WO2013029234A1

WO2013029234A1 - Method and apparatus for providing deal combinations

Info

Publication number: WO2013029234A1
Application number: PCT/CN2011/079100
Authority: WO
Inventors: Wei Wang; Hao Wang
Original assignee: Nokia Corporation
Priority date: 2011-08-30
Filing date: 2011-08-30
Publication date: 2013-03-07
Also published as: CN103917995A

Abstract

An approach is provided for providing deal combinations. A deal combination platform receives a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof. The platform further processes and/or facilitates a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations. The platform also causes, at least in part, a presentation of the one or more deal combinations in response to the request.

Description

METHOD AND APPARATUS FOR

PROVIDING DEAL COMBINATIONS

BACKGROUND

[0001] Service providers and device manufacturers (e.g., wireless, cellular, etc.) are continually challenged to deliver value and convenience to consumers by, for example, providing compelling network services. Historically, consumers have been offered discounts on consumer goods and/or services in the form of, for example, coupons. Such coupons could be obtained in newspapers and/or restaurant or retail store fliers, to name a few. Recently, consumers have been able to receive discounts on consumer goods and/or services in the form of deals through their devices provided by service providers. As the popularity of delivering deals over networks to consumers grows, consumers have become overwhelmed by the number of deals to choose from. Consumers are left with the problem of searching through a vast quantity of deals to find deals that relate to one of their particular interests. This problem is exacerbated when consumers want to find multiple deals that can be used together in anticipation of planning an activity. As such, service providers and device manufacturers face considerable challenges in providing mechanisms and services that allow consumers to receive combinations of deals, particularly combinations of deals related to an activity.

SOME EXAMPLE EMBODIMENTS

[0002] Therefore, there is a need for an approach for providing deal combinations.

[0003] According to one embodiment, a method comprises receiving a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof. The method also comprises processing and/or facilitating a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations. The method further comprises causing, at least in part, a presentation of the one or more deal combinations in response to the request. [0004] According to another embodiment, an apparatus comprises at least one processor, and at least one memory including computer program code for one or more computer programs, the at least one memory and the computer program code configured to, with the at least one processor, cause, at least in part, the apparatus to receive a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof. The apparatus is also caused to process and/or facilitate a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations. The apparatus is further caused to present the one or more deal combinations in response to the request.

[0005] According to another embodiment, a computer-readable storage medium carries one or more sequences of one or more instructions which, when executed by one or more processors, cause, at least in part, an apparatus to receive a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof. The apparatus is also caused to process and/or facilitate a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations. The apparatus is further caused to present the one or more deal combinations in response to the request.

[0006] According to another embodiment, an apparatus comprises means for receiving a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof. The apparatus also comprises means for processing and/or facilitating a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations. The apparatus further comprises means for causing, at least in part, a presentation of the one or more deal combinations in response to the request.

[0007] In addition, for various example embodiments of the invention, the following is applicable: a method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on (or derived at least in part from) any one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

[0008] For various example embodiments of the invention, the following is also applicable: a method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform any one or any combination of network or service provider methods (or processes) disclosed in this application.

[0009] For various example embodiments of the invention, the following is also applicable: a method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on data and/or information resulting from one or any combination of methods or processes disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

[0010] For various example embodiments of the invention, the following is also applicable: a method comprising creating and/or modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based at least in part on data and/or information resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention, and/or at least one signal resulting from one or any combination of methods (or processes) disclosed in this application as relevant to any embodiment of the invention.

[0011] In various example embodiments, the methods (or processes) can be accomplished on the service provider side or on the mobile device side or in any shared way between service provider and mobile device with actions being performed on both sides.

[0012] For various example embodiments, the following is applicable: An apparatus comprising means for performing the method of any of originally filed claims 1-12, 25-36 and 42-45.

[0013] Still other aspects, features, and advantages of the invention are readily apparent from the following detailed description, simply by illustrating a number of particular embodiments and implementations, including the best mode contemplated for carrying out the invention. The invention is also capable of other and different embodiments, and its several details can be modified in various obvious respects, all without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature, and not as restrictive.

BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The embodiments of the invention are illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings:

[0015] FIG. 1 is a diagram of a system capable of providing deal combinations, according to one embodiment;

[0016] FIG. 2 is a diagram of the components of deal combination platform, according to one embodiment;

[0017] FIG. 3 is a flowchart of a process for providing deal combinations, according to one embodiment;

[0018] FIG. 4 is a flowchart of a process for determining likelihood scores of one or more deal category groupings, according to one embodiment;

[0019] FIG. 5 is a flowchart of a process for combining deals into one or more deal combinations, according to one embodiment;

[0020] FIG. 6 is a diagram of a user interface utilized in the processes of FIGs. 3-5, according to one embodiment;

[0021] FIG. 7 is a diagram of a user interface utilized in the processes of FIGs. 3-5, according to one embodiment;

[0022] FIG. 8 is a diagram of hardware that can be used to implement an embodiment of the invention;

[0023] FIG. 9 is a diagram of a chip set that can be used to implement an embodiment of the invention; and [0024] FIG. 10 is a diagram of a mobile terminal (e.g., handset) that can be used to implement an embodiment of the invention.

DESCRIPTION OF SOME EMB ODF ENT S

[0025] Examples of a method, apparatus, and computer program for providing deal combinations are disclosed. In the following description, for the purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.

[0026] FIG. 1 is a diagram of a system capable of providing deal combinations, according to one embodiment. As discussed above, consumers are now offered many deals from various service providers (e.g., deal providers) via various devices, such as, for example, mobile devices. As the trend continues to offer deals to consumers over their devices, consumers are becoming overwhelmed from the type and quantity of deals that are offered. To help alleviate overwhelmed consumers, deal providers have begun to recommend deals based on consumers' profiles. The profiles are often based on the consumers' shopping interests. However, the recommended deals often belong to only category because the category matches a consumer's profile. This, in essence, provides consumers only the ability to choose recommended deals from a specific category, thus limiting the number of deals the consumers have to browse through. However, outside of the category of recommended deals, consumers are left with the burden of searching through a tremendous amount of deals to find a deal that the consumers want to use. Thus, despite these advancements, certain problems still remain in providing deals to consumers.

[0027] By way of example, one problem that still remains is that consumers often may have an activity in mind for which they would like to find deals. Often, the activities are dynamic and require more than one type of deal to accomplish. Further, another problem that still exists is the types of deals required to accomplish the activity may be unrelated to the information used to recommend deals within certain categories. For example, a consumer may wish to find deals related to local bars for getting drinks during a date. However, the consumer may not have profile information derived from, for example, shopping interests that can be used to recommend deals for getting drinks at a local bar. Additionally, even if a consumer may be able to browse multiple categories for each deal that the consumer needs to accomplish an activity based on recommendation, browsing more than one category for multiple deals can still be burdensome. For example, the consumer may have certain criteria associated with the activity that require the consumer to check the deals to ensure that each deal satisfies the criteria. Even with narrowing down the number of deals to only recommended deals, finding deals in multiple categories may still require browsing a prohibitively large number of deals and checking a prohibitively large number of deal criteria. Also, even when the consumer finds deals in each category that are related to the desired activity, the user has to validate the combination of deals to ensure that, for example, the deals can be used together or otherwise do not conflict. For example, deals often have limitations that they cannot be used with other deals, particularly if the deals are associated with a single consumer based service or goods retailer.

[0028] To address these problems, a system 100 of FIG. 1 introduces the capability to determine deals to recommend to a user based on a defined activity and combine the deals into one or more validated deal combinations that allow the user to accomplish the defined activity. By way of example, the system 100 allows a user to request deal information, the request including at least one activity and one or more criteria associated with performing the activity. The system 100 then processes the request to determine a grouping of one or more deals into one or more deal combinations. The system 100 then presents the one or more deal combinations to the user in response to the request. By way of example, the user specifies an activity and criteria for the activity, such as, for example, the planned date for the activity and the budget for the activity. The system 100 then finds one or more combinations of deals valid for the specified date and budget that complement each other to help the user accomplish the activity. Exemplary activities may include dating, grocery shopping, or soccer practice. Exemplary deals associated with the activity of dating may include, deals on flowers, deals on a restaurant and deals for watching a movie. Exemplary deals associated with grocery shopping include, deals on buying gasoline for driving a car to the grocery store, deals on food at the grocery store and deals for parking near the grocery store. [0029] In one embodiment, the user can specify an activity and can further qualify the activity according to, for example, a style or subtype of the activity. For example, if the user specifies dating as the activity, the user can further specify whether the user wants a romantic style date to accomplish the activity or an adventurous style date to accomplish the activity. Thus, the user is allowed to further define the activity to further narrow down the deals recommended and combined to accomplish the activity. In one embodiment, the user can specify various criteria associated with the deals in addition to the date and location, such as a time and/or a time span, a number of deals and/or an amount of savings, a set distance to travel to accomplish the activity, or the like.

[0030] In one embodiment, the system 100 determines one or more deal categories that are associated with the activity. The system 100 analyzes deal category groupings with the activity to determine the deal categories that are associated with the activity. The system 100 determines likelihood scores for the deal category groupings to determine whether the deal categories are associated with the activity. In one embodiment, the likelihood scores are determined by performing key word searches describing the deal categories for each deal category grouping in addition to the activity. The keyword searches may be performed using one or more external source, such as search engines on the Internet. The likelihood scores associated with the respective deal category groupings are used to select from among the total number of deal category groupings the deal category groupings that are associated with the activity and from which the deals are selected to form the deal combinations.

[0031] In one embodiment, the system 100 can adjust the likelihood scores associated with the deal category groupings based on information associated with the user that is requesting deal information associated with the activity. By way of example, the system 100 can consider prior rankings by the user of historical suggestions of deals and/or locations associated with the deals or recommendations (e.g., restaurants, cities, parks, playgrounds, bars, clubs, sports venues, music venues, etc.), prior activity of the user regarding suggestions of deals and/or deal locations, and other usage data, such as browser history. Thus, the system 100 can personalize the likelihood scores of the various deal category groupings to provide a user with more personalized deal combination recommendations. [0032] In one embodiment, the system 100 associates deals with respective deal categories of the selected one or more deal category groupings to thereby form deal groupings. The system 100 may also associate the likelihood scores associated with the deal category groupings with the respective deal groupings. Based on one or more shared deals among two or more deal groupings, the system 100 may combine the two or more deal groupings into additional deal groupings that combine their respect deals (e.g., a deal grouping of two deals is combine with a deal grouping of two deals, each sharing the same deal, to form a deal grouping of three deals). The resulting one or more deal groupings can constitute one or more deal combinations depending on the number of shared deals between deal groupings. In other words, for example, once deal groupings no longer have shared deals, combining deals is complete and the remaining deal groupings are treated as deal combinations.

