WO2014178536A1 - Procede pour fournir un element de recommandation, et support d'enregistrement pour enregistrer un programme et appareil associes - Google Patents

Procede pour fournir un element de recommandation, et support d'enregistrement pour enregistrer un programme et appareil associes Download PDF

Info

Publication number
WO2014178536A1
WO2014178536A1 PCT/KR2014/002552 KR2014002552W WO2014178536A1 WO 2014178536 A1 WO2014178536 A1 WO 2014178536A1 KR 2014002552 W KR2014002552 W KR 2014002552W WO 2014178536 A1 WO2014178536 A1 WO 2014178536A1
Authority
WO
WIPO (PCT)
Prior art keywords
item
recommendation
log data
user
recommended
Prior art date
Application number
PCT/KR2014/002552
Other languages
English (en)
Korean (ko)
Inventor
이채현
박소라
정헌
Original Assignee
에스케이플래닛 주식회사
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 에스케이플래닛 주식회사 filed Critical 에스케이플래닛 주식회사
Publication of WO2014178536A1 publication Critical patent/WO2014178536A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0631—Item recommendations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
    • H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • H04N21/4667—Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections

Definitions

  • the present invention relates to a method for providing a recommendation item, and more particularly, to a method for providing a recommendation item for recommending another item related to an item served by a web site, a recording medium, and an apparatus for recording a program therefor.
  • An object of the present invention is to propose a method for providing a recommendation item that can be directly applied to its own service without additional development on a web site that provides various contents, products or services, and a recording medium and a device recording a program therefor.
  • an object of the present invention is to propose a method for providing a recommended item that can recommend a more suitable item by reflecting the feedback generated from the user in the recommendation result, a recording medium and a device recording a program therefor.
  • a service apparatus comprising: a communication unit for data transmission and reception, a user log data, a storage unit storing a recommendation result, and a website from a terminal connected to a website through a script inserted in the website; Collecting user log data related to the related data, using the recommendation algorithm based on the user log data, calculating recommendation results for one or more recommended items related to each source item serviced by the website, and receiving the result from the web server of the website. And a control unit for extracting a recommendation item list related to the requested source item from the recommendation result in response to the recommendation item list request and transmitting the same to the web server.
  • the controller may calculate a click rate for the recommendation item associated with each source item through the click log data and the view log data for the recommendation item.
  • the controller may exclude a recommendation item whose clickthrough rate is lower than a threshold value for a predetermined period of time from the recommendation result.
  • the controller may classify the user log data into a predetermined condition or arbitrarily into a plurality of groups, and calculate a recommendation result by using a different recommendation algorithm for each group.
  • the controller may calculate a click rate for each group through the click log data and the view log data of the recommended item, and calculate a recommendation result using a recommendation algorithm used for the group having the highest click rate.
  • the controller may obtain click log data for the recommended item through the access URL of the terminal.
  • the controller may extract user data including a predetermined parameter value from a visited URL (Uniform Resource Locator) included in the user log data and obtain the click log data for the recommended item.
  • a visited URL Uniform Resource Locator
  • the controller may obtain view log data for the recommendation item through the recommendation item list.
  • the controller may extract operation information related to the operation of the terminal from the item information displayed on the visit URL and the visit URL from the visit URL (Uniform Resource Locator) included in the user log data.
  • visit URL Uniform Resource Locator
  • the controller divides and stores the recommendation result for each source item, and hashes the string including a service identifier for identifying a website, an item identifier for the source item, and a recommendation item identifier for the recommendation item related to the source item.
  • the controller divides and stores the recommendation result for each source item, and hashes the string including a service identifier for identifying a website, an item identifier for the source item, and a recommendation item identifier for the recommendation item related to the source item.
  • the controller may transmit a list of recommended items related to the requested source item in a JavaScript Object Notation (JSON) format or an iframe format.
  • JSON JavaScript Object Notation
  • the user log data may include a domain of a web site, a visit URL (Uniform Resource Locator) of the terminal, a user identifier, and visit time information.
  • a visit URL Uniform Resource Locator
  • the user identifier is generated by a web browser cookie of the terminal, and may be generated by combining a random number and a generation time.
