analysis process.
  • FIG. 4 depicts a flowchart for processing cluster data according to one representative embodiment. In step 401, a cluster of subscribers (multiple subscribers that have been repeated observed within close proximity of each other) is selected (e.g., as identified in one or more databases). In step 402, activity information and financial information (e.g., transaction details) for subscribers in the cluster are retrieved.
  • In step 403, the transactions by individuals in the cluster are categorized (if not already so processed). In step 404, the member(s) of the cluster that are likely to pay for various transactions during clustering are determined. In step 405, the types of goods and/or services that exhibit an increased or decreased probability of purchase are determined for the subscribers of the cluster. In step 406, the types of goods and/or services that exhibit a change in probability when the individuals are not clustering are identified. In step 407, the types of goods that exhibit a change in probability before and after clustering are determined for the subscribers of the cluster. In step 408, the activities that exhibit a change in probability (increase or decrease) in conjunction with the clustering are identified.
  • In step 409, the information pertaining to the clustering is stored in a suitable database or databases.
  • FIG. 5 depicts a flowchart for utilizing cluster information according to one representative embodiment. In step 501, a request (e.g., an HTTP transaction to a suitable LBS advertising web server application) is received from an LBS advertiser.
  • In step 502, a suitable web page is provided to the LBS advertiser that preferably includes interactive elements to enable the LBS advertiser to view subscriber information and to direct advertisements to suitable subscribers. In step 503, cluster information is included within the subscriber information for provision to the LBS advertiser. For example, the LBS subscriber may be allowed to click on a graphical element within the web page that represents a given subscriber. In response, subscriber information may be presented (e.g., an activity log, transaction information, activity norms, financial transaction norms, etc.). Within such information, preferably the LBS advertiser is provided information that indicates whether the subscriber is current “clustering” and, if so, with which other subscribers. The nature of the clustering is preferably identified (e.g., family clustering, peer clustering, business clustering, etc.). Also, information that identifies the types of transactions or activities that exhibit increased or decreased probability are preferably provided. By providing such information, the LBS advertiser can more effectively identify desirable subscribers for ads and/or selected more appropriate ads for the subscribers.
  • FIG. 6 depicts another flowchart for utilizing cluster information according to one representative embodiment. In step 601, advertising parameters are received (which may include one or more clustering parameter values). The advertising parameters define the desired recipients of one or more directed advertisements (e.g., as will be delivered to subscriber wireless devices). For example, the following tag-encoded parameters could be used as part of a desired LBS advertising effort to direct advertisements to subscribers: {<LOCATION>STONEBRIAR MALL</LOCATION>AND <CLUSTERING>TRUE </CLUSTERING>AND (<CLUSTERINGWITHFAMILY>TRUE </CLUSTERINGWITHFAMILY} OR<CLUSTERINGWITHFRIENDS>TRUE </CLUSTERINGWITHFRIENDS>) AND (<CLUSTERINGPURCHASER>MEAL </CLUSTERINGPURCHASER>}. In this case, the ads would be directed to subscribers located within or proximate to “Stonebriar Mall.” Also, the subscribers would be required to be clustering before the advertisement(s) associated with these parameters would be delivered. Also, the subscribers would be required to be clustering with family members or friends (as opposed to business purpose clustering). Also, each advertising target would be required by these parameters to be a subscriber within the respective cluster that tends to pay for meals during the clustering of the respective subscribers.
  • In step 602, ads are communicated by a suitable LBS advertising platform to subscribers according to the received parameters. The direction of the ads may directly depend upon the defined clustering parameters/data provided in the received parameters. For example, an advertiser may direct that advertisements are only to be sent to members of a cluster that make purchasing decisions for meals among other advertising parameters in addition to providing non-clustering advertising parameters. The ad parameters may be defined in terms of any of the clustering information discussed herein or any other suitable clustering information. Alternatively, the advertiser may provide more general advertising parameters and automated subscriber selection algorithms can select the most probable subscribers to respond based upon the clustering information.
  • Social network applications commonly refer to applications that facilitate interaction of individuals through various websites or other Internet-based distribution of content. Originally, the concept of a social network originated within the field of sociology as method of modeling social interactions or relationships. Within such modeling, individuals, groups, or organizations are represented as nodes within a social network and the relationships between the “nodes” are represented as links between the nodes thereby forming a “network.”
  • Some known social network applications have (directly or indirectly) utilized such concepts to facilitate interaction between individuals via the Internet. In most social network applications, a specific user can create an account and provide various types of content specific to the individual, such as pictures of the individual, their friends, their family, etc., personal information in text form, favorite music or videos, etc. The content is then made available to other users of the social network application. For example, one or more web pages may be defined for each user of the social network application that can be viewed by other users of the social network application. Also, social network applications typically allow a user to define a set of “friends, “contacts,” or “members” with whom the respective user wishes to repeatedly communicate. Users of a social network application may post comments or other content to portions of each other's web pages.
  • For the purpose of this application, a social network application refers to any application or system (with communication over wired and/or wireless networks) in which users are permitted to create or define accounts in which the users can make personalized information and content available for viewing by other users of the social network application and, in which, users can define, allow, or create contacts or friends within the social network application in which repeated interaction is intended to occur through the social network application. As used herein, an “account” of a social network application refers to the collection of data maintained for a respective user for interaction with the social network application and other users of the social network application whether stored together or separately. The collection of data may include user id, password, screen name, email address, wireless device info., name information, demographic information, likes/dislikes, photos, activities, relationships, etc.
  • Some representative embodiments differ from certain previously known social network applications. Some representative embodiments preferably provide functionality that enables users of a social network application to interact with other users or “friends” in unique ways. In some embodiments, users may interact with a mobile or mobile application on a smartphone of the user to indicate their “current place” for communication to other users or friends. Also, users may leave comments for other users for such places for presentation to their friends and users (e.g., via their smartphones). As used herein, the term “mobile application” refers to an application on a mobile or wireless, subscriber device which conducts network communication using the wireless functionality of the subscriber device. Some representative embodiments further provide functionality in a wireless phone to enable a user to upload data and/or images to the account of the user in an efficient manner for presentation to other users.
  • Some representative embodiments further enable users to indicate items to which the users have affinity or “like” via a “like function.” In yet further embodiments, the social network application includes location based service functionality as discussed herein. For example, activities of users of the social network application may be logged and employed to direct ads to users of the social network application (e.g., via a mobile application or other software on a given user's smartphone).
  • Referring to system 2110 as shown FIG. 22, some embodiments may conduct various social network application operations. Such operations may include operating at least one social network application server 2115 for interacting with users of the social network application. The software on server(s) 2115 may include a web server for serving pages of the social network application, e.g., HTML pages via HTTP protocols via Internet 2113. Users on computers 2114 may access their accounts, uploaded data, communicate with friends, view other user web pages on the social network application, etc.
  • In one embodiment, photo server is provided for direct uploading of photos to the social network application. Also, a mobile server may be provided for facilitating interaction with wireless, telephony subscriber devices 2111. The software on the application server may maintain selected user account data (in database or other data store 2116) for users of the social network application, where the user accounts include data defining relationships between users of the social network application. The relationships may be referred to as “friends” providing a link between respective users of the social network application. Such friends or users may have privileged status to view certain content posted to the account of another user. The content may include photos (e.g., as stored in image DB 2117).
  • Preferably, at least some of the users of the social network application are users of wireless, telephony subscriber devices 2111 (which communicate, at least partially, through wireless infrastructure 2112 of a public, telephony network). Devices 2111 may also include other wireless communication functionality (e.g., Wi-Fi or similar wireless functionality). The social network application may provide software to operate on wireless, telephony subscriber devices. The software may be in the form of browser-executable code or may be an application for installation and execution on the wireless, telephony subscriber device.
  • FIG. 23 depicts telephony device 2111 according to one representative embodiment. Device 2111 may include conventional components such as processor 2205, wireless communication circuitry 2206, camera 2207, etc. Device 2111 may include memory 2204 for storing data and software. The software may include mobile browser 2201, social network mobile application 2203, and social network application picture upload application 2202 according to some embodiments. Any other suitable software may be included including software for communicating location data and/or device use data and software for receiving ads.
  • In some embodiments, a “like-function” is provided by the social network application. The like-function is a function whereby a user of the social network application may input data, which is defined within the social network application and commonly understood by the users of the social network application, to indicate approval of or affinity with a defined item. That is, the user may input data via a user interface (e.g., on a smartphone app or via a web page on a smartphone or computer) to indicate such approval or affinity and the data is stored in the account of the user. The inputted data from the like-function may then be shared with friends of the given user or other users. The communication of “like-function” data to friends may be communicated to friends based upon access control limits (e.g., all social network users, friends only, selected friends only, etc.).
  • The like-function may be implemented in any suitable form. For example, a simple boolean graphical user input (e.g., a radio button, a select button, etc.) may be provided for the user to indicate the user's affinity or approval. Alternatively, more complex user interface element may be additionally or alternatively employed, e.g., a text input box for specific comments. For commercial items, the like-function data may be indicative of an item that the user is currently contemplating buying, the types of stores that the user is willing to purchase from, the price range of products that the user contemplates is appropriate for the goods of interest, etc. Any such suitable like-function data may be gathered in accordance with some embodiments.
  • In some embodiments, the like-function is combined with location data (e.g., as obtained by the smartphone of the respective user) to specify the location of the item identified by the user via the like-function. The like-function data may also be communicated in a location dependent manner, e.g., when selected friends are present at or arrive at a location near or proximate to the location where the originating user identified the item of interest.
  • Also, ads (e.g., as stored in ad DB 2119) may be selected based upon items identified via the like-function and any other social network application data discussed herein. The ads may also be communicated in a location dependent manner. Any of selection algorithms discussed herein may be employed for direction of ads to users of the social network application according to ad selection criteria for comparison against location, analytic, and/or other data as stored in DB 2118 as an example. Any suitable ad selection and distribution infrastructure may be employed. For example, the multiple application infrastructure discussed herein may also be employed according to some embodiments.
  • FIG. 25 depicts a user interface that may be provided by suitable software on a wireless device 2111 (e.g., by mobile browser 2201 when it is executing suitable browser executable code or application 2203). The interface includes a button for the user to select to indicate affinity or approval of the defined item 2402. The defined item may be input directly by the user via text entry. Alternatively, the defined item may be pre-defined for selection by the user. The user may input appropriate comments in text control 2403. In other embodiments, the user may also upload photos using control 2404. Control 2404 enables the user to browse files and file directories for selection of one or more photos for the upload process. Button control 2405 enables the user to upload the photo(s) and data defined by the various controls.
  • In some embodiments, the social network application includes functionality to enable interaction and/or communication between users of the social network application in relation to defined locations or “places.” In some embodiments, mobile app software is provided (e.g., via downloading and/or installation) for operation on the wireless, telephony subscriber devices. The mobile app software is intended for interacting with the social network application to access user accounts of the social network application. For example, the mobile app software may enable a user to view the profile pages of the friends of the user and the profile pages of other users (as permitted by access control data).
  • The mobile app software is preferably further adapted to enable a user of the wireless, telephony subscriber device to “check in” at respective locations from a plurality of locations. A “check in” refers to an operation that is performed via the social network application (e.g., through the mobile app software) to permit the user to indicate through the social network application the current whereabouts of the user. This location may be displayed on the user's profile page, be communicated on a map interface provided by the social network application, or may be communicated directly to the wireless, telephony subscriber devices of friends. The communication may occur in substantially real-time as the performance of the check-in operation in certain embodiments.
  • In some embodiments, the check-in operation may identify a location from a plurality of locations that are defined in the social network application and, preferably, includes places of business. The plurality of locations may include user defined locations as directly input via the software on subscriber devices.
  • In some embodiments, the mobile app software provides selections for the user to control visibility of the user's current location (and/or related content) to other users of the social network including friends of the user and customizable lesser subsets of all friends of the user. The user may select specific friends from a list to permit (or prohibit) viewing of the user's current location and location-content. Pre-defined groups or lists of friends may be defined for selection for this purpose.