[0033] In one embodiment, deal groupings are associated with the likelihood scores of the respective deal category groupings. Further, the deal groupings are ranked according to the likelihood score such that deal groupings with higher likelihood scores are ranked higher. The deal groupings can be combined into additional deal groupings until forming the deal combinations according to the likelihood scores such that deal groupings with the highest likelihood scores, and which share at least one deal, are grouped together.

[0034] In one embodiment, the system 100 validates the deal combinations to ensure that the deals within the deal combinations satisfy the criteria defined the by the user associated with the request. The system 100 also validates the deal combinations to ensure that the deals within the deal combinations complement each other and otherwise do not conflict with each other based on deal characteristics. By way of example, certain deals have characteristics or restrictions regarding the quantity and type of other deals that the deals can be combined with. The system 100 validates the deal combinations prior to presenting the deal combinations to the user to ensure that the deals within the deal combinations are valid. The deal characteristics may include, for example, temporal characteristics, location characteristics, budget characteristics, deal grouping characteristics, or a combination thereof.

[0035] As shown in FIG. 1, the system 100 comprises a user equipment (UE) 101 having connectivity to a deal combination platform 103 via a communication network 105. The UE 101 also has connectivity to a services platform 107 and content providers 113a-113n (collectively referred to as content providers 113) via the communication network. The UE 101 may include one or more applications l l la-l l ln (collectively referred to as applications 111). The applications 111 may include, for example, one or more mapping applications, messaging applications, calendar applications, context applications, sensor applications, etc. One of the applications 111a may communicate with the deal combination platform 103 to request deal information and to receive information regarding deal combinations associated with an activity. One or more of the applications 111 can also determine context information of the UE 101, the user of the UE 101 or a combination thereof. The UE 101 may also communicate with one or more sensors 117a-117n (collectively referred to as sensors 117). The sensors 117 may collect context information associated with the UE 101 , the user of the UE 101, or a combination thereof. The sensors 117 may include image sensors, audio sensors, location sensors (e.g., GPS), accelerometers, gyroscopes, brightness sensors, moisture sensors, load sensors, slope sensors, visibility sensors, etc. The sensors 117 can interface with the UE 101, the applications 111 , and the deal combination platform 103 for receiving and transmitting context information regarding the UE 101 and/or the user of the UE 101.

[0036] The deal combination platform 103 of the system 100 provides one or more deal combinations upon a request from a user and/or a UE 101 based on an activity and one or more criteria, as discussed in detail below. Connected to the deal combination platform 103 may include a deal database 115. The deal database 115 may store the one or more deals that are used by the deal combination platform 103 to generate the one or more deal combinations. The deal database 115 also may store the one or more deal categories and/or deal category groupings that are used in determining the one or more deal combinations. In one embodiment, the deal database 115 may store pre-determined relationships between a set number of activities and the deal categories such that the deal database 115 already stores information regarding the deal categories that are associated with certain activities. Thus, the deal combination platform 103 can function in an offline mode without having to determine information regarding likelihood scores of deal category groupings associated with an activity based on external keyword searches.

[0037] The system 100 also includes the services platform 107 that includes one or more services 109a-109n (collectively referred to as services 109). The services platform 107 provides one or more of the services 109 to the UE 101 and the deal combination platform 103. The services 109 can include messaging services, calendar services, context information services, sensor services, mapping/navigation services, social networking services, organizational services, audio/visual services, or the like. In one embodiment, one or more services 109 of the services platform 107 can provide one or more deals, one or more deal categories, or a combination thereof to the deal combination platform 103.

[0038] The system 100 also includes the content providers 113, which provide content to the UE 101 , the deal combination platform 103 and the services platform 107. The content providers 113 can provide messaging content, calendar content, context information content, sensor content, mapping/navigation content, social networking content, organizational content, audio/visual content, etc. In one embodiment, the content providers 113 can provide one or more deals, one or more deal categories, or a combination thereof to the deal combination platform 103.

[0039] By way of example, the communication network 105 of system 100 includes one or more networks such as a data network, a wireless network, a telephony network, or any combination thereof. It is contemplated that the data network may be any local area network (LAN), metropolitan area network (MAN), wide area network (WAN), a public data network (e.g., the Internet), short range wireless network, or any other suitable packet-switched network, such as a commercially owned, proprietary packet-switched network, e.g., a proprietary cable or fiber-optic network, and the like, or any combination thereof. In addition, the wireless network may be, for example, a cellular network and may employ various technologies including enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., worldwide interoperability for microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), wireless LAN (WLAN), Bluetooth®, Internet Protocol (IP) data casting, satellite, mobile ad-hoc network (MANET), and the like, or any combination thereof. [0040] The UE 101 is any type of mobile terminal, fixed terminal, or portable terminal including a mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal navigation device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the UE 101 can support any type of interface to the user (such as "wearable" circuitry, etc.).

[0041] By way of example, the UE 101 , the deal combination platform 103, the services platform 107 and the content providers 113 communicate with each other and other components of the communication network 105 using well known, new or still developing protocols. In this context, a protocol includes a set of rules defining how the network nodes within the communication network 105 interact with each other based on information sent over the communication links. The protocols are effective at different layers of operation within each node, from generating and receiving physical signals of various types, to selecting a link for transferring those signals, to the format of information indicated by those signals, to identifying which software application executing on a computer system sends or receives the information. The conceptually different layers of protocols for exchanging information over a network are described in the Open Systems Interconnection (OSI) Reference Model.

[0042] Communications between the network nodes are typically effected by exchanging discrete packets of data. Each packet typically comprises (1) header information associated with a particular protocol, and (2) payload information that follows the header information and contains information that may be processed independently of that particular protocol. In some protocols, the packet includes (3) trailer information following the payload and indicating the end of the payload information. The header includes information such as the source of the packet, its destination, the length of the payload, and other properties used by the protocol. Often, the data in the payload for the particular protocol includes a header and payload for a different protocol associated with a different, higher layer of the OSI Reference Model. The header for a particular protocol typically indicates a type for the next protocol contained in its payload. The higher layer protocol is said to be encapsulated in the lower layer protocol. The headers included in a packet traversing multiple heterogeneous networks, such as the Internet, typically include a physical (layer 1 ) header, a data-link (layer 2) header, an internetwork (layer 3) header and a transport (layer 4) header, and various application (layer 5, layer 6 and layer 7) headers as defined by the OSI Reference Model.

[0043] FIG. 2 is a diagram of the components of the deal combination platform 103, according to one embodiment. By way of example, the deal combination platform 103 includes one or more components for providing deal combinations. It is contemplated that the functions of these components may be combined in one or more components or performed by other components of equivalent functionality. By way of example, the deal combination platform 103 may be included in the UE 101 as one of the applications 111 or as a hardware module. In one embodiment, the UE 101 may be a service 109 running on the services platform 107. In this embodiment, the deal combination platform 103 includes an activity module 201, a deal category module 203, a deal module 205, a combination module 207, a user profile module 209 and a user interface (UI) module 211.

[0044] In one embodiment, the activity module 201 is responsible for determining the activity associated with a user's request for deal combination information. In one embodiment, by way of example, the deal combination platform 103 may be pre-configured to accept a set number and type of activities. For example, a user that requests deal information selects an activity from a dropdown list of activities. The activity module 201 includes the information associated with the list of activities that the deal combination platform 103 recognizes. In such an example, the deal combination platform 103 includes pre-determined associations between the activities in the activity list and the deal categories. In one embodiment, by way of example, the deal combination platform 103 use one or more text recognition algorithms to determine an activity from the user typing in an activity in an activity entry box. Thus, the user does not select an activity from a list of activities but rather is given the freedom to enter any activity. In such an example, the deal combination platform 103 determines the activity from the user's request and proceeds to determine categories that are associated with the activity. [0045] In one embodiment, the activity module 201 also determines a style or subtype of the activity. By way of example, if the activity is attending a sporting event, the style or subtype of the sporting event may be football, baseball, basketball, soccer, or the like. By way of a further example, if the activity is dating, the style or subtype of the date may be romantic, funny, adventurous, or the like. In one embodiment, the activity module 201 may include a list of style or subtypes of the activity for each activity. In one embodiment, the activity module 201 may determine the style or subtype of the activity based on the request, such as performing character and/or word recognition on the request.

[0046] In one embodiment, the activity module 201 also determines the criteria associated with the activity. The activity module 201 can include a list of criteria for which the user can select from to further define the requested deal combinations. The activity module 201 may also allow a user to enter any type of criteria to further define the requested deal combinations. Under either approach, the activity module 201 may then determine the criteria within the request to narrow down the deals used to generate deal combinations. The criteria may include, for example, time and/or time span criteria, date criteria, location criteria, distance traveled criteria, budget criteria, a number of deals in the combination, or the like.

[0047] In one embodiment, the deal category module 203 includes information associated with the one or more deal categories that the deal combination platform 103 recognizes. By way of example, deal categories may include restaurants, bars, cars, sporting events, nightlife, plumbing. The deal category module 203 also determines the deal categories that are associated with respective activities. In one embodiment, the deal category module 203 groups two or more deal categories into deal category groupings. By way of example, a deal category grouping may include two deal categories. The deal category module 203 then performs keyword searches associated with each deal category grouping and the activity to determine likelihood scores that the deal category groupings are associated with the activity. In one embodiment, the deal category module 203 associates each one of the deal categories with all other deal categories to generate deal category groupings. Using the above exemplary deal categories, the deals category groupings may include {restaurants, bars}, {bars, cars} {restaurants, cars}, {cars, plumbing} , etc. The deal category module 203 then performs the keyword search for all of the generated deal category groupings relative to a specific activity, such as dating. The number of results that are returned for each deal category grouping with respect to the activity provides an objective analysis of whether the deal categories of each deal category grouping are both related to each other and related to the specific topic.