  • a method for providing a recommendation item wherein the service device collects user log data related to a web site from a terminal connected to the web site through a script inserted into the web site. Calculating a recommendation result for at least one recommendation item associated with each source item served by the website using a recommendation algorithm based on the user log data; and requesting the recommendation item list request received from the web server of the website by the service apparatus. And in response to extracting a recommendation item list related to the requested source item from the recommendation result and transmitting it to the web server.
  • the service device may further include calculating a click rate for the recommendation item associated with each source item through the click log data and the view log data for the recommendation item.
  • the service device may further include the step of excluding a recommendation item whose recommendation rate is lower than a threshold value for a predetermined period from the recommendation result.
  • the service device may classify the user log data into a predetermined condition or arbitrarily into a plurality of groups, and calculate the recommendation result by using a different recommendation algorithm for each group.
  • the service device calculates the clickthrough rate for each group through the click log data and view log data for the recommended item, and calculates the recommendation result by the recommendation algorithm used for the group having the highest click rate. can do.
  • the method may further include obtaining click log data for the recommended item through the access URL of the terminal.
  • the method may further include extracting, by the service apparatus, user data including a predetermined parameter value from a visit URL (Uniform Resource Locator) included in the user log data, as the click log data for the recommended item. .
  • a visit URL Uniform Resource Locator
  • the service device may further include acquiring view log data for the recommended item through the recommended item list when there is a recommendation item list request from the web server.
  • the user device may further include extracting operation information related to the operation of the terminal from the item information displayed on the visit URL and the visit URL from the visit URL (Uniform Resource Locator) included in the user log data.
  • visit URL Uniform Resource Locator
  • the service device stores and stores the recommended results for each source item, but hashes a string including a service identifier for identifying a website, an item identifier for the source item, and a recommended item identifier for the recommended item related to the source item.
  • the method may further include storing a value calculated by applying the (hash) function together with the recommended result.
  • FIG. 1 is a diagram schematically illustrating a system to which a recommended item providing service apparatus according to an embodiment of the present invention may be applied.
  • FIG. 2 is a diagram illustrating a configuration of a service device according to an embodiment of the present invention.
  • FIG. 3 is a diagram illustrating a method for providing a recommended item according to an embodiment of the present invention.
  • FIG. 4 is a diagram illustrating a user log data collection method according to an embodiment of the present invention.
  • FIG. 5 is a diagram illustrating a user log data collection method according to an embodiment of the present invention.
  • FIG. 6 is a diagram illustrating a method of providing a recommendation item list according to an embodiment of the present invention.
  • FIG. 7 is a diagram illustrating a list of recommended items provided in an iframe format according to an embodiment of the present invention.
  • FIG. 8 illustrates an example of displaying a recommendation item list provided in an iframe format on a web page according to an embodiment of the present invention.
  • FIG. 9 is a diagram illustrating a method of collecting click log data according to an embodiment of the present invention.
  • FIG. 10 is a diagram illustrating a click rate for each recommended item according to an embodiment of the present invention.
  • FIG. 11 is a diagram illustrating a recommendation rate for each algorithm according to an embodiment of the present invention.
  • the present invention includes all kinds of goods and services that can be distributed through wired and wireless networks, content such as digitally generated texts, sounds, images, videos, software such as computer programs or applications, and the like.
  • content such as digitally generated texts, sounds, images, videos, software such as computer programs or applications, and the like.
  • FIG. 1 is a diagram schematically illustrating a system to which a recommended item providing service apparatus according to an embodiment of the present invention may be applied.
  • a system to which a recommended item providing service apparatus according to an embodiment of the present invention may be applied includes a plurality of terminals 10, a web server 20, a service apparatus 30, and a network 40. Can be configured.
  • the terminal 10 transmits and receives information to and from the web server 20 and / or the service device 30 through the network 40, and refers to a device that can be used by a user who displays such information or receives information from the user.
  • the terminal 30 may access the web server 20 and receive various information about the item and a list of recommended items provided by the service device 30.
  • the recommended item refers to a list of one or more recommended items related to a specific item, and may be generated based on user log data collected by the service device 30 from the web server 20 and / or the terminal 10. .