  • In some embodiments, the mobile app software provides input capabilities to receive one or more comments to be automatically posted to the account of the user, the one or more comments being specifically tied to respective locations identified by functionality of the wireless, telephony subscriber device such that friends of the user as selectively permitted by the user are able to view the one or more comments of the user on a map interface at the respective identified locations in substantially real-time as the user who posted the one or more comments is at the respective location.
  • In some embodiments, the number of check-ins are counted for specific merchants for users of the social network application. Incentive offers are then communicated depending upon the specific number of check-in operations performed by respective users. In this manner, users of the social network may be rewarded for loyalty to specific merchants and for participating in the check-in functionality of the social network application.
  • Also as discussed herein in regard to operations of apps and wireless, telephony subscriber devices, activities of users of the wireless, telephony subscriber devices are preferably logged (e.g., as stored in DB 2118 and/or DB 2116 in FIG. 22) where the logged activities include device use, app use, and even real-world activities as discussed herein. These activities may be inferred from location data and/or device use data. Alternatively, an individual user may explicitly input data to indicate the current activity of the user. The activities may be presented for review by other users and/or may also be employed to select advertisements for users of the social network application.
  • FIG. 24 depicts a user interface that may be provided by suitable software on a wireless device 2111 (e.g., by mobile browser 2201 when it is executing suitable browser executable code or application 2203). The interface includes “check in” button, that when selected, causes the software to communicate a suitable message to the social network application that identifies the current location of the user for use by the social network application. The location may be determined automatically using GPS functionality or other wireless location algorithms. Additionally or alternatively, the user may select a location from list 2302. Additionally or alternatively, the user may define a location via interface for the check in operation. The user may also enter a comment via text control 2303 to be display with the user's current location on the social network application. The visibility of the current location may be controlled using visibility list 2304 to select all users, all friends, a lesser subset of friends (e.g., a number of friends less than the full group of friends), or no visibility at all as desired by the user.
  • In some embodiments, the social network application is adapted to facilitate substantially real-time posting of photos to accounts (e.g., for display via profile pages) taken directly from wireless, telephony subscriber devices of users of the social network application.
  • In some embodiments, first mobile app software for operation on the wireless, telephony subscriber devices is provided for interacting with the social network application to access user accounts of the social network application. The first mobile app software may be browser executable code (e.g., an HTML variant) or a mobile application. Second mobile app software (e.g., software 2202 in FIG. 23) for operation on the wireless, telephony subscriber devices is provided for posting photos taken by the wireless, telephony subscriber devices to user accounts of the social network application. The second mobile app software is adapted to directly interact with camera functionality of the wireless, telephony subscriber devices to transfer a captured photo to at least one social network application server (preferably with photo metadata, that is data entered via data input controls by the user of a respective wireless, telephony subscriber device).
  • The second mobile app software is preferably implemented to function without requiring the respective user to log into the social network application via the first mobile app software to view the user account of the respective user. That is, the user can simply take a picture using the camera functionality of the wireless, telephony subscriber device and then post or transfer the photo to the user's account without requiring the user to interact with the social network application through the conventional user account mechanisms (including navigating to the user's login page, initial web page, selection of a photo tab from the initial web page, etc.).
  • On the server side of the social network application, messages from the second mobile app software are automatically parsed and the photos are automatically posted to users accounts with data entered by the respective users as parsed from the messages (e.g., by photo server software of server platform(s) 2105). Preferably (but not required), the automatically parsing and automatically posting occurs through separate server functionality than provided for web page access of user accounts of the social network application. The photos and messages become available for viewing on the social network application web pages of the respective users in substantially real-time.
  • In some embodiments, maps or map applications are provided in which wireless, telephony subscriber device data is presented over a map of a geographical region (see, e.g., map interface 2600 in FIG. 26). The device data may include subscriber analytic data. Alternatively, the data may include specific subscriber information. The logged activities (current and past activities) of subscribers may be presented on the maps. Also, in some embodiments, subscribers are able to identify specific areas that are excluded from data gathering according to subscriber privacy preferences.
  • In some embodiments, wireless device use data is received from multiple wireless, telephony subscriber devices by the at least one mobile device analytic server. The received wireless device use data is processed to generate subscriber analytic data and other data. Web queries are received from third-parties (e.g., other subscribers, advertisers, or other users). Web pages or web applications are communicated in response to the received web queries according to an internet protocol to the third-parties, including visual presentation of selected data items.
  • In some embodiments, each communicated web page or web application includes a display of a map of a respective geographical region and summary indications of wireless, telephony subscriber devices within the respective geographical region that are currently in use. The maps may further display the summary indications for subscribers that match subscriber or device criteria specified in the corresponding web query. Also, the web page or applications may display summary analytic data specific for different mobile applications employed on multiple, wireless telephony subscriber devices or display specific summary analytic data for different types or groups of mobile applications employed on multiple, wireless telephony subscriber devices. For example, all subscribers currently employing “gaming” applications or “social network” applications may be displayed on the map depending upon the specific supplied criteria. Trending analytics may be employed (e.g., current activity or recent activity data compared to longer-term typical or average analytic behavioral values).
  • When implemented in software, the various elements or components of representative embodiments are the code or software segments adapted to perform the respective tasks when executed on suitable computer hardware. The program or code segments can be stored in a machine readable medium, such as a processor readable medium. The “computer readable medium” may include any medium that can store or transfer information. Examples of the computer readable medium include an random access memory (RAM), electronic circuit, a semiconductor memory device, a ROM, a flash memory, an erasable programmable ROM (EPROM), a floppy diskette, a compact disk CD-ROM, an optical disk, a hard disk, a fiber optic medium. The code segments may be downloaded via computer networks such as the Internet, Intranet, etc.
  • Although representative embodiments and advantages have been described in detail, it should be understood that various changes, substitutions and alterations can be made herein without departing from the spirit and scope of the appended claims. Moreover, the scope of the present application is not intended to be limited to the particular embodiments of the process, machine, manufacture, composition of matter, means, methods and steps described in the specification. As one of ordinary skill in the art will readily appreciate from the disclosure that processes, machines, manufacture, compositions of matter, means, methods, or steps, presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized. Accordingly, the appended claims are intended to include within their scope such processes, machines, manufacture, compositions of matter, means, methods, or steps.
  • This application is related to (1) U.S. patent application Ser. No. 12/463,168, May 8, 2009, which is a continuation of PCT application number PCT/2007/083987, filed 7-NOV.-2007 (published as WO 2008/082794 A2) which claims priority to (i) U.S. patent application Ser. No. 11/559,438, filed 14-NOV.-2006; (ii) U.S. patent application Ser. No. 11/623,832, filed 17-JAN.-2007; (iii) U.S. Provisional Patent Application Ser. No. 60/864,807, filed 08-NOV.-2006; and (iv) U.S. Provisional Patent Application Ser. No. 60/917,638, filed 11-MAY-2007 and (2) is a related to U.S. patent application Ser. No. 12/967,040 which is a continuation-in-part of U.S. patent application Ser. No. 12/767,785, filed Apr. 26, 2010 which is a continuation-in-part U.S. patent application Ser. No. 11/747,286, filed May 11, 2007, which is a continuation-in-part of U.S. patent application Ser. No. 11/623,832, filed Jan. 17, 2007, which is a continuation-in-part of U.S. patent application Ser. No. 11/559,438, filed Nov. 14, 2006 (which claims the benefit of U.S. Provisional Application Ser. No. 60/736,252, filed Nov. 14, 2005, U.S. Provisional Patent Application Ser. No. 60/759,303, filed Jan. 17, 2006 and U.S. Provisional Patent Application Ser. No. 60/773,852, filed Feb. 16, 2006); U.S. patent application Ser. No. 11/623,832 also claims the benefit of U.S. Provisional Patent Application Ser. No. 60/759,303, filed Jan. 17, 2006 and U.S. Provisional Patent Application Ser. No. 60/773,852, filed Feb. 16, 2006. All of the preceding applications are incorporated herein by reference

Claims (2)

1. A method of sharing locations of users participating in a social networking service at a geographic location, the method executed by a computer system and comprising:
receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device;
associating the location information with the text descriptive information of the first user in a database;
sending the text descriptive information and the location information of the first user to a second user for display.
2. A method of conducting social network operations for users participating in a social networking service, the method executed by one or more computer systems and comprising:
providing a mobile application for use on wireless computing devices of users for interaction with one or more servers of hardware and software of the social networking service, wherein the social networking service is adapted to permit a respective user to control a social networking service account to accept other following users to follow activities of the respective user via substantially real time messaging to wireless devices of the following users, wherein the mobile application is adapted to receive manually inputted text descriptive information from a respective user for sharing via the social network service for association with a user selected photo, wherein the mobile application is further operable to communicate geographic data indicative of a current location of the respective user during interaction with the one or more servers of hardware and software of the social networking service;
interacting, by the social networking service, with instances of the mobile application on wireless computing devices of users of the social networking service to receive messages and location information, wherein the interacting comprises: automatically distributing messages received from users using the mobile application to wireless devices of follower users identified in corresponding user accounts of the social networking service in a substantially real time manner from receipt of the respective messages, wherein the distributed messages include photos and manually entered text descriptive information communicated from the mobile application for display to following users; and
providing a substantially real-time ad matching service for providing ads to users of the social networking service, wherein the ad-matching service contextually analyzes text descriptive information in messages for distribution to following users for matching against ad parameters in ad campaigns managed via the ad matching service, wherein ads matched by the ad matching service are communicated in conjunction with distribution of corresponding messages to following users of the social networking service.