[0048] In one embodiment, the number of returned results for each deal category grouping can be normalized to provide a likelihood score of between, for example, 0 and 1 , with a likelihood score of 1 indicating that the deal category grouping is associated with the activity and a likelihood score of 0 indicating that the deal category grouping is not associated with the activity. Upon determining the likelihood scores for the deal category groupings, a threshold likelihood score is used to determine whether the deal category groupings are sufficiently associated with the activity to be used to generate deal combinations for the activity. By way of example, for normalized likelihood scores of the deal category groupings between 0 to 1, the threshold likelihood score may be 0.5. Thus, all deal category groupings below the threshold are excluded with respect to an activity and all deal category groupings above the threshold are included with respect to the activity. The threshold likelihood score may be varied depending on the number of deal categories and/or the number of deals associated with each deal category.

[0049] In one embodiment, the association of deal categories with activities is performed prior to the deal combination platform 103 receiving a request for deal information. Thus, the deal combination platform 103 includes pre-defined activities and pre-defined deal categories that are grouped into pre-defined deal category groupings. Under this approach, the deal combination platform 103 may work offline when determining the deal categories that are related to a specified activity because it is not necessary to perform external keyword searches to determine the likelihood scores.

[0050] In one embodiment, the deal category module 203 further modifies the likelihood scores of the deal category groupings based on user information associated with the user that requested the deal information. The deal category module 203 can acquire the user information to personalize the likelihood scores from the user profile module 209, discussed below.

[0051] In one embodiment, the deal module 205 accounts for the deals recognized by the deal combination platform 103. The deal module 205 may receive one or more deals that are used to generate the one or more deal combinations from the services platform 107 and/or the content providers 113. The deal module 205 stores the received deals in the deal database 115. The deal module 205 also determines one or more deal characteristics of the one or more deals recognized by the deal combination platform 103. The deal module 205 compares the criteria of the request determined by the activity module 201 with the deal characteristics to determine the deals that satisfy the criteria. The deals that satisfy the criteria are the deals that are used to generate the one or more deal combinations. The deal module 205 also communicates the deal characteristics with the combination module 207 for the deal combination platform 103 to validate the deals within each combination of deals.

[0052] The combination module 207 determines the one or more deal combinations. The combination module 207 associates deals with respective deal categories that are grouped together in the deal category groupings to form deal groupings. Using the deal groupings, the combination module 207 associates deal groupings together that share one or more deals to form deal groupings of larger and larger number of deals. When the deal groupings no longer share deals in common, or when the deal groupings have a requested number of deals per deal grouping, combining the deal groupings is complete and the remaining deal groupings are treated as deal combinations.

[0053] The combination module 207 also determines the likelihood scores of the deal groupings and deal combinations. Initially, the deal groupings generated based on the deal category groupings have the same likelihood scores as the respective deal category groupings. Upon combining two or more deal groupings based on a shared deal, the combined deal grouping obtain a new likelihood score based on the likelihood scores of the original deal groupings. The new likelihood score can be based on an average of the original deal grouping likelihood scores or can be based on a product of the original deal grouping likelihood scores.

[0054] The combination module 207 also validates the generated deal groupings based on the deal characteristics associated with the respective deal groupings. The combination module 207 validates the generated deal groupings to ensure that the deals within the grouping complement each other and otherwise do not conflict, and satisfy the criteria within the user's request for deal information. Additionally, the combination module 207 validates the deal combinations based on another threshold likelihood score to remove any deal combination that, because of the likelihood scores of the deal groupings that combined to make the deal combination, do not have a high enough likelihood score. By way of example, if three deal groupings were combined to form the deal combination, and the three deal groupings had likelihood scores of 0.8, 0.8 and 0.9, the product of their likelihood scores would be 0.576 and would associated with the deal combination. The likelihood scores of the deal combination is then compared to the threshold likelihood score to determine whether or not to exclude the deal combination based on a probability that the deal combination is not associated closely enough with the activity requested by the user. Any deal combinations that are not validated, based on the criteria associated with the request, the deal characteristics not complementing each other or otherwise conflicting, and/r the combined likelihood score not meeting the threshold likelihood score of the deal combination, are excluded and not presented to the user in response to the request for deal information.

[0055] The user profile module 209 determines the user information that is used to adjust the likelihood scores associated with the one or more deal category groupings and/or deal groupings for generating the one or more deal combinations. The user information can include, prior rankings by the user of historical suggestions of deals, recommendations, and locations associated with the deals or recommendations (e.g., restaurants, cities, parks, playgrounds, bars, clubs, sports venues, music venues, etc.); prior activity of the user regarding suggestions of deals and/or deal locations; and other usage data, such as browser history. The user information also can include any type of context information gathered by the deal combination platform 103 from the UE 101, the sensors 117, the services platform 107, the content providers 113, or a combination thereof. Thus, the deal combination platform 103 can provide more personalized deal recommendations based on likelihood scores of deal category groupings that consider personalized user information.

[0056] The user interface (UI) module 211 interfaces with the UE 101 to provide the user interface used to request deal information and provide the one or more deal combinations to the user. In one embodiment, the UI module 211 generates a user interface on the UE 101 of several boxes that accept text input for the user to type in activity information and criteria information for requesting deal information. In one embodiment, the UI module 211 generates drop down lists for the user to select the activity and one or more criteria. [0057] After the deal combination platform 103 determines the one or more deal combinations, the UI module 211 presents the deal combinations to the UE 101. In one embodiment, by way of example, the UI module 21 1 presents the deal combinations to the UE 101 in the form of a list that includes the various deals, with each deal including the subject of the deal (e.g., category of the deal and/or a location associated with the deal) and the specific deal information (e.g., 50% Off, Save $20, etc.). In one embodiment, the UI module 211 also presents information regarding the total budget associated with the deal combination (e.g., either before, after, or before and after the deals are applied) and the amount of money that is saved using each deal, the entire combination of deals, or a combination thereof. In one embodiment, the UI module 211 presents the locations associated with each deal of a deal combination on a map. The distance between the locations can also be displayed for the user to get an understanding of a distance between the deals.

[0058] FIG. 3 is a flowchart of a process for providing deal combinations, according to one embodiment. In one embodiment, the deal combination platform 103 performs the process 300 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 9. In step 301 , the deal combination platform 103 receives a request for deal information. The request for deal information includes an activity and criteria associated with the activity. By way of the example, the activity may be going on a date. The criteria may include a day and time for the date, a general location for the date, and a budget for the date. The request may also include a style or subtype for the activity. By way of example, if the activity is dating, the style or subtype of the activity may be that the date is in a romantic setting.

[0059] In step 303, the deal combination platform 103 determines the categories that are associated with the activity. In one embodiment, where the user selects an activity from a list of activities, step 303 is performed by cross-referencing the pre-assigned categories to the selected activity to determine the likelihood scores associated one or more deal category groupings. This step can be performed offline because the deal combination platform 103 does not need to access external sources to perform keyword searches. Alternatively, where the user enters text associated with an activity, the deal combination platform 103 determines the activity associated with the entered text and proceeds to determine likelihood scores associated with deal categories with respect to the entered text. However, whether the likelihood scores are already determined based on pre-defined activities, or if the likelihood scores are determined for deal category groupings upon receiving a request for deal information, the likelihood scores are determined the same way.

[0060] Specifically, deal categories are grouped together (e.g., paired together) and a likelihood score for each deal category grouping is determined by, for example, performing key word searches describing the deal categories for each deal category grouping along with the activity on the Internet. By way of example, for an activity such as dating, deal category groupings of {flower, dinner} , {dinner, movie} and {dinner, soccer} are created to determine whether each one of the respective deal categories is related to dating. Each deal category is then associated with the activity of dating in, for example, a keyword search using a search engine on the Internet. The number of results returned for each deal category grouping associated with the activity is determined and normalized according to a set normalization factor. The resulting score is the likelihood score indicating the likelihood that the deal category grouping is associated with the activity. By way of example, the above deal category groupings may result in likelihood scores of: {flower, dinner} = 0.8, {dinner, movie} = 0.9 and {dinner, soccer} = 0.1. Based on these scores, there is a high likelihood that the deal category groupings {flower, dinner} and {dinner, movie} are associated with the activity dating. Further, there is a low likelihood that {dinner, movie} is related to the activity dating. Thus, according to the above method, the deal category groupings are associated with a likelihood score indicating the likelihood that the deal categories are associated with the activity.

[0061] In step 305, the deal combination platform 103 selects from among the deal category groupings the one or more deal category groupings that satisfy a certain deal category threshold, the threshold dividing the deal category groupings into groupings that are sufficiently associated with the activity and groupings that are insufficiently associated with the activity. By way of example, where the likelihood scores of the deal category groupings are normalized between 0 to 1, the threshold value may be 0.5. Thus, any deal category grouping that does not have a likelihood score of above 0.5 is excluded from the process of generating deal combinations.

[0062] In step 307, the deal combination platform 103 determines one or more deals associated with the deal categories. The deal combination platform 103 queries the deal database 115, the services platform 107, the content providers 113, or a combination thereof for deals associated with the deal categories. By way of example, if one of the deal categories deemed associated with the activity within the request is restaurants, the deal combination platform 103 determines all of the deals related to restaurants. Upon gathering the deals, the deal combination platform 103 registers any new deals acquired from the services platform 107 and/or the content providers 113 with the deal database 115 for use later in the process 300.

[0063] Further, upon gathering the deals, the deal combination platform 103 determines the deals that satisfy the criteria associated with the request for deal information. By way of example, if the request for deal information includes criteria regarding a specific location and a specific date and time that the user wants to accomplish the activity, the deal combination platform determines all of the deals that satisfy the location and date and time criteria. The deal combination platform 103 performs this analysis by comparing the criteria associated with the request for deal information with the deal characteristics of each respective deal. The deal characteristics may have limitations regarding a date and time that the deal is valid. Further, the deal characteristics may have limitations regarding locations where the deal is valid. By determining the deals that satisfy the criteria entered by the user and associated with the request for deal information, the deal combination platform 103 excludes any invalid deals and provides better deal combinations for the user.

[0064] Upon determining all of the deals associated with the respective deal categories of the deal category groupings that are above the threshold likelihood value, the process 300 proceeds to step 309 and associates the collected deals with the respective deal category groupings based on the respective deal categories the deals are associated with. Thus, by way of example, for the above-two deal category groupings that satisfied the threshold score {flower, dinner} and {dinner, movie}, the deal combination platform 103 associates deals with the deal category groupings to form one or more deal groupings. Such deal groupings for the above-two deal category groupings are, for example, {Save 40% @ Joe's Flowers, Lovers' Combo @ Justin's BBQ} and {Lovers' Combo @ Justin's BBQ, $50 Off @ SoShow Movies} .