  • the terminal 10 transmits the selection information on the item selected by the user to the web server 20, thereby using the selected item (for example, purchasing, storing a shopping cart, downloading, transferring to another terminal, etc.).
  • the terminal 10 may perform a function of transmitting user log data to the service device 30, which will be described later.
  • the terminal 10 may transmit / receive information with the web server 20 and / or the service device 30 through a web browser stored therein, but is not limited thereto.
  • the terminal described herein may be implemented in various forms.
  • a fixed terminal such as a smart TV (Smart TV), a set-top box, a desktop computer, etc. can be used, and any terminal that can send and receive messages with other users over a network,
  • the device is also applicable to the terminal of the present invention.
  • the web server 20 collectively refers to servers of a service provider that provides various services on the web, and is not limited to a specific server or a server that provides a specific service.
  • the web server 20 provides the above-described item and various information about the item to the terminal 10 connected to the web server 20, the terminal 10 (that is, the user)
  • the recommended item list for the selected item may be received from the service device 30 and provided to the terminal 10.
  • the web server 20 may perform a function of transmitting user log data to the service device 30, which will be described later.
  • the service device 30 refers to a device that performs a function for providing the web server 20 with a list of recommended items for various items provided by the web server 20.
  • the service device 30 collects and processes user log data from the terminal 10 and / or the web server 20 and calculates a list of recommended items for each item to the web server 20.
  • the user log data refers to a set of information indicating a history such as which terminal 10 (ie, user) performed what operation on which item on which web server and when.
  • the service device 30 collects view log data and / or click log data from the terminal 10 and / or the web server 20 or from the collected user log data.
  • the reprocessing may provide a list of recommended items in which feedback is reflected according to a user's visit or operation.
  • the view log data refers to a set of information indicating a history of providing a web page displaying a specific item to the terminal 10 by connecting the web server 20 of the terminal 10 (that is, the user). do.
  • the click log data is included in the recommendation item list by the terminal 10 (that is, the user) by clicking on the recommendation item list provided to the web server 20 by the service device 30.
  • a web page displaying a recommendation item clicked through a link means a set of information representing a history provided to the terminal 10.
  • the service device 30 may be implemented as a set of various devices to support the above-described operation.
  • a storage server capable of storing and managing log data (eg, user logs, view logs, click log data), a collection server that collects log data, a clustering server that converts or processes log data, It may be implemented including an API (Application Program Interface) server for calculating a list of recommended items and providing a list of recommended items to a web server, a feedback processing server for modifying a list of recommended items based on a feedback result, or selecting a recommendation algorithm.
  • each module performing a function corresponding to the above-described operation may be implemented in one service device 30.
  • the terminal 10, the web server 20, and the service device 30 transmit and receive various related information through the network 40.
  • the network 40 may use various types of networks.
  • 3G mobile communication, 4G mobile communication, WLAN (Wireless LAN), Wi-Fi, Wibro, Wimax, High Speed Downlink Packet Access (HSDPA), or Ethernet Wired communication methods such as Ethernet, xDSL (ADSL, VDSL), Hybrid Fiber Coaxial Cable (HFC), Fiber to The Curb (FTTC), and Fiber To The Home (FTTH) can be used. It may be.
  • it may include all other types of communication methods that are well known or developed in the future.
  • FIG. 2 is a diagram illustrating a configuration of a service device according to an embodiment of the present invention.
  • the configuration of the service device 30 illustrated in FIG. 2 illustrates functionally divided functional elements, and any one or more components may be implemented by being physically integrated with each other.
  • the service device 30 may include a communication unit 210, a control unit 220, and a storage unit 230.
  • the communication unit 210, the control unit 220, and the storage unit 230 constituting the service device 30 may be functionally connected to each other to perform a function according to the present invention.
  • the communication unit 210 may include one or more modules that enable wired / wireless communication with one or more terminals 10 and / or the web server 20.
  • the communication unit 210 may receive the user log data from the one or more terminals 10 and / or the web server 20.
  • the communication unit 210 may receive a recommendation item list request message from the web server 20, and transmit the recommendation item list to the web server 20 in response to the recommendation item list request message.
  • a redirect URL Uniform Resource Locator
  • the controller 220 is configured to perform overall control of the service device 30, and controls the flow of signals for performing the functions of the communication unit 210 and the storage unit 250.