US13/969,561 2005-11-14 2013-08-17 Method of conducting social network application operations Abandoned US20140108540A1 (en)

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US73625205P true 2005-11-14 2005-11-14
US75930306P true 2006-01-17 2006-01-17
US77385206P true 2006-02-16 2006-02-16
US86480706P true 2006-11-08 2006-11-08
US11/559,438 US20070112741A1 (en) 2005-11-14 2006-11-14 Search engine providing persistent search functionality over multiple search queries and method for operating the same
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US91763807P true 2007-05-11 2007-05-11
US11/747,286 US20070214180A1 (en) 2005-11-14 2007-05-11 Social network application for processing image or video data from wireless devices of users and methods of operation
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US12/463,168 US20100285818A1 (en) 2009-05-08 2009-05-08 Location based service for directing ads to subscribers
US12/767,785 US20100324994A1 (en) 2005-11-14 2010-04-26 Location based service for directing ads to subscribers
US12/967,040 US8260725B2 (en) 2005-11-14 2010-12-13 Method of conducting operations for a social network application including notification list generation with offer hyperlinks according to notification rules
US13/586,839 US8571999B2 (en) 2005-11-14 2012-08-15 Method of conducting operations for a social network application including activity list generation
US13/969,561 US20140108540A1 (en) 2005-11-14 2013-08-17 Method of conducting social network application operations

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Cited By (19)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120102165A1 (en) * 2010-10-21 2012-04-26 International Business Machines Corporation Crowdsourcing location based applications and structured data for location based applications
US20130086160A1 (en) * 2011-09-29 2013-04-04 Shyam Sundar RAJARAM Social and contextual recommendations
US20130182603A1 (en) * 2010-09-29 2013-07-18 British Telecommunications Public Limited Company Method of determining location
US20140222577A1 (en) * 2006-03-17 2014-08-07 Raj Abhyanker Campaign in a geo-spatial environment
US8965409B2 (en) 2006-03-17 2015-02-24 Fatdoor, Inc. User-generated community publication in an online neighborhood social network
US9004396B1 (en) 2014-04-24 2015-04-14 Fatdoor, Inc. Skyteboard quadcopter and method
US9022324B1 (en) 2014-05-05 2015-05-05 Fatdoor, Inc. Coordination of aerial vehicles through a central server
US9037516B2 (en) 2006-03-17 2015-05-19 Fatdoor, Inc. Direct mailing in a geo-spatial environment
US9064288B2 (en) 2006-03-17 2015-06-23 Fatdoor, Inc. Government structures and neighborhood leads in a geo-spatial environment
US9070101B2 (en) 2007-01-12 2015-06-30 Fatdoor, Inc. Peer-to-peer neighborhood delivery multi-copter and method
US9071367B2 (en) 2006-03-17 2015-06-30 Fatdoor, Inc. Emergency including crime broadcast in a neighborhood social network
US9098545B2 (en) 2007-07-10 2015-08-04 Raj Abhyanker Hot news neighborhood banter in a geo-spatial social network
US9373149B2 (en) 2006-03-17 2016-06-21 Fatdoor, Inc. Autonomous neighborhood vehicle commerce network and community
US9439367B2 (en) 2014-02-07 2016-09-13 Arthi Abhyanker Network enabled gardening with a remotely controllable positioning extension
US9441981B2 (en) 2014-06-20 2016-09-13 Fatdoor, Inc. Variable bus stops across a bus route in a regional transportation network
US9451020B2 (en) 2014-07-18 2016-09-20 Legalforce, Inc. Distributed communication of independent autonomous vehicles to provide redundancy and performance
US9457901B2 (en) 2014-04-22 2016-10-04 Fatdoor, Inc. Quadcopter with a printable payload extension system and method
US9459622B2 (en) 2007-01-12 2016-10-04 Legalforce, Inc. Driverless vehicle commerce network and community
US9971985B2 (en) 2014-06-20 2018-05-15 Raj Abhyanker Train based community

Families Citing this family (33)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140019542A1 (en) * 2003-08-20 2014-01-16 Ip Holdings, Inc. Social Networking System and Behavioral Web
US8843560B2 (en) * 2006-04-28 2014-09-23 Yahoo! Inc. Social networking for mobile devices
US7809805B2 (en) 2007-02-28 2010-10-05 Facebook, Inc. Systems and methods for automatically locating web-based social network members
US9183571B2 (en) * 2007-09-14 2015-11-10 Qualcomm Incorporated System and method for providing advertisement data to a mobile computing device
US9378507B2 (en) * 2009-06-17 2016-06-28 1020, Inc. System and method of disseminating electronic content utilizing geographic and time granularities
US9119027B2 (en) * 2009-10-06 2015-08-25 Facebook, Inc. Sharing of location-based content item in social networking service
EP2343866B1 (en) * 2010-01-11 2016-03-30 Vodafone Holding GmbH Network-based system for social interactions between users
US9201952B1 (en) * 2010-12-21 2015-12-01 Google Inc. User interface for activity status and history
US9448961B1 (en) 2011-10-18 2016-09-20 Google Inc. Prioritized download of social network content
US9342209B1 (en) * 2012-08-23 2016-05-17 Audible, Inc. Compilation and presentation of user activity information
US10032233B2 (en) * 2012-10-17 2018-07-24 Facebook, Inc. Social context in augmented reality
US20140113652A1 (en) * 2012-10-24 2014-04-24 Yael G. Maguire Sensing Distance Between Wireless Devices Using Multiple Scales of Controlled Bandwidth
US20140236731A1 (en) * 2013-02-21 2014-08-21 Adobe Systems Incorporated Using Interaction Data of Application Users to Target a Social-Networking Advertisement
US9530168B2 (en) * 2013-03-28 2016-12-27 Linkedin Corporation Reducing churn rate for a social network service
US9323852B2 (en) 2013-09-20 2016-04-26 Bank Of America Corporation Activity list filters for a financial and social management system
US9324115B2 (en) 2013-09-20 2016-04-26 Bank Of America Corporation Activity review for a financial and social management system
US9324114B2 (en) 2013-09-20 2016-04-26 Bank Of America Corporation Interactive map for grouped activities within a financial and social management system
US20150088718A1 (en) * 2013-09-20 2015-03-26 Bank Of America Corporation Past packages for a financial and social management system
US9934536B2 (en) 2013-09-20 2018-04-03 Bank Of America Corporation Interactive map for grouped activities within a financial and social management system
US10002395B2 (en) 2013-09-20 2018-06-19 Bank Of America Corporation Interactive mapping system for user experience augmentation
US9786018B2 (en) 2013-09-20 2017-10-10 Bank Of America Corporation Activity list enhanced with images for a financial and social management system
US9786019B2 (en) 2013-09-20 2017-10-10 Bank Of America Corporation Grouped packages for a financial and social management system
US10157407B2 (en) 2013-10-29 2018-12-18 Elwha Llc Financier-facilitated guaranty provisioning
US20150120530A1 (en) * 2013-10-29 2015-04-30 Elwha LLC, a limited liability corporation of the State of Delaware Guaranty provisioning via social networking
US20150134371A1 (en) * 2013-11-12 2015-05-14 Stubhub, Inc. Systems and methods for automatic scrapbook generation
US9883004B2 (en) * 2013-11-25 2018-01-30 Google Llc Systems and methods for generating a viewer-specific visitor history for a location
US9672291B2 (en) 2014-02-19 2017-06-06 Google Inc. Summarizing social interactions between users
US10147102B2 (en) * 2014-03-31 2018-12-04 Paypal, Inc. Person/group check-in system
US9838502B2 (en) * 2014-08-06 2017-12-05 Michael D. CROFT Systems and methods for RWD app store based collaborative enterprise information management
US9509857B2 (en) 2014-12-10 2016-11-29 Google Inc. Mobile device push notification using mobile application usage history
US10015721B2 (en) * 2015-10-16 2018-07-03 At&T Mobility Ii Llc Mobile application testing engine
US9679426B1 (en) 2016-01-04 2017-06-13 Bank Of America Corporation Malfeasance detection based on identification of device signature
US10171496B2 (en) * 2016-01-19 2019-01-01 Cisco Technology, Inc. Beacon spoofing prevention

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070174117A1 (en) * 2006-01-23 2007-07-26 Microsoft Corporation Advertising that is relevant to a person
US20080104227A1 (en) * 2006-11-01 2008-05-01 Yahoo! Inc. Searching and route mapping based on a social network, location, and time

Family Cites Families (478)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6937998B1 (en) 1987-12-28 2005-08-30 Symbol Technologies, Inc. Arrangement for and method of expediting transactions based on a customer's proximity to the transactions
US6076733A (en) 1993-11-24 2000-06-20 Metrologic Instruments, Inc. Web-based system and method for enabling a viewer to access and display HTML-encoded documents located on the world wide web (WWW) by reading URL-encoded bar code symbols printed on a web-based information resource guide
US5671436A (en) 1991-08-21 1997-09-23 Norand Corporation Versatile RF data capture system
US6535890B2 (en) 1999-11-16 2003-03-18 Aircraft Technical Publishers Computer aided maintenance and repair information system for equipment subject to regulatory compliance
US5603081A (en) 1993-11-01 1997-02-11 Telefonaktiebolaget Lm Ericsson Method for communicating in a wireless communication system
US20020198791A1 (en) 1999-04-21 2002-12-26 Perkowski Thomas J. Internet-based consumer product brand marketing communication system which enables manufacturers, retailers and their respective agents, and consumers to carry out product-related functions along the demand side of the retail chain in an integrated manner
GB9419860D0 (en) 1994-10-03 1994-11-16 Stack Ltd Vehicle travel meter
US5937413A (en) 1994-11-30 1999-08-10 Electronics And Telecommunications Research Institure Data audits based on timestamp criteria in replicated data bases within digital mobile telecommunication system
US5963940A (en) 1995-08-16 1999-10-05 Syracuse University Natural language information retrieval system and method
US5689547A (en) 1995-11-02 1997-11-18 Ericsson Inc. Network directory methods and systems for a cellular radiotelephone
US6993494B1 (en) 1998-06-01 2006-01-31 Harrah's Operating Company, Inc. Resource price management incorporating indirect value
US6745194B2 (en) 2000-08-07 2004-06-01 Alta Vista Company Technique for deleting duplicate records referenced in an index of a database
US6837436B2 (en) 1996-09-05 2005-01-04 Symbol Technologies, Inc. Consumer interactive shopping system
US5926624A (en) 1996-09-12 1999-07-20 Audible, Inc. Digital information library and delivery system with logic for generating files targeted to the playback device
US6253188B1 (en) 1996-09-20 2001-06-26 Thomson Newspapers, Inc. Automated interactive classified ad system for the internet
US5948061A (en) 1996-10-29 1999-09-07 Double Click, Inc. Method of delivery, targeting, and measuring advertising over networks
US6285987B1 (en) 1997-01-22 2001-09-04 Engage, Inc. Internet advertising system
US5996011A (en) 1997-03-25 1999-11-30 Unified Research Laboratories, Inc. System and method for filtering data received by a computer system
US6742047B1 (en) 1997-03-27 2004-05-25 Intel Corporation Method and apparatus for dynamically filtering network content
US5907831A (en) 1997-04-04 1999-05-25 Lotvin; Mikhail Computer apparatus and methods supporting different categories of users
KR19980076633A (en) 1997-04-11 1998-11-16 윤종용 Search in a mobile information terminal apparatus and method
US6516416B2 (en) 1997-06-11 2003-02-04 Prism Resources Subscription access system for use with an untrusted network
US6029141A (en) 1997-06-27 2000-02-22 Amazon.Com, Inc. Internet-based customer referral system
US6097939A (en) 1997-07-11 2000-08-01 Compaq Computer Corporation Method and apparatus for event data maintenance per MIN/ESN pair in a mobile telephone system
US6664922B1 (en) 1997-08-28 2003-12-16 At Road, Inc. Method for distributing location-relevant information using a network
US6327470B1 (en) 1997-11-07 2001-12-04 Ericsson Inc. Handover between fixed and mobile networks for dual mode phones
US6247047B1 (en) 1997-11-18 2001-06-12 Control Commerce, Llc Method and apparatus for facilitating computer network transactions
US6092100A (en) 1997-11-21 2000-07-18 International Business Machines Corporation Method for intelligently resolving entry of an incorrect uniform resource locator (URL)
US5973683A (en) 1997-11-24 1999-10-26 International Business Machines Corporation Dynamic regulation of television viewing content based on viewer profile and viewing history
US6029139A (en) 1998-01-28 2000-02-22 Ncr Corporation Method and apparatus for optimizing promotional sale of products based upon historical data
EP1062602B8 (en) 1998-02-13 2018-06-13 Oath Inc. Search engine using sales and revenue to weight search results
US6799298B2 (en) 1998-03-11 2004-09-28 Overture Services, Inc. Technique for locating an item of interest within a stored representation of data
US6434532B2 (en) 1998-03-12 2002-08-13 Aladdin Knowledge Systems, Ltd. Interactive customer support for computer programs using network connection of user machine
US6421675B1 (en) 1998-03-16 2002-07-16 S. L. I. Systems, Inc. Search engine
US6226510B1 (en) 1998-03-19 2001-05-01 American Secure Care, Llc Emergency phone for automatically summoning multiple emergency response services
US6246997B1 (en) 1998-03-26 2001-06-12 International Business Machines Corp. Electronic commerce site with query interface
US6061658A (en) 1998-05-14 2000-05-09 International Business Machines Corporation Prospective customer selection using customer and market reference data
US6182050B1 (en) 1998-05-28 2001-01-30 Acceleration Software International Corporation Advertisements distributed on-line using target criteria screening with method for maintaining end user privacy