[0065] After associating deals with the associated deal categories of respective deal category groupings, the process 300 proceeds to step 311. At step 311, the deal combination platform 103 groups two or more deal groupings that share at least one deal together to form one or more additional deal grouping. By way of example with respect to the above-two deal groupings, {Save 40% @ Joe's Flowers, Lovers' Combo @ Justin's BBQ} and {Lovers' Combo @ Justin's BBQ, $50 Off @ SoShow Movies} , the deal groupings share at least one deal, namely {Lovers' Combo @ Justin's BBQ} . Thus, the two deal groupings can be combined to form a deal grouping of {Save 40% @ Joe's Flowers, Lovers' Combo @ Justin's BBQ, $50 Off @ SoShow Movies} . As discussed in detail with respect to FIG. 4, deal groupings can be further combined based on shared deals between larger and larger groupings of deals. However, after the deal groupings have been combined such there are no more shared deals between deal groupings, or such that the number of deals in the deal groupings matches a set number of deals defined by the user as one of the criteria of the request, the deal combination platform 103 stops generating the deal combinations and proceeds to step 313.

[0066] At step 313, the deal combination platform 103 validates the deals of the one or more deal combinations. The deal combination platform 103 determines the deal characteristics of the respective deals for each deal combinations and determines whether any of the deal characteristics conflict with other deal characteristics of deals within the same deal combination. The deal combination platform 103 also determines whether any of the deal characteristics conflict with any of the criteria associated with the request for deal information to further ensure that the deals satisfy the criteria. If any deal combinations contain deals that have conflicting deals characteristics, or if any deal with a deal combination does not satisfy the criteria, the deal combination platform 103 discards the deal combination.

[0067] In step 313, the deal combination platform 103 also validates the deal combinations based on the likelihood scores associated with the deal combinations. As the deal groupings are combined to form deal groupings with more and more deals, eventually leading to the deal combinations, the respective likelihood scores of the deals groupings are combined to form the likelihood scores of the deal combinations. To ensure that the deals within the deal combinations are sufficiently related to the activity, the deal combination platform 103 compares the likelihood scores of the deal combinations with another threshold likelihood score. Deal combinations with likelihood scores that do not satisfy the additional threshold likelihood scores are discarded and not presented to the user. [0068] At step 315, the deal combination platform 103 presents the one or more deal combinations to the UE 101 (and associated user) that requested the deal information. In one embodiment, the deal combination platform 103 presents the deal combinations in list form. In one embodiment, the deal combination platform 103 presents the deals of a deal combination overlaid on a map of the area surrounding the locations associated with the specific deals. Thus, the deal combination platform 103 can visualize for the user the area the user has to travel in order to execute the deals of a deal combination. In presenting the map view with the overlaid locations associated with the deals, the deal combination platform 103 also lists other deal combinations so the user can cycle through the deal combinations to get a better idea of the locations of the deals compared to other deal combinations.

[0069] When presenting the generated deal combinations, the deal combination platform 103 can rank the presented deals based on various factors including, for example, the likelihood scores associated with the deal combinations, the total budget required to accomplish the activity associated with the request and the specific deals of each deal combination, the total savings associated with the deal combination, or the like. Thus, in one embodiment, the deal combination platform 103 may present the deal combinations according to the likelihood score that the deal combination is associated with the activity, with the deal combinations that have the highest likelihood score appearing first. In one embodiment, the deal combination platform may present the deal combinations according to the total budget required to accomplish the activity or the total savings generated by the deal combination, with either the highest or lowest amounts listed first. In one embodiment, the deal combination platform 103 may present the deal combinations ranked according to several of the above approaches. For example, the deal combination platform 103 may rank the deal combinations according to likelihood scores, with deal combinations having similar likelihood scores further ranked by total budget, and with deal combinations having similar total budgets further ranked by total savings.

[0070] In one embodiment, the deal combination platform 103 sorts the deals of respective deal combinations based on the time restraints for executing the deals. For example, some deals have deal characteristics regarding what time of the day the deals are valid, or are associated with locations that have restrictions regarding when the locations are open. The deal combination platform 103 can sort the deals according to order in which should act on the deals to ensure that the user can use all of the deals within a deal combination.

[0071] In one embodiment, the user can select the method in which the deal combination platform ranks the deal combinations. In one embodiment, the deal combination platform 103 automatically sorts the deal combinations based on a default setting.

[0072] FIG. 4 is a flowchart of a process 400 for determining one or more deal combinations associated with an activity, according to one embodiment. In one embodiment, the deal combination platform 103 performs the process 400 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 9. At step 401, the deal combination platform 103 determines one or more deal categories for which to determine whether they are associated with an activity. In one embodiment, the deal combination platform 103 may determine the deal categories from the deal database 115. In one embodiment, the deal combination platform 103 may determine additional deal categories from the services platform 107 and/or the content providers 113. The deal categories represent, for example, categories of goods and/or services related to consumers. However, the deal categories may represent any category associated with a good or a service that is for sale to any entity (e.g., consumer, retailer, manufacturer, or the like).

[0073] At step 403, the deal categories are grouped into one or more deal groupings. In one embodiment, each deal category is paired up with every other deal category to form deal category groupings of pairs of deal categories. Thus, for every N deal categories there are ((N) x (N-l))/2 unique deal category pairings. However, the deal categories can be grouped into any type of grouping (e.g., triples, quadruples, etc.).

[0074] At step 405, the deal category groupings and the associated activity are provided as keywords and searched together in external sources (e.g., the Internet, Google®) to determine a probability that the deal categories of the respective deal category groupings are related to the activity. The probability can be based on, for example, the number of documents that are found that contain the keywords associated with the activity and the deal categories. Upon finding the number of documents related to the keywords for the deal categories and the activity, the number of documents can be normalized based on a normalization factor to be between 0 to 1 , with 0 representing the deal categories and the activity are not related and with 1 representing the deal categories and the activity are related. The normalization factor can be based on, for example, the number of documents that are returned for the keyword searching the activity alone. Alternatively, the normalization factor can be based on, for example, the highest number of documents for the deal category pairing that is the most closely related to activity.

[0075] By way of example, an activity may be dating and two deal category groupings may be {restaurants, tires} and {restaurants, movie} . Upon performing a keyword search for the respective deal category groupings with respect to the activity dating, the deal category grouping {restaurants, tires} may have a low number of returned results (e.g., 100,000) and the deal category grouping {restaurants, movie} may have a high number of returned results (e.g., 10,000,000). Basing the normalization factor on the number of returned results for the activity alone (e.g., 20,000,000), the normalized likelihood score for {restaurants, tires} would be 0.005 and the normalized likelihood score for {restaurants, movie} would be 0.5. Thus, the deal category of {restaurants, tires} is not related to dating and the deal category of {restaurants, movies} is related to dating.

[0076] In one embodiment, the deal combination platform 103 can further modify the likelihood scores of deal category groupings. At step 407, the deal combination platform 103 determines user information to adjust the likelihood score associated with the one or more deal category groupings and/or deal groupings for generating the one or more deal combinations. As discussed above, the user information can include, prior rankings by the user of historical suggestions of deals, recommendations, and locations associated with the deals or recommendations (e.g., restaurants, cities, parks, playgrounds, bars, clubs, sports venues, music venues, etc.); prior activity of the user regarding suggestions of deals and/or deal locations, and other usage data, such as browser history. The user information can include any type of context information that can be gathered by the deal combination platform 103 from the UE 101, the sensors 117, the services platform 107, the content providers 113, or a combination thereof. Thus, the deal combination platform 103 can provide more personalized deal recommendations based on likelihood scores of deal category groupings that consider personalized user information of the user that requested the deal information. At step 409, the deal combination platform 103 further modifies the likelihood scores of the one or more deal category groupings to take into account the personalized information of the user that requested information pertaining to deal combinations.

[0077] FIG. 5 is a flowchart of a process 500 for combining deals into one or more deal combinations, according to one embodiment. In one embodiment, the deal combination platform 103 performs the process 500 and is implemented in, for instance, a chip set including a processor and a memory as shown in FIG. 9. At step 503, after step 501, which corresponds to step 309 of process 300, the deal combination platform 103 associates the likelihood scores of the deal category groupings with the deal groupings generated by associating deals with the respective deal categories of the deal category groupings. Accordingly, the deal groupings are associated with likelihood scores that similarly indicate the likelihood that the deal groupings are associated with the activity. In one embodiment, where the likelihood scores were determined for deal category groupings consisting of two deal categories, the deal groupings at the beginning of the process 500 may only include two deals. However, the deal groupings at the beginning of process 500 may contain any number of deals.

[0078] At step 505, the deal combination platform 103 ranks the deal groupings according to their likelihood scores in a descending order. Thus, the deal groupings that have higher likelihood scores precede deal groupings that have lower likelihood scores.

[0079] At step 507, the deal combination platform 103 determines a first deal grouping starting at the top of the list of deal groupings that has the highest likelihood score and that shares at least one deal with another deal grouping.

[0080] At step 509, the deal combination platform 103 determines the next highest deal grouping (e.g., a second deal grouping) that shares at least the same deal as the first deal grouping.

[0081] At step 511 , the deal combination platform 103 groups the first deal grouping and the second deal grouping to generate a 2nd-level deal grouping. In other words, if the first deal grouping and the second deal grouping each included two deals, one of which was shared between the two deal groupings, the 2nd-level deal grouping contains three deals, including the one shared deal and possibly two other deals that were not shared. Thus, the 2nd-level deal grouping has a larger number of deals than the first deal grouping and the second deal grouping. [0082] At step 513, the deal combination platform 103 determines the likelihood score for the 2nd-level deal grouping. In one embodiment, the likelihood score of the 2nd-level deal grouping is the average of the likelihood scores of the deal groupings that formed the 2nd-level deal grouping, i.e., the likelihood score of the first deal grouping and the likelihood score the second deal grouping. In one embodiment, the likelihood score of the 2nd-level deal grouping is the product of the likelihood scores of the deal groupings that formed the 2nd-level deal grouping. Thus, by way of example, if the likelihood scores of the first deal grouping and the second deal grouping were 0.8 and 0.9, respectively, under the first approach the likelihood score of the resulting 2nd-level deal grouping is 0.85. Under the second approach, the likelihood scores of the resulting 2nd-level deal grouping is 0.72.