  • the controller 220 may include an operating system (OS), an application program, and a process device for driving each component, for example, a central processing unit (CPU).
  • OS operating system
  • application program application program
  • process device for driving each component for example, a central processing unit (CPU).
  • CPU central processing unit
  • the controller 220 may include a data collector 221, a data processor 222, a recommendation calculator 223, a recommendation result provider 224, and a feedback processor 225. Can be.
  • the data collector 221 may perform a function of collecting the above-described user log data from the terminal 10 and / or the web server 20 and storing the user log data in the storage 230.
  • the data processor 222 extracts data necessary for calculation in order to calculate the recommended item from the user log data collected and stored by the data collector 221, and converts or processes the extracted data into a data format suitable for calculation.
  • the stored user log data may be stored in the storage 230.
  • a function of converting or processing the recommendation calculation result calculated and stored by the recommendation calculation unit 223 into a format for providing the web server 20 through the Internet to the database 230 may be stored in the database 230. Can be.
  • the recommendation calculator 223 calculates a recommendation item using various recommendation algorithms from the converted user log data processed by the data processor 222, and stores the recommendation calculation result of calculating the recommendation item in the storage 230. To perform the function.
  • the recommendation item list extraction unit 224 extracts the recommendation item list for the corresponding item from the recommendation result of the storage unit 230 and the web server 20. ) Can be sent. Also, remove items from the recommendation result (or recommendation item list), add new recommendation items to the recommendation result (or recommendation item list), add additional information to the recommendation result (or recommendation item list), etc. Postprocessing the recommendation result (or recommendation item list) may be performed.
  • the feedback processor 225 collects click log data and / or view log data, reprocesses the recommendation result (or recommendation item list) based on the collected click log data and / or view log data, or recommends the calculator 223. ) May determine a recommendation algorithm used for recommendation calculation.
  • the feedback processing unit 225 receives a connection request from the terminal 10 by clicking on a user's recommendation item on a web page provided by the web server 20, and uses the click log data as the click log data. It performs a function of storing in the storage unit 230, it may perform a function of transmitting a redirect (redirect) URL to the corresponding terminal 10, the connection request. In addition, the feedback processing unit 225 may perform a function of extracting data having a specific parameter or format from the user log data and storing the data in the storage unit 230 as click log data.
  • the feedback processor 225 may receive a recommendation item list request message from the web server 20, and store the same in the database 230 as view log data. .
  • the data collector 221, the data processor 222, the recommendation calculator 223, the recommendation result provider 224, and the feedback processor 225 are illustrated as respective blocks. It may be integrated into one device and implemented, or as described above, some or each of them may be implemented in physically different devices. In addition, a plurality of devices that perform the same function may be implemented in parallel.
  • the storage unit 230 is a means for storing data and programs necessary for the operation of the service device 30, and basically stores an operating program and an application program to be executed by the service device 30.
  • the storage unit 230 is the user log data collected by the data collection unit 241, the converted user log data processed by the data processing unit 222 and the recommendation results, recommendation calculation unit 223 The recommendation calculation result calculated by) and the view log data and the click log data collected by the feedback collector 245 may be stored.
  • Such a storage unit 250 may be implemented by various storage means.
  • the storage unit 250 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (for example, SD or XD).
  • Memory random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EPEROM), programmable read-only memory (PROM)
  • At least one type of storage medium may include a magnetic memory, a magnetic disk, and an optical disk.
  • the storage unit 250 may be inside or outside the controller 220 and may be connected to the controller 220 by various well-known means.
  • the user log data processed by the data processing unit 222 is referred to as 'converted user log data' separately from the 'user log data' collected by the data collection unit 221.
  • the result calculated by the recommendation calculation unit 223 is referred to as a 'recommended calculation result'
  • the recommendation calculation result processed by the data processing unit 222 is referred to as a 'recommended result'.
  • the recommendation result provided by the recommendation result providing unit 224 about the specific item requested by the web server 20 in the recommendation result is referred to as a 'recommended item list'. That is, the recommendation result encompasses a list of recommended items recommended for all items.