US6006225A (en) 1998-06-15 1999-12-21 Amazon.Com Refining search queries by the suggestion of correlated terms from prior searches
US6573883B1 (en) 1998-06-24 2003-06-03 Hewlett Packard Development Company, L.P. Method and apparatus for controlling a computing device with gestures
US6665837B1 (en) 1998-08-10 2003-12-16 Overture Services, Inc. Method for identifying related pages in a hyperlinked database
US6226618B1 (en) 1998-08-13 2001-05-01 International Business Machines Corporation Electronic content delivery system
US6141341A (en) 1998-09-09 2000-10-31 Motorola, Inc. Voice over internet protocol telephone system and method
US6317722B1 (en) 1998-09-18 2001-11-13 Amazon.Com, Inc. Use of electronic shopping carts to generate personal recommendations
US6446076B1 (en) 1998-11-12 2002-09-03 Accenture Llp. Voice interactive web-based agent system responsive to a user location for prioritizing and formatting information
US6487538B1 (en) 1998-11-16 2002-11-26 Sun Microsystems, Inc. Method and apparatus for local advertising
US6216129B1 (en) 1998-12-03 2001-04-10 Expanse Networks, Inc. Advertisement selection system supporting discretionary target market characteristics
US6577861B2 (en) 1998-12-14 2003-06-10 Fujitsu Limited Electronic shopping system utilizing a program downloadable wireless telephone
US6512919B2 (en) 1998-12-14 2003-01-28 Fujitsu Limited Electronic shopping system utilizing a program downloadable wireless videophone
US6564327B1 (en) 1998-12-23 2003-05-13 Worldcom, Inc. Method of and system for controlling internet access
US6135349A (en) 1999-02-01 2000-10-24 First Data Corporation System and method for enabling a merchant to apply for a credit card processing account using the internet
US6651053B1 (en) 1999-02-01 2003-11-18 Barpoint.Com, Inc. Interactive system for investigating products on a network
US20060178986A1 (en) 2000-02-17 2006-08-10 Giordano Joseph A System and method for processing financial transactions using multi-payment preferences
US6199099B1 (en) 1999-03-05 2001-03-06 Ac Properties B.V. System, method and article of manufacture for a mobile communication network utilizing a distributed communication network
US6356905B1 (en) 1999-03-05 2002-03-12 Accenture Llp System, method and article of manufacture for mobile communication utilizing an interface support framework
US6907566B1 (en) 1999-04-02 2005-06-14 Overture Services, Inc. Method and system for optimum placement of advertisements on a webpage
US6963850B1 (en) 1999-04-09 2005-11-08 Amazon.Com, Inc. Computer services for assisting users in locating and evaluating items in an electronic catalog based on actions performed by members of specific user communities
US20040220926A1 (en) 2000-01-03 2004-11-04 Interactual Technologies, Inc., A California Cpr[P Personalization services for entities from multiple sources
US6519585B1 (en) 1999-04-27 2003-02-11 Infospace, Inc. System and method for facilitating presentation of subject categorizations for use in an on-line search query engine
US6625732B1 (en) 1999-04-29 2003-09-23 Charles R Weirauch Method for tracking the devices used to load, read, and write removable storage media
US6336117B1 (en) 1999-04-30 2002-01-01 International Business Machines Corporation Content-indexing search system and method providing search results consistent with content filtering and blocking policies implemented in a blocking engine
US6609113B1 (en) 1999-05-03 2003-08-19 The Chase Manhattan Bank Method and system for processing internet payments using the electronic funds transfer network
US6339761B1 (en) 1999-05-13 2002-01-15 Hugh V. Cottingham Internet service provider advertising system
US6269361B1 (en) 1999-05-28 2001-07-31 Goto.Com System and method for influencing a position on a search result list generated by a computer network search engine
US7231358B2 (en) 1999-05-28 2007-06-12 Overture Services, Inc. Automatic flight management in an online marketplace
US7013292B1 (en) 1999-06-10 2006-03-14 Felicite.Com Inc. Method and system for universal gift registry
US7512551B2 (en) 1999-06-23 2009-03-31 Signature Systems Llc Method and system for implementing a search engine with reward components and payment components
US20020087408A1 (en) 1999-06-25 2002-07-04 Burnett Jonathan Robert System for providing information to intending consumers
US20050075932A1 (en) 1999-07-07 2005-04-07 Mankoff Jeffrey W. Delivery, organization, and redemption of virtual offers from the internet, interactive-tv, wireless devices and other electronic means
US6559828B1 (en) 1999-08-13 2003-05-06 Clothing Plus Oy User interface for selecting functions in an electronic hardware
US7062453B1 (en) 1999-08-31 2006-06-13 Interchange Corporation Methods and systems for a dynamic networked commerce architecture
US20020052781A1 (en) 1999-09-10 2002-05-02 Avantgo, Inc. Interactive advertisement mechanism on a mobile device
US6829475B1 (en) 1999-09-22 2004-12-07 Motorola, Inc. Method and apparatus for saving enhanced information contained in content sent to a wireless communication device
US6556997B1 (en) 1999-10-07 2003-04-29 Comverse Ltd. Information retrieval system
US6807574B1 (en) 1999-10-22 2004-10-19 Tellme Networks, Inc. Method and apparatus for content personalization over a telephone interface
US6615172B1 (en) 1999-11-12 2003-09-02 Phoenix Solutions, Inc. Intelligent query engine for processing voice based queries
AUPQ439299A0 (en) 1999-12-01 1999-12-23 Silverbrook Research Pty Ltd Interface system
US6704787B1 (en) 1999-12-03 2004-03-09 Intercard Payments, Inc. Date of birth authentication system and method using demographic and/or geographic data supplied by a subscriber that is verified by a third party
US6963867B2 (en) 1999-12-08 2005-11-08 A9.Com, Inc. Search query processing to provide category-ranked presentation of search results
US6480837B1 (en) 1999-12-16 2002-11-12 International Business Machines Corporation Method, system, and program for ordering search results using a popularity weighting
US6834195B2 (en) 2000-04-04 2004-12-21 Carl Brock Brandenberg Method and apparatus for scheduling presentation of digital content on a personal communication device
CA2362416C (en) 2000-01-05 2009-08-04 Mitsubishi Denki Kabushiki Kaisha Keyword extracting device
AU2941701A (en) 2000-01-14 2001-07-24 Airomedia Inc System and method for location-based stimuli motivated information delivery
US6772340B1 (en) 2000-01-14 2004-08-03 Microsoft Corporation Digital rights management system operating on computing device and having black box tied to computing device
US6546388B1 (en) 2000-01-14 2003-04-08 International Business Machines Corporation Metadata search results ranking system
US6704727B1 (en) 2000-01-31 2004-03-09 Overture Services, Inc. Method and system for generating a set of search terms
US7047033B2 (en) 2000-02-01 2006-05-16 Infogin Ltd Methods and apparatus for analyzing, processing and formatting network information such as web-pages
US6775537B1 (en) 2000-02-04 2004-08-10 Nokia Corporation Apparatus, and associated method, for facilitating net-searching operations performed by way of a mobile station
US6775831B1 (en) 2000-02-11 2004-08-10 Overture Services, Inc. System and method for rapid completion of data processing tasks distributed on a network
US7136860B2 (en) 2000-02-14 2006-11-14 Overture Services, Inc. System and method to determine the validity of an interaction on a network
US6669087B2 (en) 2000-02-14 2003-12-30 Intermec Ip Corp. Method and apparatus for accessing product information using bar code data
EP1264477A4 (en) 2000-02-23 2003-10-01 Penta Trading Ltd Systems and methods for generating and providing previews of electronic files such as web files
EP1258111A2 (en) 2000-02-24 2002-11-20 mBlox Ltd. A system and method for providing information services to a mobile device user
FI112433B (en) 2000-02-29 2003-11-28 Nokia Corp Location-bound services
US6996538B2 (en) 2000-03-07 2006-02-07 Unisone Corporation Inventory control system and methods
US20010054001A1 (en) 2000-03-10 2001-12-20 Robinson Gary B. System and method for advertising
US6961584B2 (en) 2000-03-22 2005-11-01 Mlr, Llc Tiered wireless, multi-modal access system and method
WO2001075728A1 (en) 2000-03-30 2001-10-11 I411, Inc. Methods and systems for enabling efficient retrieval of data from data collections
AU4976801A (en) 2000-04-02 2001-10-15 Tangis Corp Soliciting information based on a computer user's context
US6697730B2 (en) 2000-04-04 2004-02-24 Georgia Tech Research Corp. Communications and computing based urban transit system
US7155415B2 (en) 2000-04-07 2006-12-26 Movielink Llc Secure digital content licensing system and method
US6718365B1 (en) 2000-04-13 2004-04-06 International Business Machines Corporation Method, system, and program for ordering search results using an importance weighting
US20030084098A1 (en) 2000-04-13 2003-05-01 Daniel Lavin Navigation server for use with, for example, a wireless web access device having a navigation control unit
AU5163401A (en) 2000-04-17 2001-10-30 Emtera Corp System and method for wireless purchases of goods and services
US6526275B1 (en) 2000-04-24 2003-02-25 Motorola, Inc. Method for informing a user of a communication device where to obtain a product and communication system employing same
JP2001312497A (en) 2000-04-28 2001-11-09 Yamaha Corp Content generating device, content distribution system, device and method for content reproduction, and storage medium
US20020046104A1 (en) 2000-05-09 2002-04-18 Geomicro, Inc. Method and apparatus for generating targeted impressions to internet clients
US20010051911A1 (en) 2000-05-09 2001-12-13 Marks Michael B. Bidding method for internet/wireless advertising and priority ranking in search results
US7725525B2 (en) 2000-05-09 2010-05-25 James Duncan Work Method and apparatus for internet-based human network brokering
US6876997B1 (en) 2000-05-22 2005-04-05 Overture Services, Inc. Method and apparatus for indentifying related searches in a database search system
AU773351B2 (en) 2000-05-31 2004-05-20 Ntt Docomo, Inc. Method and system for distributing advertisements over network
US20010054066A1 (en) 2000-06-13 2001-12-20 Louis Spitzer Apparatus and method for transmitting information from signage to portable computing device, and system utilizing same
AR029290A1 (en) 2000-06-28 2003-06-18 American Express Travel Relate System and method for integrating public and private data
US7487112B2 (en) 2000-06-29 2009-02-03 Barnes Jr Melvin L System, method, and computer program product for providing location based services and mobile e-commerce
KR20010007743A (en) 2000-07-27 2001-02-05 이승열 WAP connecting method using guidecode inserted an advertisement
US6968179B1 (en) 2000-07-27 2005-11-22 Microsoft Corporation Place specific buddy list services
US6647269B2 (en) 2000-08-07 2003-11-11 Telcontar Method and system for analyzing advertisements delivered to a mobile unit
US6954641B2 (en) 2000-08-14 2005-10-11 Vesivius, Inc. Communique wireless subscriber device for a cellular communication network
WO2002015102A1 (en) 2000-08-15 2002-02-21 Extreming, Inc. E-commerce enabling virtual streaming multimedia server, system, method and article
WO2002015051A1 (en) 2000-08-16 2002-02-21 Verisign, Inc. A numeric/voice name internet access architecture and methodology
GB2371178B (en) 2000-08-22 2003-08-06 Symbian Ltd A method of enabling a wireless information device to access data services
CA2420215A1 (en) 2000-08-23 2002-06-27 Neurogen Corporation High affinity small molecule c5a receptor modulators
US6950994B2 (en) 2000-08-31 2005-09-27 Yahoo! Inc. Data list transmutation and input mapping
US6892206B2 (en) 2000-08-31 2005-05-10 Yahoo! Inc. Reduction of meta data in a network
US7155508B2 (en) 2000-09-01 2006-12-26 Yodlee.Com, Inc. Target information generation and ad server
US7792539B2 (en) 2000-09-06 2010-09-07 Eric Inselberg Method and apparatus for interactive audience participation at a live entertainment event
US20020073420A1 (en) 2000-09-07 2002-06-13 Incomkorea Co., Ltd. Method for transmitting advertisements via electronic mails
US20020062310A1 (en) 2000-09-18 2002-05-23 Smart Peer Llc Peer-to-peer commerce system
US6701317B1 (en) 2000-09-19 2004-03-02 Overture Services, Inc. Web page connectivity server construction
US6374177B1 (en) 2000-09-20 2002-04-16 Motorola, Inc. Method and apparatus for providing navigational services in a wireless communication device
US7007239B1 (en) 2000-09-21 2006-02-28 Palm, Inc. Method and apparatus for accessing a contacts database and telephone services
JP2002101060A (en) 2000-09-22 2002-04-05 Pioneer Electronic Corp Advertisement information providing apparatus
US7089036B2 (en) 2000-10-03 2006-08-08 Cingular Wireless Ii, Llc Location information erase on SIM cards
US20030079222A1 (en) 2000-10-06 2003-04-24 Boykin Patrick Oscar System and method for distributing perceptually encrypted encoded files of music and movies
US20070112645A1 (en) 2000-10-11 2007-05-17 Ebay Inc. Sales system with sales activity feedback
US6904408B1 (en) 2000-10-19 2005-06-07 Mccarthy John Bionet method, system and personalized web content manager responsive to browser viewers' psychological preferences, behavioral responses and physiological stress indicators
US6560600B1 (en) 2000-10-25 2003-05-06 Alta Vista Company Method and apparatus for ranking Web page search results
US20020051521A1 (en) 2000-10-27 2002-05-02 Patrick R. Scott Communication service with advertisement
US20020053076A1 (en) 2000-10-30 2002-05-02 Mark Landesmann Buyer-driven targeting of purchasing entities
US20030158776A1 (en) 2000-10-30 2003-08-21 Mark Landesmann Buyer-driven targeting of purchasing entities
JP4095243B2 (en) 2000-11-28 2008-06-04 キヤノン株式会社 Url acquisition and processing system and method and storage medium storing a program for executing the process.