[0083] At step 515, the deal combination platform 103 determines whether there are any more deals that are shared between deal groupings, excluding any 2nd-level deal groupings. If there are more shared deals, the process 500 proceeds back to step 507 and continues grouping deal groupings that share at least one common deal, excluding any 2nd-level deal groupings. If there are no more shared deals between the deal groupings, excluding any 2nd-level deal groupings, the process 500 proceeds to step 517.

[0084] At step 517, the deal combination platform 103 determines a first 2nd-level deal grouping starting at the top of the list of 2nd-level deal groupings that have the highest likelihood scores that shares at least one deal with another 2nd-level deal grouping.

[0085] At step 519, the deal combination platform 103 determines the next highest 2nd-level deal grouping (e.g., a second 2nd-level deal grouping) that shares at least the same deal as the first 2nd-level deal grouping.

[0086] At step 521, the deal combination platform 103 groups the first 2nd-level deal grouping and the second 2nd-level deal grouping to generate a 3rd-level deal grouping. In other words, if the first 2nd-level deal grouping and the second 2nd-level deal grouping each included three deals, one of which was shared between the two 2nd-level deal groupings, the 3rd-level deal grouping contains five deals, including the one shared deal and possibly four other deals that were not shared. Thus, the 3rd-level deal grouping has a larger number of deals than the first 2nd-level deal grouping and the second 2nd-level deal grouping. [0087] At step 523, the deal combination platform 103 determines the likelihood score for the 3rd-level deal grouping. In one embodiment, the likelihood score of the 3rd-level deal grouping is the average of the likelihood scores of the deal groupings that formed the 3rd-level deal grouping, i.e., the likelihood score of the first 2nd-level deal grouping and the likelihood score the second 2nd-level deal grouping, as discussed above. In one embodiment, the likelihood score of the 2nd-level deal grouping is the product of the likelihood scores of the deal groupings that formed the 2nd-level deal grouping.

[0088] At step 525, the deal combination platform 103 determines whether there are any more deals that are shared between 2nd-level deal groupings, excluding any 3rd-level deal groupings. If there are more shared deals, the process 500 proceeds back to step 517 and continues grouping 2nd-level deal groupings that share at least one common deal. If there are no more shared deals between the 2nd-level deal groupings, excluding any 3rd-level deal groupings, the process 500 keeps repeating process steps 517-523 for increasing levels of deal groupings until the latest created level of deal groupings do not share a deal in common (e.g., Nth-level deal groupings were created but do not share a deal in common). Alternatively, the deal combination platform 103 continues repeating process steps 517-523 until the set number of deals per deal combination is reached, as defined by criteria in the request for deal information. In one embodiment, a shared deal between two deal groupings is based on the specific deal. In one embodiment, a shared deal between two deal groupings is based on the category of the deal.

[0089] FIG. 6 is a diagram of a user interface 601 utilized in the processes of FIGs. 3-5, according to one embodiment. The user interface 601 includes an indicator 603 that allows a user to enter an activity to generate a request for deal information. In one embodiment, the indicator 603 can be in the form of a text box that accept textual entries by the user. In one embodiment, the indicator 603 can be in the form of a dropdown menu that includes pre-defined activities for the user to select from. By way of example, as illustrated in FIG. 6, the activity selected by the user in indicator 603 is Dating.

[0090] The user interface 601 may also include an indicator 605 that allows a user to enter a style or subtype of the activity to further define the activity. Like indicator 603, indicator 605 can be in the form of a text box that accepts textual entries by the user or may be in the form of a dropdown menu that includes pre-defined styles or subtypes of the pre-defined activities. By way of example, as illustrated in FIG. 6, the style or subtype selected by the user in indicator 605 is Romantic.

[0091] The user interface 601 may also include various indicators for entering criteria associated with the request for deal information related to an activity. By way of example, the user interface 601 includes indicators 607 and 609 for entering criteria associated with the activity. Indicator 607 allows the user to enter date information for when the activity will take place. Indicator 609 allows the user to enter budget information for how much or how little the user would like to spend to accomplish the activity. By way of example, as illustrated in FIG. 6, the date associated with the activity is August 16, 2011, and the budget associated with the activity is $500.

[0092] The user interface 601 also includes an indicator 611 that allows the user to initiate a query of deal combinations upon entering the activity information and the criteria in indicators 603-609. After initiating the query, the deal combination platform 103 generates one or more deal combinations 613a and 613b and displays the deal combination on the user interface 601. In one embodiment, the deal combination platform 103 can rank the presented deal combinations according to their respective likelihood scores. Thus, as illustrated in FIG. 6, the deal combination 613a has a higher likelihood score than the deal combination 613b so that the deal combination 613a is presented first. The presented deal combinations 613a and 613b include the various deals that are associated with each combination. Deal combination 613a includes deals 615a-615c. Although the deal combinations 615a-615c illustrated in FIG. 6 contain only three deals each, the deal combinations may contain fewer or more than three deals, as discussed above. The deals 615a-615c are presented along with their subject or category (e.g., flowers for deal 615a), the location associated with the deal (e.g., Justin's BBQ for deal 615b) and the specifics of the deal (e.g., 9 PM $100 $50 for deal 615c). In one embodiment, the specific deals may be presented in the order in which they should be executed within each deal combination based on the deal characteristics concerning times the deals are valid or concerning times the locations are open. In one embodiment, the specific deals may be presented in a random order within each deal combination. The deals combinations 615a-615c may also include the total cost associated with the deal combination and the total savings associated with the deal combination. Thus, for example, for deal combination 613a, the total cost associated with accomplishing the activity using the deal combination is $480 and the total savings is $200.

[0093] In one embodiment, the deal combination platform 103 may rank the presented deal combinations based on the total cost associated with the deal combinations to accomplish the task rather than the likelihood score of the deal combinations. In one embodiment, the deal combination platform 103 may rank the presented deal combinations based on the total savings associated with the deal combination rather than the likelihood score of the deal combinations.

[0094] In one embodiment, presented deals within the presented deal combinations may be selectable by the user and modified to belong to different deal combinations. Thus, by way of example, if the user wants to use deal combination 613a of FIG. 6, but the user would rather have a picnic prior to going to Justin's BBQ rather than buying flowers at Joe's Flowers, the user may select either one of deal 615a or deal 615d and move the selected deal to the other deal combination. In one embodiment, the user interface 601 is displayed on a touch screen. In which case, a user may simply drag and drop deals to re-arrange the deals within a deal combination. For example, the user may drag deal 615e (i.e., Dinner @ Toast) and drop it in place of deal 615b (i.e., Dinner @ Justin's BBQ). Thus, the deal combination platform 103 allows the user to further configure the deal combinations based on the user's preference to create additional alternatives to consider the deals. Upon switching one or more deals for one or more deal combinations, the deal combination platform 103 re-checks the validity for the newly created deal combinations, as discussed above, to ensure that the deal combinations are valid.

[0095] FIG. 7 is a diagram of an additional user interface 701 utilized in the processes of FIGs. 3-5, according to one embodiment. The user interface 701 includes an indicator 703 that displays the activity, style or subtype of activity, and criteria that the user entered to define the requested deal information. The user interface 701 also includes an indicator 705 that displays brief information regarding the deal combinations generated by the deal combination platform 103 based on the activity and criteria. In one embodiment, the brief information associated with the deal combinations illustrated in indicator 705 includes the total budget associated with the deals of the deal combination required to accomplish the task, and the total distance between locations associated with the respective deals. By way of example, for the deal combination associated with Option 1, the total budget is $480 and the total distance between locations associated with the deals is 20 km. The indicator 705 allows the user to select one of the deal combinations to present additional information regarding the deal combination.

[0096] The user interface 701 may also include indicator 707 that displays the specific deal information associated with the deal combination selected in indicator 705. By way of example, the specific deal information associated with Option 1 of the deal combinations is the same information associated with deal combination 613a in FIG. 6. The specific deals of the selected option may be presented in the order in which they should be executed according to their respective deal characteristics. Thus, for example, SoShow Movie accepts the deal after 9 PM, Justin's BBQ accepts the deal between 6-9 PM and Joe's Flowers may be open 24 hours a day. Accordingly, Joe's Flowers can come at the beginning or at the end, but SoShow Movie should come after Justin's BBQ.

[0097] The user interface 701 may also include a map 709 that displays the specific locations 71 la-71 lc associated with the deals of the selected deal combination. Inclusion of the map 709 that illustrates the specific locations 71 la-71 lc associated with the deals allows the user to better visualize a route required to navigate to the various locations to accomplish the deals. This allows, for example, the user to better understand whether to choose the selected deal combination or choose a different deal combination. The specific locations 71 la-71 lc can also be numbered according to the timeline in which the deals should be executed.

[0098] In one embodiment, the route between places can be calculated based on the times associated with the deals, as discussed above, and the route can be shown between locations associated with the various deals of a respective deal combination. By way of example, the route 715 illustrated in FIG. 7 starts from the user's current location 713 and proceeds to Joe's Flowers at indicator 71 la. Then, from Joe's Flowers the route 715 proceeds to Justin's BBQ at indicator 711b. Finally, from Justin's BBQ the route 715 proceeds to SoShow Movie at indicator 71 lc. In one embodiment, the route 715 is implemented by an interface between the deal combination platform 103 and a map application 111a running on the UE 101.

[0099] In one embodiment, an indicator 717 for enabling the display of the route 715 between deal locations on the map 109 can be generated. By way of example, the locations associated with the deals can be received by the map application 111a from the deal combination platform 103 by way of the names of the locations (e.g., names of restaurants, stores, and the like) that are recognized by the map application 111a or by of way coordinates. After selecting the indicator 717, the route can be shown using the map application 111a, such as the application Nokia maps on a Nokia device, taking into account where the user currently is located as the starting point for the route.