  • FIG. 3 is a diagram illustrating a method for providing a recommended item according to an embodiment of the present invention.
  • the service device 30 may collect the above-described user log data from the terminal 10 and / or the web server 20 (S301).
  • the service device 30 may collect user log data from the terminal 10 and / or the web server 20 synchronously (ie, real time collection) or asynchronously (eg, collecting at a specific period).
  • the user log data may be continuously collected from the terminal 10 and / or the web server 20 regardless of the collection method.
  • the service device 30 may extract data necessary for the recommendation calculation in order to calculate the recommendation item from the user log data collected in operation S301, and convert the extracted data into a data format suitable for the recommendation calculation (S303).
  • the service device 30 performs the data conversion step. It may not be performed, that is, step S303 may be omitted.
  • the service device 30 may calculate a recommendation item using various recommendation algorithms using the user log data converted in S303 and store the recommendation calculation result in operation S305.
  • the service device 30 may calculate a recommendation item for each recommendation algorithm for all items.
  • the user log data may be arbitrarily divided into a plurality of groups according to a specific criterion, and a recommendation item may be calculated using a different recommendation algorithm for each group.
  • the time point at which the service device 30 calculates the recommended item may or may not be the same as the time point at which the user log data is collected in step S301, and may be calculated with a certain period.
  • the service device 30 may convert the recommendation calculation result calculated in step S305 into a suitable data format in order to provide the web server 20 through the Internet (S307). As described above, if the service device 30 does not perform the data conversion step in step S303, step S307 may also be omitted.
  • the service device 30 may perform post-processing on the calculated recommendation result (or recommendation item list), and then provide the recommendation item list to the corresponding web server 20 collecting user log data (S309).
  • the service device 30 may provide the recommendation item list to the web server 20 at regular intervals, or the service device 30 may request a recommendation item list for a specific item from the web server 20 to the corresponding item.
  • the recommended item list may be transmitted to the web server 20.
  • the service device 30 may collect the user's feedback and reflect it in the recommendation (S311). That is, the service device 30 reprocesses the recommendation result (or recommendation item list) based on the collected click log data and / or view log data (branch to step S309), or the recommendation calculation unit 223 calculates the recommendation.
  • a recommendation algorithm to be used can be determined (branch to step S305) (S311).
  • the service device 30 may collect the above-described user log data from the terminal 10 and / or the web server 20 (S301).
  • the user log data refers to a set of information indicating which user performed what action on which item on which web server and when.
  • the user log data includes information for identifying a browser mounted on the terminal 10 used by the user, information for limiting exposure to a specific user for other items, and a member ID of the user managed by the web server 20. (ID: Identifier) information and the like.
  • Table 1 illustrates information that may be included in user log data according to the present invention.
  • the service device 30 may use the following method for collecting such user log data.
  • the service device 30 may access the web server 20 to extract and obtain user log data, or may receive and obtain user log data transmitted from the web server 20. It demonstrates with reference.
  • FIG. 4 is a diagram illustrating a user log data collection method according to an embodiment of the present invention.
  • the web server 20 access path information of the web page including the user log data to inform the service device 30 that the specific operation has been performed.
  • a connection request message including a may be transmitted to the service device 30 (S401).
  • the web server 20 may transmit a connection request message to the service device 30 using the POST HTTP protocol.
  • the service device 30 When the service device 30 receives the access request message from the web server 20, the service device 30 accesses the web server 20 based on the access path information of the web page included in the access request message and logs the user included in the web page. The data is extracted and obtained (S403).
  • the service device 30 may extract user log data from the web server 20 using the GET HTTP protocol.
  • the service device 30 stores the obtained user log data (S405).
  • the user log data on the operation of the user terminal 10 connected to the web server 20 from the web server 20 is transferred to the service device 30 through the TCP / IP protocol. By transmitting, the user log data may be obtained from the service device 30.
  • the service device 30 may insert a script into a web site serviced by the web server 20 and obtain user log data from the user terminal 10 through the inserted script. A description with reference to FIG. 5 below.
  • FIG. 5 is a diagram illustrating a user log data collection method according to an embodiment of the present invention.
  • the service device 30 may insert a script into a web site provided by the web server 20 (S501).