US20050086112A1 (en) 2000-11-28 2005-04-21 Roy Shkedi Super-saturation method for information-media
US20020065713A1 (en) 2000-11-29 2002-05-30 Awada Faisal M. Coupon delivery via mobile phone based on location
US6957390B2 (en) * 2000-11-30 2005-10-18 Mediacom.Net, Llc Method and apparatus for providing dynamic information to a user via a visual display
US20020078045A1 (en) 2000-12-14 2002-06-20 Rabindranath Dutta System, method, and program for ranking search results using user category weighting
US20050171863A1 (en) 2000-12-15 2005-08-04 Hagen Philip A. System and computerized method for classified ads
US6959436B2 (en) 2000-12-15 2005-10-25 Innopath Software, Inc. Apparatus and methods for intelligently providing applications and data on a mobile device system
US20020077897A1 (en) 2000-12-19 2002-06-20 Zellner Samuel N. Identity blocking service from a web advertiser
US20030006911A1 (en) 2000-12-22 2003-01-09 The Cadre Group Inc. Interactive advertising system and method
US20040068552A1 (en) 2001-12-26 2004-04-08 David Kotz Methods and apparatus for personalized content presentation
US20020123928A1 (en) 2001-01-11 2002-09-05 Eldering Charles A. Targeting ads to subscribers based on privacy-protected subscriber profiles
US7289623B2 (en) 2001-01-16 2007-10-30 Utbk, Inc. System and method for an online speaker patch-through
US7035811B2 (en) 2001-01-23 2006-04-25 Intimate Brands, Inc. System and method for composite customer segmentation
US7027987B1 (en) 2001-02-07 2006-04-11 Google Inc. Voice interface for a search engine
US6778834B2 (en) 2001-02-27 2004-08-17 Nokia Corporation Push content filtering
US6778975B1 (en) 2001-03-05 2004-08-17 Overture Services, Inc. Search engine for selecting targeted messages
WO2002076003A2 (en) 2001-03-19 2002-09-26 Imesh Ltd. System and method for peer-to-peer file exchange mechanism from multiple sources
US6889054B2 (en) 2001-03-29 2005-05-03 International Business Machines Corporation Method and system for schedule based advertising on a mobile phone
US20020143860A1 (en) 2001-03-31 2002-10-03 Koninklijke Philips Electronics N. V. Machine readable label reader system with versatile default mode
US20020156677A1 (en) 2001-04-18 2002-10-24 Peters Marcia L. Method and system for providing targeted advertising in public places and carriers
US6968178B2 (en) 2001-04-27 2005-11-22 Hewlett-Packard Development Company, L.P. Profiles for information acquisition by devices in a wireless network
US6944447B2 (en) 2001-04-27 2005-09-13 Accenture Llp Location-based services
US7219309B2 (en) 2001-05-02 2007-05-15 Bitstream Inc. Innovations for the display of web pages
US20020169654A1 (en) 2001-05-08 2002-11-14 Santos Cipriano A. Method and system of determining differential promotion allocations
US6920448B2 (en) 2001-05-09 2005-07-19 Agilent Technologies, Inc. Domain specific knowledge-based metasearch system and methods of using
US6728731B2 (en) 2001-05-15 2004-04-27 Yahoo!, Inc. Method and apparatus for accessing targeted, personalized voice/audio web content through wireless devices
US6727930B2 (en) 2001-05-18 2004-04-27 Hewlett-Packard Development Company, L.P. Personal digital assistant with streaming information display
US7376591B2 (en) 2001-06-07 2008-05-20 Owens Cstephani D Interactive internet shopping and data integration method and system
US7421411B2 (en) 2001-07-06 2008-09-02 Nokia Corporation Digital rights management in a mobile communications environment
US20030020749A1 (en) 2001-07-10 2003-01-30 Suhayya Abu-Hakima Concept-based message/document viewer for electronic communications and internet searching
US20030014659A1 (en) 2001-07-16 2003-01-16 Koninklijke Philips Electronics N.V. Personalized filter for Web browsing
US7793326B2 (en) 2001-08-03 2010-09-07 Comcast Ip Holdings I, Llc Video and digital multimedia aggregator
US6996393B2 (en) 2001-08-31 2006-02-07 Nokia Corporation Mobile content delivery system
US7007074B2 (en) 2001-09-10 2006-02-28 Yahoo! Inc. Targeted advertisements using time-dependent key search terms
CN1202683C (en) 2001-09-25 2005-05-18 华为技术有限公司 Communication function control method of mobile phone
US20030130887A1 (en) 2001-10-03 2003-07-10 Thurston Nathaniel Non-deterministic method and system for the optimization of a targeted content delivery
JP3975720B2 (en) 2001-10-23 2007-09-12 株式会社日立製作所 Ic card, customer information analysis system and customer information analysis results providing method
US20030100320A1 (en) 2001-10-31 2003-05-29 Peeyush Ranjan Efficient hyperlinks for transmitted hyperlinked information
US7497369B2 (en) 2001-10-31 2009-03-03 Amazon.Com, Inc. Metadata service that supports user-to-user sales via third party web pages
US6996579B2 (en) 2001-11-02 2006-02-07 At&T Corp. E-coupon service for location-aware mobile commerce which determines whether to supply requested e-coupons based on the number of requests received in a processing cycle, and a threshold number of requests required to make expected returns from redeemed coupons greater than advertising fees
US20030093311A1 (en) 2001-11-05 2003-05-15 Kenneth Knowlson Targeted advertising
US6826572B2 (en) 2001-11-13 2004-11-30 Overture Services, Inc. System and method allowing advertisers to manage search listings in a pay for placement search system using grouping
US7487262B2 (en) 2001-11-16 2009-02-03 At & T Mobility Ii, Llc Methods and systems for routing messages through a communications network based on message content
US7159194B2 (en) 2001-11-30 2007-01-02 Palm, Inc. Orientation dependent functionality of an electronic device
US20030135825A1 (en) 2001-12-05 2003-07-17 Matthew Gertner Dynamically generated mark-up based graphical user interfaced with an extensible application framework with links to enterprise resources
US7020654B1 (en) 2001-12-05 2006-03-28 Sun Microsystems, Inc. Methods and apparatus for indexing content
US7062258B1 (en) 2001-12-06 2006-06-13 Oracle International Corporation Wallet for storage of information for automated entry into forms of mobile applications
US20030115318A1 (en) 2001-12-13 2003-06-19 Microsoft Corporation. Concentric user-targeting delivery system and methods
AUPR947701A0 (en) 2001-12-14 2002-01-24 Activesky, Inc. Digital multimedia publishing system for wireless devices
US20030135582A1 (en) 2001-12-21 2003-07-17 Docomo Communications Laboratories Usa, Inc. Context aware search service
US20030126095A1 (en) 2001-12-28 2003-07-03 Docomo Communications Laboratories Usa, Inc. Context-aware market-making service
US6978264B2 (en) 2002-01-03 2005-12-20 Microsoft Corporation System and method for performing a search and a browse on a query
US20030135581A1 (en) 2002-01-15 2003-07-17 Jeffrey Phelan Method and apparatus for distributing information based on a geographic location determined for the information
US7484007B2 (en) 2002-02-01 2009-01-27 Codekko Inc. System and method for partial data compression and data transfer
US7203907B2 (en) 2002-02-07 2007-04-10 Sap Aktiengesellschaft Multi-modal synchronization
JP3924476B2 (en) 2002-02-26 2007-06-06 富士通株式会社 Image data processing system
US6813489B1 (en) 2002-03-01 2004-11-02 Yahoo! Inc. System and method for mobile electronic messaging
US9087319B2 (en) 2002-03-11 2015-07-21 Oracle America, Inc. System and method for designing, developing and implementing internet service provider architectures
US20040203630A1 (en) 2002-03-15 2004-10-14 Wang Charles Chuanming Method and apparatus for targeting service delivery to mobile devices
JP3863053B2 (en) 2002-04-12 2006-12-27 シャープ株式会社 Information distribution method, information distribution apparatus, information distribution program and computer-readable recording medium it
US7145457B2 (en) 2002-04-18 2006-12-05 Computer Associates Think, Inc. Integrated visualization of security information for an individual
US20040203854A1 (en) 2002-04-26 2004-10-14 Nowak Steven P. Formatting location information based on output device specifications
JP4166503B2 (en) 2002-05-13 2008-10-15 ヒューレット・パッカード・カンパニーHewlett−Packard Company The information processing system based on the identification code
US7015817B2 (en) 2002-05-14 2006-03-21 Shuan Michael Copley Personal tracking device
CA2388150A1 (en) 2002-05-29 2003-11-29 Ibm Canada Limited-Ibm Canada Limitee Toggleable widget for a user interface
US20030225632A1 (en) 2002-05-30 2003-12-04 Vincent Tong Method and system for providing personalized online shopping service
US20050144073A1 (en) 2002-06-05 2005-06-30 Lawrence Morrisroe Method and system for serving advertisements
US6752300B2 (en) 2002-06-06 2004-06-22 Fobus International Ltd. Holster for a handgun
US7668816B2 (en) 2002-06-11 2010-02-23 Microsoft Corporation Dynamically updated quick searches and strategies
WO2004003705A2 (en) 2002-06-27 2004-01-08 Small World Productions, Inc. System and method for locating and notifying a user of a person, place or thing having attributes matching the user's stated prefernces
US7209915B1 (en) 2002-06-28 2007-04-24 Microsoft Corporation Method, system and apparatus for routing a query to one or more providers
US7130923B2 (en) 2002-07-01 2006-10-31 Avaya Technology Corp. Method and apparatus for guessing correct URLs using tree matching
US7277718B2 (en) 2002-07-22 2007-10-02 Cingular Wireless Ii, Llc Methods and apparatus for formatting information for a communication
US20040019478A1 (en) 2002-07-29 2004-01-29 Electronic Data Systems Corporation Interactive natural language query processing system and method
CA2494122A1 (en) 2002-07-31 2004-02-12 Truecontext Corporation Contextual computing system
US7200413B2 (en) 2002-07-31 2007-04-03 Interchange Corporation Methods and system for enhanced directory assistance using wireless messaging protocols
US7599911B2 (en) 2002-08-05 2009-10-06 Yahoo! Inc. Method and apparatus for search ranking using human input and automated ranking
US20040044571A1 (en) 2002-08-27 2004-03-04 Bronnimann Eric Robert Method and system for providing advertising listing variance in distribution feeds over the internet to maximize revenue to the advertising distributor
CN1679028A (en) 2002-08-29 2005-10-05 松下电器产业株式会社 Content processing apparatus and content display apparatus
US6832259B2 (en) 2002-08-29 2004-12-14 Motorola, Inc. Dynamic adjustment of transmitted data size for a subscriber device
US6983280B2 (en) 2002-09-13 2006-01-03 Overture Services Inc. Automated processing of appropriateness determination of content for search listings in wide area network searches
CN1685348A (en) 2002-09-18 2005-10-19 Nds有限公司 System for multimedia viewing based on entitlements
US7716161B2 (en) 2002-09-24 2010-05-11 Google, Inc, Methods and apparatus for serving relevant advertisements
US20040122735A1 (en) 2002-10-09 2004-06-24 Bang Technologies, Llc System, method and apparatus for an integrated marketing vehicle platform
US7184020B2 (en) 2002-10-30 2007-02-27 Matsushita Electric Industrial Co., Ltd. Operation instructing device, operation instructing method, and operation instructing program
US7249123B2 (en) 2002-10-31 2007-07-24 International Business Machines Corporation System and method for building social networks based on activity around shared virtual objects
US20040088177A1 (en) 2002-11-04 2004-05-06 Electronic Data Systems Corporation Employee performance management method and system