[0100] In one embodiment, the time to travel from place to place is important, such as when the deals include temporal restrictions, and the map application 111a can inform the user of the travel time between locations. In one embodiment, the deal combination platform 103 in combination with the map application 111a can provide the user indications or alerts associated with when the user should start or continue along the route 715 to the next location so as to not miss the deals. In one embodiment, the route planning may include traffic information or the like along the route in order to keep the user within a set timetable. In one embodiment, the deal combination platform 103 and/or the map application 111a can interface with a calendar application 111b running on the UE 101 to provide the user calendar type alerts to keep the user within a set timetable. Thus, the user can stay, for example, at a first location longer if the user finds the place interesting. Then, the map application 111a and/or calendar application 111b will alert the user at the appropriate time for the user to proceed to the next location.

[0101] As discussed above, the deals within a deal combination may relate to each other such that the user needs to use the deals in a predefined order or needs to use the deals within a predefined time. Under this approach, the map application 111a and/or calendar application 111b can follow the user's usage of time, where the user is currently located, transactions history, or the like to inform the user when to travel next location along the route 715. When completed, the device can give an advertisement of next deal.

[0102] The processes described herein for providing deal combinations may be advantageously implemented via software, hardware, firmware or a combination of software and/or firmware and/or hardware. For example, the processes described herein, may be advantageously implemented via processor(s), Digital Signal Processing (DSP) chip, an Application Specific Integrated Circuit (ASIC), Field Programmable Gate Arrays (FPGAs), etc. Such exemplary hardware for performing the described functions is detailed below.

[0103] FIG. 8 illustrates a computer system 800 upon which an embodiment of the invention may be implemented. Although computer system 800 is depicted with respect to a particular device or equipment, it is contemplated that other devices or equipment (e.g., network elements, servers, etc.) within FIG. 8 can deploy the illustrated hardware and components of system 800. Computer system 800 is programmed (e.g., via computer program code or instructions) to provide deal combinations as described herein and includes a communication mechanism such as a bus 810 for passing information between other internal and external components of the computer system 800. Information (also called data) is represented as a physical expression of a measurable phenomenon, typically electric voltages, but including, in other embodiments, such phenomena as magnetic, electromagnetic, pressure, chemical, biological, molecular, atomic, subatomic and quantum interactions. For example, north and south magnetic fields, or a zero and non-zero electric voltage, represent two states (0, 1) of a binary digit (bit). Other phenomena can represent digits of a higher base. A superposition of multiple simultaneous quantum states before measurement represents a quantum bit (qubit). A sequence of one or more digits constitutes digital data that is used to represent a number or code for a character. In some embodiments, information called analog data is represented by a near continuum of measurable values within a particular range. Computer system 800, or a portion thereof, constitutes a means for performing one or more steps of providing deal combinations.

[0104] A bus 810 includes one or more parallel conductors of information so that information is transferred quickly among devices coupled to the bus 810. One or more processors 802 for processing information are coupled with the bus 810.

[0105] A processor (or multiple processors) 802 performs a set of operations on information as specified by computer program code related to provide deal combinations. The computer program code is a set of instructions or statements providing instructions for the operation of the processor and/or the computer system to perform specified functions. The code, for example, may be written in a computer programming language that is compiled into a native instruction set of the processor. The code may also be written directly using the native instruction set (e.g., machine language). The set of operations include bringing information in from the bus 810 and placing information on the bus 810. The set of operations also typically include comparing two or more units of information, shifting positions of units of information, and combining two or more units of information, such as by addition or multiplication or logical operations like OR, exclusive OR (XOR), and AND. Each operation of the set of operations that can be performed by the processor is represented to the processor by information called instructions, such as an operation code of one or more digits. A sequence of operations to be executed by the processor 802, such as a sequence of operation codes, constitute processor instructions, also called computer system instructions or, simply, computer instructions. Processors may be implemented as mechanical, electrical, magnetic, optical, chemical or quantum components, among others, alone or in combination.

[0106] Computer system 800 also includes a memory 804 coupled to bus 810. The memory 804, such as a random access memory (RAM) or any other dynamic storage device, stores information including processor instructions for providing deal combinations. Dynamic memory allows information stored therein to be changed by the computer system 800. RAM allows a unit of information stored at a location called a memory address to be stored and retrieved independently of information at neighboring addresses. The memory 804 is also used by the processor 802 to store temporary values during execution of processor instructions. The computer system 800 also includes a read only memory (ROM) 806 or any other static storage device coupled to the bus 810 for storing static information, including instructions, that is not changed by the computer system 800. Some memory is composed of volatile storage that loses the information stored thereon when power is lost. Also coupled to bus 810 is a non-volatile (persistent) storage device 808, such as a magnetic disk, optical disk or flash card, for storing information, including instructions, that persists even when the computer system 800 is turned off or otherwise loses power.

[0107] Information, including instructions for providing deal combinations, is provided to the bus 810 for use by the processor from an external input device 812, such as a keyboard containing alphanumeric keys operated by a human user, a microphone, an Infrared (IR) remote control, a joystick, a game pad, a stylus pen, a touch screen, or a sensor. A sensor detects conditions in its vicinity and transforms those detections into physical expression compatible with the measurable phenomenon used to represent information in computer system 800. Other external devices coupled to bus 810, used primarily for interacting with humans, include a display device 814, such as a cathode ray tube (CRT), a liquid crystal display (LCD), a light emitting diode (LED) display, an organic LED (OLED) display, a plasma screen, or a printer for presenting text or images, and a pointing device 816, such as a mouse, a trackball, cursor direction keys, or a motion sensor, for controlling a position of a small cursor image presented on the display 814 and issuing commands associated with graphical elements presented on the display 814. In some embodiments, for example, in embodiments in which the computer system 800 performs all functions automatically without human input, one or more of external input device 812, display device 814 and pointing device 816 is omitted.

[0108] In the illustrated embodiment, special purpose hardware, such as an application specific integrated circuit (ASIC) 820, is coupled to bus 810. The special purpose hardware is configured to perform operations not performed by processor 802 quickly enough for special purposes. Examples of ASICs include graphics accelerator cards for generating images for display 814, cryptographic boards for encrypting and decrypting messages sent over a network, speech recognition, and interfaces to special external devices, such as robotic arms and medical scanning equipment that repeatedly perform some complex sequence of operations that are more efficiently implemented in hardware.

[0109] Computer system 800 also includes one or more instances of a communications interface 870 coupled to bus 810. Communication interface 870 provides a one-way or two- way communication coupling to a variety of external devices that operate with their own processors, such as printers, scanners and external disks. In general the coupling is with a network link 878 that is connected to a local network 880 to which a variety of external devices with their own processors are connected. For example, communication interface 870 may be a parallel port or a serial port or a universal serial bus (USB) port on a personal computer. In some embodiments, communications interface 870 is an integrated services digital network (ISDN) card or a digital subscriber line (DSL) card or a telephone modem that provides an information communication connection to a corresponding type of telephone line. In some embodiments, a communication interface 870 is a cable modem that converts signals on bus 810 into signals for a communication connection over a coaxial cable or into optical signals for a communication connection over a fiber optic cable. As another example, communications interface 870 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN, such as Ethernet. Wireless links may also be implemented. For wireless links, the communications interface 870 sends or receives or both sends and receives electrical, acoustic or electromagnetic signals, including infrared and optical signals, that carry information streams, such as digital data. For example, in wireless handheld devices, such as mobile telephones like cell phones, the communications interface 870 includes a radio band electromagnetic transmitter and receiver called a radio transceiver. In certain embodiments, the communications interface 870 enables connection to the communication network 105 for providing deal combinations to the UE 101.

[0110] The term "computer-readable medium" as used herein refers to any medium that participates in providing information to processor 802, including instructions for execution. Such a medium may take many forms, including, but not limited to computer-readable storage medium (e.g., non-volatile media, volatile media), and transmission media. Non-transitory media, such as non-volatile media, include, for example, optical or magnetic disks, such as storage device 808. Volatile media include, for example, dynamic memory 804. Transmission media include, for example, twisted pair cables, coaxial cables, copper wire, fiber optic cables, and carrier waves that travel through space without wires or cables, such as acoustic waves and electromagnetic waves, including radio, optical and infrared waves. Signals include man-made transient variations in amplitude, frequency, phase, polarization or other physical properties transmitted through the transmission media. Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, CDRW, DVD, any other optical medium, punch cards, paper tape, optical mark sheets, any other physical medium with patterns of holes or other optically recognizable indicia, a RAM, a PROM, an EPROM, a FLASH-EPROM, an EEPROM, a flash memory, any other memory chip or cartridge, a carrier wave, or any other medium from which a computer can read. The term computer-readable storage medium is used herein to refer to any computer-readable medium except transmission media. [0111] Logic encoded in one or more tangible media includes one or both of processor instructions on a computer-readable storage media and special purpose hardware, such as ASIC 820.

[0112] Network link 878 typically provides information communication using transmission media through one or more networks to other devices that use or process the information. For example, network link 878 may provide a connection through local network 880 to a host computer 882 or to equipment 884 operated by an Internet Service Provider (ISP). ISP equipment 884 in turn provides data communication services through the public, world-wide packet-switching communication network of networks now commonly referred to as the Internet 890.

[0113] A computer called a server host 892 connected to the Internet hosts a process that provides a service in response to information received over the Internet. For example, server host 892 hosts a process that provides information representing video data for presentation at display 814. It is contemplated that the components of system 800 can be deployed in various configurations within other computer systems, e.g., host 882 and server 892.

[0114] At least some embodiments of the invention are related to the use of computer system 800 for implementing some or all of the techniques described herein. According to one embodiment of the invention, those techniques are performed by computer system 800 in response to processor 802 executing one or more sequences of one or more processor instructions contained in memory 804. Such instructions, also called computer instructions, software and program code, may be read into memory 804 from another computer-readable medium such as storage device 808 or network link 878. Execution of the sequences of instructions contained in memory 804 causes processor 802 to perform one or more of the method steps described herein. In alternative embodiments, hardware, such as ASIC 820, may be used in place of or in combination with software to implement the invention. Thus, embodiments of the invention are not limited to any specific combination of hardware and software, unless otherwise explicitly stated herein.

[0115] The signals transmitted over network link 878 and other networks through communications interface 870, carry information to and from computer system 800. Computer system 800 can send and receive information, including program code, through the networks 880, 890 among others, through network link 878 and communications interface 870. In an example using the Internet 890, a server host 892 transmits program code for a particular application, requested by a message sent from computer 800, through Internet 890, ISP equipment 884, local network 880 and communications interface 870. The received code may be executed by processor 802 as it is received, or may be stored in memory 804 or in storage device 808 or any other non-volatile storage for later execution, or both. In this manner, computer system 800 may obtain application program code in the form of signals on a carrier wave.