  • the terminal 10 accesses the web server 20 (S503) and visits a web page provided by the web server 20, the terminal 10 executes a script inserted in the web page (S505).
  • the log data of the user may be automatically transmitted to the service device 30 by the script (S507).
  • the terminal 10 provides information on URLs, visit times, and values of parameters included in the script. To the device 30.
  • UID User IDentifier
  • the user identifier means a value for distinguishing a user.
  • the terminal 10 executes the script, the terminal 10 first finds whether a user identifier value is stored in a cookie of a web browser, and if the user identifier is stored, the value is a service device. Transfer to 30. On the other hand, if the user identifier is not stored in the cookie of the web browser, a random numeric value and a creation time are combined (for example, 33619442.1366005959274) to generate information that can identify the user, and transmit the generated information to the service device 30. .
  • Visit URL information means URL information on the web page of the web server 20 to which the access.
  • the reference address (referrer) information means the URL information about the previously visited web page when visiting the web page of the web server 20 through a link.
  • the access time information means time information that the terminal 10 visits a web page of the web server 20.
  • the user agent information of the web browser refers to information for distinguishing the web browser used by the terminal 10 when accessing the web server 20. For example, the information for identifying whether the web browser used in the terminal 10 is a web browser for a mobile device or a web browser for a desktop may correspond thereto. Such information may be collected by a web browser mounted on the terminal 10 to transmit the entire information synchronously or asynchronously to the service device 30.
  • the meta information means other additional information to be considered when the service device 30 calculates a recommendation item.
  • the meta information may identify a user more accurately, such as member information, on a web site operated by a web server. Information or information on whether an item requires adult certification may be applicable.
  • Such meta information is transmitted to the service device 30 by the terminal 10 when the script embedded in the web page of the web server 20 has a format for requesting meta information. .
  • the terminal 10 transmits values (value1, value2) for each parameter (key, key2) to the service device 30. To be sent).
  • the service device 30 that receives the user log data from the terminal 10 in the manner described above stores the obtained user log data (S509).
  • Table 2 illustrates user log data collected by the service device 30.
  • the service device 30 (particularly, the data processing unit 222) extracts data necessary for the recommendation calculation in order to calculate the recommendation item from the user log data collected in step S301, and recommends the extracted data for the calculation.
  • the data format may be transformed and stored (S303).
  • the service device 30 extracts an item identifier (ITEM_ID) and an action identifier (ACTION_ID) from the visited URL information by using a regular expression predefined for each service identifier (SERVICE_ID).
  • ⁇ is a variable indicating that '/' exists to distinguish each path when a plurality of paths are included in the regular expression
  • $ is a variable indicating that the regular expression is finished.
  • the service device 30 uses the corresponding member ID as the user identifier (USER_ID), If not, the terminal 10 uses the user identifier USER_IDENTIFIER generated based on the web browser cookie as the user identifier USER_ID.
  • the service device 30 converts the user identifier USER_ID and the item identifier ITEM_ID extracted or acquired through the above-described method into a predefined numeric identifier, and the numeric identifier predefined in the extracted operation identifier ACTION_ID. To give.
  • the service device 30 may convert each user identifier, an operation identifier, and an item identifier into a predetermined numeric identifier, such as a one-to-one mapping relationship between a domain and a service identifier, or optionally convert to a numeric identifier having a continuous integer value ( Or grant).
  • Table 3 illustrates the converted user identifier table.
  • the original identifier 'chaehyun' indicates a case where the user member information value of the web server 20 is delivered and used as the user identifier
  • '44209103.136609' or '68709103.015529' is based on the web browser cookie of the terminal 10. This is the case that the generated value is used as a user identifier.
  • Table 4 illustrates the converted item identifier table.
  • Table 5 illustrates the translated action identifier table.
  • the recommendation algorithm x (RECOMMEND_VISIT_ALGORITHM_x) represents an operation in which the user terminal 10 accesses the web server 20 having the corresponding service identifier through a recommendation item list calculation result calculated using the recommendation algorithm x. .
  • Table 6 illustrates the converted user log data.