US20040098370A1 (en) 2002-11-15 2004-05-20 Bigchampagne, Llc Systems and methods to monitor file storage and transfer on a peer-to-peer network
AU2003285702A1 (en) 2003-01-06 2004-07-29 Koninklijke Philips Electronics N.V. Multi-factor application selection
US7472110B2 (en) 2003-01-29 2008-12-30 Microsoft Corporation System and method for employing social networks for information discovery
US20040158630A1 (en) 2003-02-12 2004-08-12 Chang Tsung-Yen Dean Monitoring and controlling network activity in real-time
US20040162830A1 (en) * 2003-02-18 2004-08-19 Sanika Shirwadkar Method and system for searching location based information on a mobile device
FI115879B (en) 2003-03-07 2005-07-29 Nokia Corp Channel selection in a wireless communication system
US6947930B2 (en) 2003-03-21 2005-09-20 Overture Services, Inc. Systems and methods for interactive search query refinement
US20040193698A1 (en) 2003-03-24 2004-09-30 Sadasivuni Lakshminarayana Method for finding convergence of ranking of web page
US7185088B1 (en) 2003-03-31 2007-02-27 Microsoft Corporation Systems and methods for removing duplicate search engine results
US7480867B1 (en) 2003-03-31 2009-01-20 Unisys Corporation Logistic management system having user interface with customizable data fields
US7376714B1 (en) 2003-04-02 2008-05-20 Gerken David A System and method for selectively acquiring and targeting online advertising based on user IP address
US20040199422A1 (en) 2003-04-03 2004-10-07 Larry Napier Consumer transaction-based marketing of goods and services
US20040225647A1 (en) 2003-05-09 2004-11-11 John Connelly Display system and method
WO2004102855A2 (en) 2003-05-09 2004-11-25 Landmat International Inc. Content publishing over mobile networks
US7356332B2 (en) 2003-06-09 2008-04-08 Microsoft Corporation Mobile information system for presenting information to mobile devices
US7069308B2 (en) 2003-06-16 2006-06-27 Friendster, Inc. System, method and apparatus for connecting users in an online computer system based on their relationships within social networks
US20050027666A1 (en) 2003-07-15 2005-02-03 Vente, Inc Interactive online research system and method
DE10333075B4 (en) 2003-07-21 2011-06-16 Siemens Ag Method and apparatus for setting training in sport, especially in running
US20050041647A1 (en) 2003-08-05 2005-02-24 Stinnie Desmond L. Internet voice & data messaging (IVDM) portal
US20060236258A1 (en) 2003-08-11 2006-10-19 Core Mobility, Inc. Scheduling of rendering of location-based content
EP1661018A4 (en) 2003-08-15 2009-08-26 Oversee Net Internet domain keyword optimization
US20070274506A1 (en) 2003-08-20 2007-11-29 Bret Schundler Distributed call center system and method for volunteer mobilization
US20050065995A1 (en) 2003-09-23 2005-03-24 Microsoft Corporation Content and task-execution services provided through dialog-based interfaces
US7668950B2 (en) 2003-09-23 2010-02-23 Marchex, Inc. Automatically updating performance-based online advertising system and method
US7346839B2 (en) 2003-09-30 2008-03-18 Google Inc. Information retrieval based on historical data
US20050222989A1 (en) 2003-09-30 2005-10-06 Taher Haveliwala Results based personalization of advertisements in a search engine
US7647242B2 (en) 2003-09-30 2010-01-12 Google, Inc. Increasing a number of relevant advertisements using a relaxed match
US8560493B2 (en) 2003-10-01 2013-10-15 Google Inc. Determining and/or using end user local time information in an ad system
US7428497B2 (en) 2003-10-06 2008-09-23 Utbk, Inc. Methods and apparatuses for pay-per-call advertising in mobile/wireless applications
US7120235B2 (en) 2003-10-06 2006-10-10 Ingenio, Inc. Method and apparatus to provide pay-per-call performance based advertising
US8027878B2 (en) 2003-10-06 2011-09-27 Utbk, Inc. Method and apparatus to compensate demand partners in a pay-per-call performance based advertising system
WO2005043312A2 (en) 2003-10-24 2005-05-12 Caringfamily, Llc Use of a closed communication service to diagnose and treat conditions in subjects
US7797529B2 (en) * 2003-11-10 2010-09-14 Yahoo! Inc. Upload security scheme
US20050114312A1 (en) 2003-11-26 2005-05-26 Microsoft Corporation Efficient string searches using numeric keypad
US20050119936A1 (en) 2003-12-02 2005-06-02 Robert Buchanan Sponsored media content
US20050149399A1 (en) 2003-12-18 2005-07-07 Fuji Photo Film Co., Ltd. Service server and service method
US20050144065A1 (en) 2003-12-19 2005-06-30 Palo Alto Research Center Incorporated Keyword advertisement management with coordinated bidding among advertisers
US20050144297A1 (en) 2003-12-30 2005-06-30 Kidsnet, Inc. Method and apparatus for providing content access controls to access the internet
US9235849B2 (en) 2003-12-31 2016-01-12 Google Inc. Generating user information for use in targeted advertising
US7734729B2 (en) 2003-12-31 2010-06-08 Amazon Technologies, Inc. System and method for obtaining information relating to an item of commerce using a portable imaging device
US20050191936A1 (en) 2004-01-07 2005-09-01 Marine Jon C. Doll
US7444327B2 (en) 2004-01-09 2008-10-28 Microsoft Corporation System and method for automated optimization of search result relevance
US20050154717A1 (en) 2004-01-09 2005-07-14 Microsoft Corporation System and method for optimizing paid listing yield
US20050154639A1 (en) 2004-01-09 2005-07-14 Zetmeir Karl D. Business method and model for integrating social networking into electronic auctions and ecommerce venues.
US8015119B2 (en) 2004-01-21 2011-09-06 Google Inc. Methods and systems for the display and navigation of a social network
EP1577830A2 (en) 2004-01-23 2005-09-21 Neal E. Solomon Adaptive dynamic computer system
US7707122B2 (en) 2004-01-29 2010-04-27 Yahoo ! Inc. System and method of information filtering using measures of affinity of a relationship
US7269590B2 (en) 2004-01-29 2007-09-11 Yahoo! Inc. Method and system for customizing views of information associated with a social network user
US7885901B2 (en) 2004-01-29 2011-02-08 Yahoo! Inc. Method and system for seeding online social network contacts
US20050171936A1 (en) 2004-01-30 2005-08-04 Bo Zhu Wireless search engine and method thereof
EP1713189A1 (en) 2004-02-05 2006-10-18 Matsushita Electric Industrial Co., Ltd. Terminal apparatus and received data displaying method
US7310676B2 (en) * 2004-02-09 2007-12-18 Proxpro, Inc. Method and computer system for matching mobile device users for business and social networking
JP2005227894A (en) 2004-02-10 2005-08-25 Sony Corp Data recording method, data recording device, and data recording system
US7707039B2 (en) 2004-02-15 2010-04-27 Exbiblio B.V. Automatic modification of web pages
US7523112B2 (en) 2004-02-19 2009-04-21 Research In Motion Limited System and method for searching a remote database
US8421872B2 (en) 2004-02-20 2013-04-16 Google Inc. Image base inquiry system for search engines for mobile telephones with integrated camera
US7496360B2 (en) 2004-02-27 2009-02-24 Texas Instruments Incorporated Multi-function telephone
US20050197846A1 (en) 2004-03-04 2005-09-08 Peter Pezaris Method and system for generating a proximity index in a social networking environment
US20050198305A1 (en) 2004-03-04 2005-09-08 Peter Pezaris Method and system for associating a thread with content in a social networking environment
US20050198031A1 (en) 2004-03-04 2005-09-08 Peter Pezaris Method and system for controlling access to user information in a social networking environment
US6896188B1 (en) 2004-03-05 2005-05-24 Stuart Graham Method and system for providing a check premium
US8244725B2 (en) 2004-03-10 2012-08-14 Iron Mountain Incorporated Method and apparatus for improved relevance of search results
WO2005089286A2 (en) 2004-03-15 2005-09-29 America Online, Inc. Sharing social network information
US8005835B2 (en) 2004-03-15 2011-08-23 Yahoo! Inc. Search systems and methods with integration of aggregate user annotations
US20050216550A1 (en) 2004-03-26 2005-09-29 Paseman William G Communication mode and group integration for social networks
US20060161778A1 (en) 2004-03-29 2006-07-20 Nokia Corporation Distinguishing between devices of different types in a wireless local area network (WLAN)
US20050221843A1 (en) 2004-03-30 2005-10-06 Kimberley Friedman Distribution of location specific advertising information via wireless communication network
US20050234929A1 (en) 2004-03-31 2005-10-20 Ionescu Mihai F Methods and systems for interfacing applications with a search engine
US7693825B2 (en) 2004-03-31 2010-04-06 Google Inc. Systems and methods for ranking implicit search results
US20050233742A1 (en) 2004-04-16 2005-10-20 Jeyhan Karaoguz Location based directories Via a broadband access gateway
WO2005106749A2 (en) 2004-04-23 2005-11-10 Maritz Inc. Cardholder loyalty program with rebate
US7100827B2 (en) 2004-04-28 2006-09-05 Goodrich Corporation Aircraft cargo loading logistics system
US8024335B2 (en) 2004-05-03 2011-09-20 Microsoft Corporation System and method for dynamically generating a selectable search extension
US8611873B2 (en) 2004-05-12 2013-12-17 Synchronoss Technologies, Inc. Advanced contact identification system
US7689452B2 (en) 2004-05-17 2010-03-30 Lam Chuck P System and method for utilizing social networks for collaborative filtering
WO2005116979A2 (en) 2004-05-17 2005-12-08 Visible Path Corporation System and method for enforcing privacy in social networks
US20050266889A1 (en) 2004-05-28 2005-12-01 Kuhl Lawrence E User interface methods and apparatus for initiating telephone calls from a mobile station
AU2004320238B2 (en) 2004-06-04 2008-07-03 Mitsubishi Denki Kabushiki Kaisha Certificate issuance server and certification system for certifying operating environment
US8019875B1 (en) * 2004-06-04 2011-09-13 Google Inc. Systems and methods for indicating a user state in a social network
US7865511B2 (en) 2004-06-25 2011-01-04 Apple Inc. News feed browser
US7720828B2 (en) 2004-06-29 2010-05-18 Blake Bookstaff Method and system for automated intelligent electronic advertising
US8825639B2 (en) 2004-06-30 2014-09-02 Google Inc. Endorsing search results
US7437364B1 (en) 2004-06-30 2008-10-14 Google Inc. System and method of accessing a document efficiently through multi-tier web caching
US20060004627A1 (en) 2004-06-30 2006-01-05 Shumeet Baluja Advertisements for devices with call functionality, such as mobile phones
US7562069B1 (en) 2004-07-01 2009-07-14 Aol Llc Query disambiguation
EP1767900A4 (en) 2004-07-15 2010-01-20 Amosense Co Ltd Mobile terminal device
US20060184617A1 (en) 2005-02-11 2006-08-17 Nicholas Frank C Method and system for the creating, managing, and delivery of feed formatted content
US20060036565A1 (en) 2004-08-10 2006-02-16 Carl Bruecken Passive monitoring of user interaction with a browser application
US7890871B2 (en) 2004-08-26 2011-02-15 Redlands Technology, Llc System and method for dynamically generating, maintaining, and growing an online social network
US8010460B2 (en) 2004-09-02 2011-08-30 Linkedin Corporation Method and system for reputation evaluation of online users in a social networking scheme
US20060059129A1 (en) 2004-09-10 2006-03-16 Hideyuki Azuma Public relations communication methods and systems
US20060075335A1 (en) 2004-10-01 2006-04-06 Tekflo, Inc. Temporal visualization algorithm for recognizing and optimizing organizational structure