[0116] Various forms of computer readable media may be involved in carrying one or more sequence of instructions or data or both to processor 802 for execution. For example, instructions and data may initially be carried on a magnetic disk of a remote computer such as host 882. The remote computer loads the instructions and data into its dynamic memory and sends the instructions and data over a telephone line using a modem. A modem local to the computer system 800 receives the instructions and data on a telephone line and uses an infra-red transmitter to convert the instructions and data to a signal on an infra-red carrier wave serving as the network link 878. An infrared detector serving as communications interface 870 receives the instructions and data carried in the infrared signal and places information representing the instructions and data onto bus 810. Bus 810 carries the information to memory 804 from which processor 802 retrieves and executes the instructions using some of the data sent with the instructions. The instructions and data received in memory 804 may optionally be stored on storage device 808, either before or after execution by the processor 802.

[0117] FIG. 9 illustrates a chip set or chip 900 upon which an embodiment of the invention may be implemented. Chip set 900 is programmed to provide deal combinations as described herein and includes, for instance, the processor and memory components described with respect to FIG. 8 incorporated in one or more physical packages (e.g., chips). By way of example, a physical package includes an arrangement of one or more materials, components, and/or wires on a structural assembly (e.g., a baseboard) to provide one or more characteristics such as physical strength, conservation of size, and/or limitation of electrical interaction. It is contemplated that in certain embodiments the chip set 900 can be implemented in a single chip. It is further contemplated that in certain embodiments the chip set or chip 900 can be implemented as a single "system on a chip." It is further contemplated that in certain embodiments a separate ASIC would not be used, for example, and that all relevant functions as disclosed herein would be performed by a processor or processors. Chip set or chip 900, or a portion thereof, constitutes a means for performing one or more steps of providing user interface navigation information associated with the availability of functions. Chip set or chip 900, or a portion thereof, constitutes a means for performing one or more steps of providing deal combinations.

[0118] In one embodiment, the chip set or chip 900 includes a communication mechanism such as a bus 901 for passing information among the components of the chip set 900. A processor 903 has connectivity to the bus 901 to execute instructions and process information stored in, for example, a memory 905. The processor 903 may include one or more processing cores with each core configured to perform independently. A multi-core processor enables multiprocessing within a single physical package. Examples of a multi-core processor include two, four, eight, or greater numbers of processing cores. Alternatively or in addition, the processor 903 may include one or more microprocessors configured in tandem via the bus 901 to enable independent execution of instructions, pipelining, and multithreading. The processor 903 may also be accompanied with one or more specialized components to perform certain processing functions and tasks such as one or more digital signal processors (DSP) 907, or one or more application-specific integrated circuits (ASIC) 909. A DSP 907 typically is configured to process real-world signals (e.g., sound) in real time independently of the processor 903. Similarly, an ASIC 909 can be configured to performed specialized functions not easily performed by a more general purpose processor. Other specialized components to aid in performing the inventive functions described herein may include one or more field programmable gate arrays (FPGA), one or more controllers, or one or more other special- purpose computer chips.

[0119] In one embodiment, the chip set or chip 900 includes merely one or more processors and some software and/or firmware supporting and/or relating to and/or for the one or more processors. [0120] The processor 903 and accompanying components have connectivity to the memory 905 via the bus 901. The memory 905 includes both dynamic memory (e.g., RAM, magnetic disk, writable optical disk, etc.) and static memory (e.g., ROM, CD-ROM, etc.) for storing executable instructions that when executed perform the inventive steps described herein to provide deal combination. The memory 905 also stores the data associated with or generated by the execution of the inventive steps.

[0121] FIG. 10 is a diagram of exemplary components of a mobile terminal (e.g., handset) for communications, which is capable of operating in the system of FIG. 1 , according to one embodiment. In some embodiments, mobile terminal 1001 , or a portion thereof, constitutes a means for performing one or more steps of providing deal combinations. Generally, a radio receiver is often defined in terms of front-end and back-end characteristics. The front-end of the receiver encompasses all of the Radio Frequency (RF) circuitry whereas the back-end encompasses all of the base-band processing circuitry. As used in this application, the term "circuitry" refers to both: (1) hardware-only implementations (such as implementations in only analog and/or digital circuitry), and (2) to combinations of circuitry and software (and/or firmware) (such as, if applicable to the particular context, to a combination of processor(s), including digital signal processor(s), software, and memory(ies) that work together to cause an apparatus, such as a mobile phone or server, to perform various functions). This definition of "circuitry" applies to all uses of this term in this application, including in any claims. As a further example, as used in this application and if applicable to the particular context, the term "circuitry" would also cover an implementation of merely a processor (or multiple processors) and its (or their) accompanying software/or firmware. The term "circuitry" would also cover if applicable to the particular context, for example, a baseband integrated circuit or applications processor integrated circuit in a mobile phone or a similar integrated circuit in a cellular network device or other network devices.

[0122] Pertinent internal components of the telephone include a Main Control Unit (MCU) 1003, a Digital Signal Processor (DSP) 1005, and a receiver/transmitter unit including a microphone gain control unit and a speaker gain control unit. A main display unit 1007 provides a display to the user in support of various applications and mobile terminal functions that perform or support the steps of providing deal combinations. The display 1007 includes display circuitry configured to display at least a portion of a user interface of the mobile terminal (e.g., mobile telephone). Additionally, the display 1007 and display circuitry are configured to facilitate user control of at least some functions of the mobile terminal. An audio function circuitry 1009 includes a microphone 1011 and microphone amplifier that amplifies the speech signal output from the microphone 1011. The amplified speech signal output from the microphone 1011 is fed to a coder/decoder (CODEC) 1013.

[0123] A radio section 1015 amplifies power and converts frequency in order to communicate with a base station, which is included in a mobile communication system, via antenna 1017. The power amplifier (PA) 1019 and the transmitter/modulation circuitry are operationally responsive to the MCU 1003, with an output from the PA 1019 coupled to the duplexer 1021 or circulator or antenna switch, as known in the art. The PA 1019 also couples to a battery interface and power control unit 1020.

[0124] In use, a user of mobile terminal 1001 speaks into the microphone 1011 and his or her voice along with any detected background noise is converted into an analog voltage. The analog voltage is then converted into a digital signal through the Analog to Digital Converter (ADC) 1023. The control unit 1003 routes the digital signal into the DSP 1005 for processing therein, such as speech encoding, channel encoding, encrypting, and interleaving. In one embodiment, the processed voice signals are encoded, by units not separately shown, using a cellular transmission protocol such as enhanced data rates for global evolution (EDGE), general packet radio service (GPRS), global system for mobile communications (GSM), Internet protocol multimedia subsystem (IMS), universal mobile telecommunications system (UMTS), etc., as well as any other suitable wireless medium, e.g., microwave access (WiMAX), Long Term Evolution (LTE) networks, code division multiple access (CDMA), wideband code division multiple access (WCDMA), wireless fidelity (WiFi), satellite, and the like, or any combination thereof.

[0125] The encoded signals are then routed to an equalizer 1025 for compensation of any frequency-dependent impairments that occur during transmission though the air such as phase and amplitude distortion. After equalizing the bit stream, the modulator 1027 combines the signal with a RF signal generated in the RF interface 1029. The modulator 1027 generates a sine wave by way of frequency or phase modulation. In order to prepare the signal for transmission, an up-converter 1031 combines the sine wave output from the modulator 1027 with another sine wave generated by a synthesizer 1033 to achieve the desired frequency of transmission. The signal is then sent through a PA 1019 to increase the signal to an appropriate power level. In practical systems, the PA 1019 acts as a variable gain amplifier whose gain is controlled by the DSP 1005 from information received from a network base station. The signal is then filtered within the duplexer 1021 and optionally sent to an antenna coupler 1035 to match impedances to provide maximum power transfer. Finally, the signal is transmitted via antenna 1017 to a local base station. An automatic gain control (AGC) can be supplied to control the gain of the final stages of the receiver. The signals may be forwarded from there to a remote telephone which may be another cellular telephone, any other mobile phone or a land-line connected to a Public Switched Telephone Network (PSTN), or other telephony networks.

[0126] Voice signals transmitted to the mobile terminal 1001 are received via antenna 1017 and immediately amplified by a low noise amplifier (LNA) 1037. A down-converter 1039 lowers the carrier frequency while the demodulator 1041 strips away the RF leaving only a digital bit stream. The signal then goes through the equalizer 1025 and is processed by the DSP 1005. A Digital to Analog Converter (DAC) 1043 converts the signal and the resulting output is transmitted to the user through the speaker 1045, all under control of a Main Control Unit (MCU) 1003 which can be implemented as a Central Processing Unit (CPU).

[0127] The MCU 1003 receives various signals including input signals from the keyboard 1047. The keyboard 1047 and/or the MCU 1003 in combination with other user input components (e.g., the microphone 1011) comprise a user interface circuitry for managing user input. The MCU 1003 runs a user interface software to facilitate user control of at least some functions of the mobile terminal 1001 to provide deal combinations. The MCU 1003 also delivers a display command and a switch command to the display 1007 and to the speech output switching controller, respectively. Further, the MCU 1003 exchanges information with the DSP 1005 and can access an optionally incorporated SFM card 1049 and a memory 1051. In addition, the MCU 1003 executes various control functions required of the terminal. The DSP 1005 may, depending upon the implementation, perform any of a variety of conventional digital processing functions on the voice signals. Additionally, DSP 1005 determines the background noise level of the local environment from the signals detected by microphone 1011 and sets the gain of microphone 1011 to a level selected to compensate for the natural tendency of the user of the mobile terminal 1001.

[0128] The CODEC 1013 includes the ADC 1023 and DAC 1043. The memory 1051 stores various data including call incoming tone data and is capable of storing other data including music data received via, e.g., the global Internet. The software module could reside in RAM memory, flash memory, registers, or any other form of writable storage medium known in the art. The memory device 1051 may be, but not limited to, a single memory, CD, DVD, ROM, RAM, EEPROM, optical storage, magnetic disk storage, flash memory storage, or any other non-volatile storage medium capable of storing digital data.

[0129] An optionally incorporated SIM card 1049 carries, for instance, important information, such as the cellular phone number, the carrier supplying service, subscription details, and security information. The SIM card 1049 serves primarily to identify the mobile terminal 1001 on a radio network. The card 1049 also contains a memory for storing a personal telephone number registry, text messages, and user specific mobile terminal settings.