US20060074883A1 (en) 2004-10-05 2006-04-06 Microsoft Corporation Systems, methods, and interfaces for providing personalized search and information access
US20060080613A1 (en) 2004-10-12 2006-04-13 Ray Savant System and method for providing an interactive social networking and role playing game within a virtual community
US7543232B2 (en) 2004-10-19 2009-06-02 International Business Machines Corporation Intelligent web based help system
CN102982092B (en) 2004-10-19 2017-06-09 飞扬管理有限公司 System and method for location-based social network
US7668889B2 (en) 2004-10-27 2010-02-23 At&T Intellectual Property I, Lp Method and system to combine keyword and natural language search results
US8184128B2 (en) 2004-10-27 2012-05-22 Hewlett-Packard Development Company, L. P. Data distribution system and method therefor
US7689458B2 (en) 2004-10-29 2010-03-30 Microsoft Corporation Systems and methods for determining bid value for content items to be placed on a rendered page
US8171022B2 (en) 2004-11-05 2012-05-01 Johnston Jeffrey M Methods, systems, and computer program products for facilitating user interaction with customer relationship management, auction, and search engine software using conjoint analysis
US20060106674A1 (en) 2004-11-16 2006-05-18 Gpshopper, Inc. Mobile shopping method and application
US20060123053A1 (en) 2004-12-02 2006-06-08 Insignio Technologies, Inc. Personalized content processing and delivery system and media
US20060123014A1 (en) 2004-12-07 2006-06-08 David Ng Ranking Internet Search Results Based on Number of Mobile Device Visits to Physical Locations Related to the Search Results
US20060122879A1 (en) 2004-12-07 2006-06-08 O'kelley Brian Method and system for pricing electronic advertisements
US20060143183A1 (en) 2004-12-23 2006-06-29 Goldberg Adam J System and method for providing collection sub-groups
US20060155597A1 (en) 2005-01-10 2006-07-13 Gleason David M Method, system and apparatus for location based advertising
US7606799B2 (en) 2005-01-12 2009-10-20 Fmr Llc Context-adaptive content distribution to handheld devices
US20060167747A1 (en) 2005-01-25 2006-07-27 Microsoft Corporation Content-targeted advertising for interactive computer-based applications
US20080195483A1 (en) 2005-02-01 2008-08-14 Moore James F Widget management systems and advertising systems related thereto
US20060259434A1 (en) 2005-02-09 2006-11-16 Vilcauskas Andrew Jr Ringtone distribution system
US9202219B2 (en) 2005-02-16 2015-12-01 Yellowpages.Com Llc System and method to merge pay-for-performance advertising models
US20070244900A1 (en) 2005-02-22 2007-10-18 Kevin Hopkins Internet-based search system and method of use
US7716300B2 (en) 2005-02-22 2010-05-11 Microsoft Corporation Systems and methods to facilitate self regulation of social networks through trading and gift exchange
US20060194186A1 (en) 2005-02-28 2006-08-31 Amit Nanda Method and apparatus for automatically grouping within a networking database and system for parents
EP1866806A1 (en) 2005-03-09 2007-12-19 Medio Systems, Inc. Method and system for active ranking of browser search engine results
US20060242017A1 (en) 2005-03-09 2006-10-26 Medio Systems, Inc. Method and system of bidding for advertisement placement on computing devices
US8219567B2 (en) 2005-03-15 2012-07-10 Microsoft Corporation Mobile friendly internet searches
KR100690021B1 (en) 2005-03-15 2007-03-08 엔에이치엔(주) Online human network management system and method for stimulating users to build various faces of relation
US20060217110A1 (en) 2005-03-25 2006-09-28 Core Mobility, Inc. Prioritizing the display of non-intrusive content on a mobile communication device
US20060218225A1 (en) 2005-03-28 2006-09-28 Hee Voon George H Device for sharing social network information among users over a network
US20060224447A1 (en) 2005-03-31 2006-10-05 Ross Koningstein Automated offer management using audience segment information
US20060229063A1 (en) 2005-04-12 2006-10-12 Microsoft Corporation Systems and methods automatically updating contact information
US20060242007A1 (en) 2005-04-20 2006-10-26 Leong Kian F Systems and methods for advertising payments
US7308261B2 (en) 2005-04-25 2007-12-11 Yahoo! Inc. Method for quick registration from a mobile device
US7451161B2 (en) 2005-04-28 2008-11-11 Friendster, Inc. Compatibility scoring of users in a social network
US20060248573A1 (en) 2005-04-28 2006-11-02 Content Guard Holdings, Inc. System and method for developing and using trusted policy based on a social model
US8438142B2 (en) 2005-05-04 2013-05-07 Google Inc. Suggesting and refining user input based on original user input
JP2006317575A (en) 2005-05-11 2006-11-24 Matsushita Electric Ind Co Ltd Audio decoding device
US7647312B2 (en) 2005-05-12 2010-01-12 Microsoft Corporation System and method for automatic generation of suggested inline search terms
US20060256008A1 (en) 2005-05-13 2006-11-16 Outland Research, Llc Pointing interface for person-to-person information exchange
US20060271438A1 (en) 2005-05-24 2006-11-30 Andrew Shotland Advertising systems and methods
US20060271425A1 (en) 2005-05-27 2006-11-30 Microsoft Corporation Advertising in application programs
US20060287919A1 (en) 2005-06-02 2006-12-21 Blue Mustard Llc Advertising search system and method
US20060287936A1 (en) 2005-06-03 2006-12-21 Jacobson Clifford R Subodmain name marketing
US20060288015A1 (en) 2005-06-15 2006-12-21 Schirripa Steven R Electronic content classification
KR100744724B1 (en) 2005-06-24 2007-08-01 (주)뮤직소프트 System for managing online record shop and method for the same
US20060293065A1 (en) 2005-06-27 2006-12-28 Lucent Technologies Inc. Dynamic information on demand
US7831520B2 (en) 2005-06-28 2010-11-09 Ebay Inc. Mobile device communication system
US7672931B2 (en) 2005-06-30 2010-03-02 Microsoft Corporation Searching for content using voice search queries
US8090084B2 (en) 2005-06-30 2012-01-03 At&T Intellectual Property Ii, L.P. Automated call router for business directory using the world wide web
US20070005587A1 (en) 2005-06-30 2007-01-04 Microsoft Corporation Relative search results based off of user interaction
US20070011078A1 (en) 2005-07-11 2007-01-11 Microsoft Corporation Click-fraud reducing auction via dual pricing
US8706546B2 (en) 2005-07-18 2014-04-22 Google Inc. Selecting and/or scoring content-relevant advertisements
US20070112739A1 (en) 2005-07-19 2007-05-17 4Info, Inc. Intelligent mobile search client
US8166010B2 (en) 2005-07-26 2012-04-24 Taptu Limited Processing and sending search results over a wireless network to a mobile device
US20070027857A1 (en) 2005-07-28 2007-02-01 Li Deng System and method for searching multimedia and download the search result to mobile devices
US20070027751A1 (en) 2005-07-29 2007-02-01 Chad Carson Positioning advertisements on the bases of expected revenue
US20070033210A1 (en) 2005-08-02 2007-02-08 Motorola, Inc. Application data interaction method and system using an interaction manager
US8295851B2 (en) 2005-08-03 2012-10-23 Michael Edward Finnegan Realtime, interactive and geographically defined computerized personal matching systems and methods
US20070032244A1 (en) * 2005-08-08 2007-02-08 Microsoft Corporation Group-centric location tagging for mobile devices
US8073700B2 (en) 2005-09-12 2011-12-06 Nuance Communications, Inc. Retrieval and presentation of network service results for mobile device using a multimodal browser
US20070061303A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Mobile search result clustering
US20070061246A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Mobile campaign creation
US20070060173A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Managing sponsored content based on transaction history
US20070061242A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Implicit searching for mobile content
US8027879B2 (en) 2005-11-05 2011-09-27 Jumptap, Inc. Exclusivity bidding for mobile sponsored content
US20080214148A1 (en) 2005-11-05 2008-09-04 Jorey Ramer Targeting mobile sponsored content within a social network
US20090240568A1 (en) 2005-09-14 2009-09-24 Jorey Ramer Aggregation and enrichment of behavioral profile data using a monetization platform
US20080214204A1 (en) 2005-11-01 2008-09-04 Jorey Ramer Similarity based location mapping of mobile comm facility users
US20070198485A1 (en) 2005-09-14 2007-08-23 Jorey Ramer Mobile search service discovery
US7912458B2 (en) 2005-09-14 2011-03-22 Jumptap, Inc. Interaction analysis and prioritization of mobile content
US20080270220A1 (en) 2005-11-05 2008-10-30 Jorey Ramer Embedding a nonsponsored mobile content within a sponsored mobile content
US20070073717A1 (en) 2005-09-14 2007-03-29 Jorey Ramer Mobile comparison shopping
US8131271B2 (en) 2005-11-05 2012-03-06 Jumptap, Inc. Categorization of a mobile user profile based on browse behavior
US20070192318A1 (en) 2005-09-14 2007-08-16 Jorey Ramer Creation of a mobile search suggestion dictionary
US7769764B2 (en) 2005-09-14 2010-08-03 Jumptap, Inc. Mobile advertisement syndication
US20090234745A1 (en) 2005-11-05 2009-09-17 Jorey Ramer Methods and systems for mobile coupon tracking
US8666376B2 (en) 2005-09-14 2014-03-04 Millennial Media Location based mobile shopping affinity program
US8311888B2 (en) 2005-09-14 2012-11-13 Jumptap, Inc. Revenue models associated with syndication of a behavioral profile using a monetization platform
US20080242279A1 (en) 2005-09-14 2008-10-02 Jorey Ramer Behavior-based mobile content placement on a mobile communication facility
US20070239724A1 (en) 2005-09-14 2007-10-11 Jorey Ramer Mobile search services related to direct identifiers
US20080214152A1 (en) 2005-09-14 2008-09-04 Jorey Ramer Methods and systems of mobile dynamic content presentation
US8364521B2 (en) 2005-09-14 2013-01-29 Jumptap, Inc. Rendering targeted advertisement on mobile communication facilities
US20070168354A1 (en) 2005-11-01 2007-07-19 Jorey Ramer Combined algorithmic and editorial-reviewed mobile content search results
US20070100651A1 (en) 2005-11-01 2007-05-03 Jorey Ramer Mobile payment facilitation
US20080214149A1 (en) 2005-09-14 2008-09-04 Jorey Ramer Using wireless carrier data to influence mobile search results
US20070061317A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Mobile search substring query completion
US20080215623A1 (en) 2005-09-14 2008-09-04 Jorey Ramer Mobile communication facility usage and social network creation
US20080214155A1 (en) 2005-11-01 2008-09-04 Jorey Ramer Integrating subscription content into mobile search results
US7676394B2 (en) 2005-09-14 2010-03-09 Jumptap, Inc. Dynamic bidding and expected value
US7577665B2 (en) 2005-09-14 2009-08-18 Jumptap, Inc. User characteristic influenced search results
US7603360B2 (en) 2005-09-14 2009-10-13 Jumptap, Inc. Location influenced search results
US20090240569A1 (en) 2005-09-14 2009-09-24 Jorey Ramer Syndication of a behavioral profile using a monetization platform
US8103545B2 (en) 2005-09-14 2012-01-24 Jumptap, Inc. Managing payment for sponsored content presented to mobile communication facilities
US9201979B2 (en) 2005-09-14 2015-12-01 Millennial Media, Inc. Syndication of a behavioral profile associated with an availability condition using a monetization platform
US20080215429A1 (en) 2005-11-01 2008-09-04 Jorey Ramer Using a mobile communication facility for offline ad searching
US20070073722A1 (en) 2005-09-14 2007-03-29 Jorey Ramer Calculation and presentation of mobile content expected value
US20080009268A1 (en) 2005-09-14 2008-01-10 Jorey Ramer Authorized mobile content search results
US8195133B2 (en) 2005-09-14 2012-06-05 Jumptap, Inc. Mobile dynamic advertisement creation and placement
US20090029687A1 (en) 2005-09-14 2009-01-29 Jorey Ramer Combining mobile and transcoded content in a mobile search result
US9076175B2 (en) 2005-09-14 2015-07-07 Millennial Media, Inc. Mobile comparison shopping
US20070100805A1 (en) 2005-09-14 2007-05-03 Jorey Ramer Mobile content cross-inventory yield optimization
US8832100B2 (en) 2005-09-14 2014-09-09 Millennial Media, Inc. User transaction history influenced search results
US20070061245A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Location based presentation of mobile content
US7860871B2 (en) 2005-09-14 2010-12-28 Jumptap, Inc. User history influenced search results
US20070073719A1 (en) 2005-09-14 2007-03-29 Jorey Ramer Physical navigation of a mobile search application
US20090234861A1 (en) 2005-09-14 2009-09-17 Jorey Ramer Using mobile application data within a monetization platform
US20070100652A1 (en) 2005-11-01 2007-05-03 Jorey Ramer Mobile pay per call
US20070100653A1 (en) 2005-11-01 2007-05-03 Jorey Ramer Mobile website analyzer
US8688671B2 (en) 2005-09-14 2014-04-01 Millennial Media Managing sponsored content based on geographic region
US20070061335A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Multimodal search query processing
US20080214153A1 (en) 2005-09-14 2008-09-04 Jorey Ramer Mobile User Profile Creation based on User Browse Behaviors
US20070061211A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Preventing mobile communication facility click fraud
US9471925B2 (en) 2005-09-14 2016-10-18 Millennial Media Llc Increasing mobile interactivity
US20080214154A1 (en) 2005-11-01 2008-09-04 Jorey Ramer Associating mobile and non mobile web content
US20070100806A1 (en) 2005-11-01 2007-05-03 Jorey Ramer Client libraries for mobile content
US7702318B2 (en) 2005-09-14 2010-04-20 Jumptap, Inc. Presentation of sponsored content based on mobile transaction event
US20070061198A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Mobile pay-per-call campaign creation
US20070288427A1 (en) 2005-09-14 2007-12-13 Jorey Ramer Mobile pay-per-call campaign creation
US20070073718A1 (en) 2005-09-14 2007-03-29 Jorey Ramer Mobile search service instant activation
US20070118533A1 (en) 2005-09-14 2007-05-24 Jorey Ramer On-off handset search box
US7752209B2 (en) 2005-09-14 2010-07-06 Jumptap, Inc. Presenting sponsored content on a mobile communication facility
US20080214151A1 (en) 2005-09-14 2008-09-04 Jorey Ramer Methods and systems for mobile coupon placement
US20070061247A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Expected value and prioritization of mobile content
US7548915B2 (en) 2005-09-14 2009-06-16 Jorey Ramer Contextual mobile content placement on a mobile communication facility
US8290810B2 (en) 2005-09-14 2012-10-16 Jumptap, Inc. Realtime surveying within mobile sponsored content
US8615719B2 (en) 2005-09-14 2013-12-24 Jumptap, Inc. Managing sponsored content for delivery to mobile communication facilities
US20090234711A1 (en) 2005-09-14 2009-09-17 Jorey Ramer Aggregation of behavioral profile data using a monetization platform
US8229914B2 (en) 2005-09-14 2012-07-24 Jumptap, Inc. Mobile content spidering and compatibility determination
US20070061334A1 (en) 2005-09-14 2007-03-15 Jorey Ramer Search query address redirection on a mobile communication facility
US20070100650A1 (en) 2005-09-14 2007-05-03 Jorey Ramer Action functionality for mobile content search results
US8660891B2 (en) 2005-11-01 2014-02-25 Millennial Media Interactive mobile advertisement banners
US8989718B2 (en) 2005-09-14 2015-03-24 Millennial Media, Inc. Idle screen advertising
US7945943B2 (en) 2005-09-19 2011-05-17 Silverbrook Research Pty Ltd Retrieving an access token via a coded surface
GB2430507A (en) 2005-09-21 2007-03-28 Stephen Robert Ives System for managing the display of sponsored links together with search results on a mobile/wireless device
US20070073656A1 (en) 2005-09-29 2007-03-29 Bandi Krishna M Wireless device with application search function
US20070078832A1 (en) 2005-09-30 2007-04-05 Yahoo! Inc. Method and system for using smart tags and a recommendation engine using smart tags
US20070078851A1 (en) 2005-10-05 2007-04-05 Grell Mathew L System and method for filtering search query results
US20070083611A1 (en) 2005-10-07 2007-04-12 Microsoft Corporation Contextual multimedia advertisement presentation
US20070106564A1 (en) 2005-11-04 2007-05-10 Utiba Pte Ltd. Mobile phone as a point of sale (POS) device
US8166061B2 (en) 2006-01-10 2012-04-24 Aol Inc. Searching recent content publication activity
US7788188B2 (en) 2006-01-30 2010-08-31 Hoozware, Inc. System for providing a service to venues where people aggregate
US8311845B2 (en) 2006-02-07 2012-11-13 Groupon, Inc. Pay-for-visit advertising based on visits to physical locations
US20080040428A1 (en) 2006-04-26 2008-02-14 Xu Wei Method for establishing a social network system based on motif, social status and social attitude
WO2007139857A2 (en) 2006-05-24 2007-12-06 Archetype Media, Inc. Storing data related to social publishers and associating the data with electronic brand data
US20080010343A1 (en) 2006-05-24 2008-01-10 Digital Sports, Inc. Method of providing a digital athlete profile
US7792903B2 (en) 2006-05-31 2010-09-07 Red Hat, Inc. Identity management for open overlay for social networks and online services
US7822762B2 (en) 2006-06-28 2010-10-26 Microsoft Corporation Entity-specific search model
US20090030952A1 (en) 2006-07-12 2009-01-29 Donahue Michael J Global asset management
US7669123B2 (en) 2006-08-11 2010-02-23 Facebook, Inc. Dynamically providing a news feed about a user of a social network
US8402094B2 (en) 2006-08-11 2013-03-19 Facebook, Inc. Providing a newsfeed based on user affinity for entities and monitored actions in a social network environment
US20080120390A1 (en) 2006-09-15 2008-05-22 Icebreaker, Inc. Date management within a social interaction network
US20080126411A1 (en) 2006-09-26 2008-05-29 Microsoft Corporation Demographic prediction using a social link network
US8812582B2 (en) 2006-11-30 2014-08-19 Red Hat, Inc. Automated screen saver with shared media
US8671114B2 (en) 2006-11-30 2014-03-11 Red Hat, Inc. Search results weighted by real-time sharing activity
US7752553B2 (en) 2006-12-01 2010-07-06 Red Hat, Inc. Method and system for aggregating and displaying an event stream
BRPI0815640A2 (en) 2007-08-20 2016-05-10 Facebook Inc advertising methods for social network members and ad selection to be submitted by social networking site and advertising system for social network members
US20100257023A1 (en) 2009-04-07 2010-10-07 Facebook, Inc. Leveraging Information in a Social Network for Inferential Targeting of Advertisements
US9026131B2 (en) * 2009-07-21 2015-05-05 Modena Enterprises, Llc Systems and methods for associating contextual information and a contact entry with a communication originating from a geographic location
US10217117B2 (en) * 2011-09-15 2019-02-26 Stephan HEATH System and method for social networking interactions using online consumer browsing behavior, buying patterns, advertisements and affiliate advertising, for promotions, online coupons, mobile services, products, goods and services, entertainment and auctions, with geospatial mapping technology
US9510141B2 (en) * 2012-06-04 2016-11-29 Apple Inc. App recommendation using crowd-sourced localized app usage data

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070174117A1 (en) * 2006-01-23 2007-07-26 Microsoft Corporation Advertising that is relevant to a person
US20080104227A1 (en) * 2006-11-01 2008-05-01 Yahoo! Inc. Searching and route mapping based on a social network, location, and time

Cited By (23)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9071367B2 (en) 2006-03-17 2015-06-30 Fatdoor, Inc. Emergency including crime broadcast in a neighborhood social network
US9037516B2 (en) 2006-03-17 2015-05-19 Fatdoor, Inc. Direct mailing in a geo-spatial environment
US20140222577A1 (en) * 2006-03-17 2014-08-07 Raj Abhyanker Campaign in a geo-spatial environment
US8965409B2 (en) 2006-03-17 2015-02-24 Fatdoor, Inc. User-generated community publication in an online neighborhood social network
US9002754B2 (en) * 2006-03-17 2015-04-07 Fatdoor, Inc. Campaign in a geo-spatial environment
US9373149B2 (en) 2006-03-17 2016-06-21 Fatdoor, Inc. Autonomous neighborhood vehicle commerce network and community
US9064288B2 (en) 2006-03-17 2015-06-23 Fatdoor, Inc. Government structures and neighborhood leads in a geo-spatial environment
US9459622B2 (en) 2007-01-12 2016-10-04 Legalforce, Inc. Driverless vehicle commerce network and community
US9070101B2 (en) 2007-01-12 2015-06-30 Fatdoor, Inc. Peer-to-peer neighborhood delivery multi-copter and method
US9098545B2 (en) 2007-07-10 2015-08-04 Raj Abhyanker Hot news neighborhood banter in a geo-spatial social network
US9144052B2 (en) * 2010-09-29 2015-09-22 British Telecommunications Public Limited Company Method of determining location
US20130182603A1 (en) * 2010-09-29 2013-07-18 British Telecommunications Public Limited Company Method of determining location
US20120102165A1 (en) * 2010-10-21 2012-04-26 International Business Machines Corporation Crowdsourcing location based applications and structured data for location based applications
US10169017B2 (en) * 2010-10-21 2019-01-01 International Business Machines Corporation Crowdsourcing location based applications and structured data for location based applications
US9047606B2 (en) * 2011-09-29 2015-06-02 Hewlett-Packard Development Company, L.P. Social and contextual recommendations
US20130086160A1 (en) * 2011-09-29 2013-04-04 Shyam Sundar RAJARAM Social and contextual recommendations
US9439367B2 (en) 2014-02-07 2016-09-13 Arthi Abhyanker Network enabled gardening with a remotely controllable positioning extension
US9457901B2 (en) 2014-04-22 2016-10-04 Fatdoor, Inc. Quadcopter with a printable payload extension system and method
US9004396B1 (en) 2014-04-24 2015-04-14 Fatdoor, Inc. Skyteboard quadcopter and method
US9022324B1 (en) 2014-05-05 2015-05-05 Fatdoor, Inc. Coordination of aerial vehicles through a central server
US9441981B2 (en) 2014-06-20 2016-09-13 Fatdoor, Inc. Variable bus stops across a bus route in a regional transportation network
US9971985B2 (en) 2014-06-20 2018-05-15 Raj Abhyanker Train based community
US9451020B2 (en) 2014-07-18 2016-09-20 Legalforce, Inc. Distributed communication of independent autonomous vehicles to provide redundancy and performance

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US8571999B2 (en) 2013-10-29
US10064004B2 (en) 2018-08-28
US20140108539A1 (en) 2014-04-17
US9147201B2 (en) 2015-09-29
US20140108140A1 (en) 2014-04-17
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US20140108537A1 (en) 2014-04-17
US9129304B2 (en) 2015-09-08

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