[0130] While the invention has been described in connection with a number of embodiments and implementations, the invention is not so limited but covers various obvious modifications and equivalent arrangements, which fall within the purview of the appended claims. Although features of the invention are expressed in certain combinations among the claims, it is contemplated that these features can be arranged in any combination and order.

Claims

CLAIMS WHAT IS CLAIMED IS:

1. A method comprising facilitating a processing of and/or processing (1) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the following:

a request for deal information, the request specifying at least one activity, one or more

criteria for performing the at least one activity, or a combination thereof;

a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations; and

a presentation of the one or more deal combinations in response to the request.

2. A method of claim 1 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a determination of at least one or more respective likelihood scores of one or more deal

category groupings based, at least in part, on a probability that the one or more deal category groupings are associated with the at least one activity;

a processing of the one or more respective likelihood scores to select from among the one or more deal category groupings; and

a determination of at least the one or more deals, the one or more deal combinations, or a combination thereof based, at least in part, on the selected one or more deal category groupings.

3. A method of claim 2, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: a grouping of the one or more deals into the one or more deal combinations based, at least in part, on one or more shared deals associated with two or more of the selected one or more deal category groupings.

4. A method according to any of claims 2 and 3, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a grouping of the one or more deals into one or more deal groupings based, at least in part, on the selected one or more deal category groupings; and

a determination of at least the one or more deal combinations based, at least in part, on one or more shared deals associated with two or more deals groupings.

5. A method of claim 4, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

an association of the one or more respective likelihood scores of the selected one or more deal category groupings with respective ones of the one or more deal groupings, wherein the one or more deal combinations are based, at least in part, on the respective

likelihood scores of the one or more deals groupings.

6. A method according to any of claims 4 and 5, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a ranking of the one or more deal groupings based, at least in part, on the one more respective likelihood scores of one or more respective deal category groupings; and

a grouping of the one or more deals into the one or more deal combinations based, at least in part, on one or more shared deals between a deal grouping of a highest likelihood score and a deal grouping of a next highest likelihood score.

7. A method according to any of claims 2-6, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

an adjustment of the one or more respective likelihood scores based, at least in part, on

information associated with a user, wherein the at least one activity is associated with the user.

8. A method according to any of claims 2-7, wherein the selection from among the one or more deal category groupings is based, at least in part, on the respective likelihood scores satisfying at least one threshold likelihood score.

9. A method according to any of claims 1-8, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a determination of at least the one or more deals based, at least in part, on the one or more deals satisfying the one or more criteria for performing the at least one activity.

10. A method of claim 9, wherein the one or more criteria include a time criteria, a location criteria, a budget criteria, or a combination thereof.

11. A method according to any of claims 1-10, wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following:

a validation of the one or more deal combinations based, at least in part, on agreement

between one or more deal characteristics of respective deals of the one or more deal combinations, one or more criteria for performing the at least one activity, or a combination thereof,

wherein the presentation of the one or more deal combinations is a presentation of one or more validated deal combinations.

12. A method of claim 11, wherein the deal characteristics include temporal characteristics, location characteristics, budget characteristics, deal grouping characteristics, or a combination thereof.

13. An apparatus comprising:

at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following,

receive a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof; process and/or facilitating a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations; and

cause, at least in part, a presentation of the one or more deal combinations in response to the request.

14. An apparatus of claim 13, wherein the apparatus is further caused to:

determine one or more respective likelihood scores of one or more deal category groupings based, at least in part, on a probability that the one or more deal category groupings are associated with the at least one activity;

process and/or facilitate a processing of the one or more respective likelihood scores to select from among the one or more deal category groupings; and

determine the one or more deals, the one or more deal combinations, or a combination

thereof based, at least in part, on the selected one or more deal category groupings.

15. An apparatus of claim 14, wherein the apparatus is further caused to:

cause, at least in part, a grouping of the one or more deals into the one or more deal

combinations based, at least in part, on one or more shared deals associated with two or more of the selected one or more deal category groupings.

16. An apparatus according to any of claims 14 and 15, wherein the apparatus is further caused to:

cause, at least in part, a grouping of the one or more deals into one or more deal groupings based, at least in part, on the selected one or more deal category groupings; and determine the one or more deal combinations based, at least in part, on one or more shared deals associated with two or more deals groupings.

17. An apparatus of claim 16, wherein the apparatus is further caused to:

cause, at least in part, an association of the one or more respective likelihood scores of the selected one or more deal category groupings with respective ones of the one or more deal groupings,

wherein the one or more deal combinations are based, at least in part, on the respective

likelihood scores of the one or more deals groupings.

18. An apparatus according to any of claims 16 and 17, wherein the apparatus is further caused to:

cause, at least in part, a ranking of the one or more deal groupings based, at least in part, on the one more respective likelihood scores of one or more respective deal category groupings; and

combinations based, at least in part, on one or more shared deals between a deal grouping of a highest likelihood score and a deal grouping of a next highest likelihood score.

19. An apparatus according to any of claims 14-18, wherein the apparatus is further caused to:

cause, at least in part, an adjustment of the one or more respective likelihood scores based, at least in part, on information associated with a user,

wherein the at least one activity is associated with the user.

20. An apparatus according to any of claims 14-19, wherein the selection from among the one or more deal category groupings is based, at least in part, on the respective likelihood scores satisfying at least one threshold likelihood score.

21. An apparatus according to any of claims 13-20, wherein the apparatus is further caused to:

determine the one or more deals based, at least in part, on the one or more deals satisfying the one or more criteria for performing the at least one activity.

22. An apparatus of claim 21 , wherein the one or more criteria include a time criteria, a location criteria, a budget criteria, or a combination thereof.

23. An apparatus according to any of claims 13-22, wherein the apparatus is further caused to:

cause, at least in part, a validation of the one or more deal combinations based, at least in part, on agreement between one or more deal characteristics of respective deals of the one or more deal combinations, one or more criteria for performing the at least one activity, or a combination thereof,

24. An apparatus of claim 23, wherein the deal characteristics include temporal

characteristics, location characteristics, budget characteristics, deal grouping characteristics, or a combination thereof.

25. A method comprising:

receiving a request for deal information, the request specifying at least one activity, one or more criteria for performing the at least one activity, or a combination thereof;

processing and/or facilitating a processing of the at least one activity, the one or more criteria, or the combination thereof to cause, at least in part, a grouping of one or more deals into one or more deal combinations; and

causing, at least in part, a presentation of the one or more deal combinations in response to the request.

26. A method of claim 25, further comprising:

determining one or more respective likelihood scores of one or more deal category groupings based, at least in part, on a probability that the one or more deal category groupings are associated with the at least one activity;

processing and/or facilitating a processing of the one or more respective likelihood scores to select from among the one or more deal category groupings; and

determining the one or more deals, the one or more deal combinations, or a combination thereof based, at least in part, on the selected one or more deal category groupings.

27. A method of claim 26, further comprising:

causing, at least in part, a grouping of the one or more deals into the one or more deal

28. A method according to any of claims 26 and 27, further comprising:

causing, at least in part, a grouping of the one or more deals into one or more deal groupings based, at least in part, on the selected one or more deal category groupings; and determining the one or more deal combinations based, at least in part, on one or more shared deals associated with two or more deals groupings.

29. A method of claim 28, further comprising:

causing, at least in part, an association of the one or more respective likelihood scores of the selected one or more deal category groupings with respective ones of the one or more deal groupings,

likelihood scores of the one or more deals groupings.

30. A method according to any of claims 28 and 29, further comprising: causing, at least in part, a ranking of the one or more deal groupings based, at least in part, on the one more respective likelihood scores of one or more respective deal category groupings; and

31. A method according to any of claims 26-30, further comprising:

causing, at least in part, an adjustment of the one or more respective likelihood scores based, at least in part, on information associated with a user,

wherein the at least one activity is associated with the user.

32. A method according to any of claims 26-31 , wherein the selection from among the one or more deal category groupings is based, at least in part, on the respective likelihood scores satisfying at least one threshold likelihood score.

33. A method according to any of claims 25-32, further comprising:

determining the one or more deals based, at least in part, on the one or more deals satisfying the one or more criteria for performing the at least one activity.

34. A method of claim 33, wherein the one or more criteria include a time criteria, a location criteria, a budget criteria, or a combination thereof.

35. A method according to any of claims 25-34, further comprising:

causing, at least in part, a validation of the one or more deal combinations based, at least in part, on agreement between one or more deal characteristics of respective deals of the one or more deal combinations, one or more criteria for performing the at least one activity, or a combination thereof,

36. A method of claim 35, wherein the deal characteristics include temporal characteristics, location characteristics, budget characteristics, deal grouping characteristics, or a combination thereof.

37. An apparatus according to any of claims 13-24, wherein the apparatus is a mobile phone further comprising:

user interface circuitry and user interface software configured to facilitate user control of at least some functions of the mobile phone through use of a display and configured to respond to user input; and

a display and display circuitry configured to display at least a portion of a user interface of the mobile phone, the display and display circuitry configured to facilitate user control of at least some functions of the mobile phone.

38. A computer-readable storage medium carrying one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to perform at least a method according to any of claims 25-36.

39. An apparatus comprising means for performing a method according to any of claims 25-36.

40. An apparatus of claim 39, wherein the apparatus is a mobile phone further comprising: user interface circuitry and user interface software configured to facilitate user control of at least some functions of the mobile phone through use of a display and configured to respond to user input; and

41. A computer program product including one or more sequences of one or more instructions which, when executed by one or more processors, cause an apparatus to at least perform the steps of the method according to any of claims 25-36.

42. A method comprising facilitating access to at least one interface configured to allow access to at least one service, the at least one service configured to perform the method according to any of claims 25-36.

43. A method comprising facilitating a processing of and/or processing (1 ) data and/or (2) information and/or (3) at least one signal, the (1) data and/or (2) information and/or (3) at least one signal based, at least in part, on the method according to any of claims 25-36.

44. A method comprising facilitating creating and/or facilitating modifying (1) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on the method according to any of claims 25-36.

45. A method comprising creating and/or modifying (1 ) at least one device user interface element and/or (2) at least one device user interface functionality, the (1) at least one device user interface element and/or (2) at least one device user interface functionality based, at least in part, on the method according to any of claims 25-36.