  • the service device 30 may assign different version information to distinguish the converted user log data according to the items of the information included in the converted user log data. For example, in the case of the converted user log data having version 0, as shown in the example of Table 6, the converted user identifier, the converted item identifier, the service identifier, the operation identifier, the time item, but the conversion having the version 1 In the case of the user log data, information items other than those included or not included in version 0 may be added.
  • the service device 30 may calculate the recommendation item using various recommendation algorithms using the user log data converted in S303, and store the recommendation calculation result (S305).
  • the service device 30 may calculate a recommendation item by applying various recommendation algorithms so as to apply a recommendation algorithm suitable for the nature of the service provided by the web server 20 providing the recommendation result.
  • a recommendation algorithm suitable for the nature of the service provided by the web server 20 providing the recommendation result.
  • Each group may calculate recommendation items according to different recommendation algorithms. For example, the converted user log data having an odd user identifier (USER_ID) and the converted user log data having an even number may be distinguished, and a recommended item may be calculated using an A recommendation algorithm and a B recommendation algorithm, respectively.
  • the service device 30 calculates similarity with all items except for the corresponding items for all items belonging to the converted user log data included in the predetermined range (ie, all or groups). For example, if a total of 100 items belong to the converted user log data within a predetermined range, the similarity between the first item and 99 items other than the corresponding item is calculated, and the 99 items other than the second item and the corresponding item are calculated. The similarity with other items is calculated for all items by calculating the similarity between them.
  • the service device 30 may use various recommendation algorithms to calculate the similarity between two items. For example, jacquard similarity, log likelihood similarity, Pearson correlation, or the like may be used. These similarity calculation methods are already known methods and will not be described in detail below. Hereinafter, description will be made on the assumption that jacquard similarity is used as a recommendation algorithm for convenience of description, and jacquard similarity is defined as in Equation 1 below.
  • the jacquard similarity between two items is determined by the number of users who visited both items (the number of users who accessed both web pages displaying both items) and the number of unions of users who visited both items (the two items).
  • the number of users who have access to any one or more of the displayed web pages is calculated by dividing the number of users who have accessed both web pages displaying two items), and as a result, the more users who visit both items, the greater the similarity between the two items. .
  • the number of users who access the web page displaying item A is 20
  • the number of users who access the web page displaying item B is 10
  • the service device 30 calculates all similarities for all items belonging to the user log data converted within a predetermined range (all or in a group) using the recommendation algorithm, and then recommends n items in the order of similarity for each item. Calculate it as an item.
  • N items may be calculated as recommended items in order of similarity for each item among the items.
  • the method of calculating the recommendation item using the jacquard similarity described above is just one example, and as described above, the service device 30 may calculate the recommendation item for each item using various recommendation algorithms. In addition, even when the recommendation scores of the recommended items for each item are calculated using different recommendation algorithms, the recommendation scores may all be set at the same level (eg, between 0 and 1). As described above, the result of recommendation calculation according to each recommendation algorithm is shown in Table 7 below.
  • Table 7 illustrates the recommendation calculation results calculated according to each recommendation algorithm.
  • the SCORE value indicates a value for calculating the similarity between the item and the recommended item according to the recommendation algorithm
  • the method METHOD indicates an identification number for the recommendation algorithm used for the similarity calculation.
  • the service device 30 may convert the recommendation calculation result calculated in step S305 into a suitable data format in order to provide the web server 20 (S307).
  • the service device 30 changes the identifier of the item converted from the recommendation calculation result to the original identifier, and adds and stores the service identifier and the calculated date.
  • Table 8 illustrates the converted format of the recommendation calculation result.
  • the service device 30 may convert and store the recommendation calculation result into a data format suitable for finally providing the web server 20 through the Internet.
  • the service device 30 may be stored in the JSON (JavaScript Object Notation) format as shown in Table 9 below.
  • JSON JavaScript Object Notation
  • the JSON format is just one example, and the service device 30 may store the data in various data formats such as Extensible Markup Language (XML) format or YAML Ain't Markup Language (YAML) format. have.
  • XML Extensible Markup Language
  • YAML YAML Ain't Markup Language
  • Table 9 illustrates the recommended result format that is finally converted and stored.
  • the hash value means a value calculated so as not to store the recommended item list for the corresponding item when the recommended item list recommended for the specific item is the same, and the service identifier (SERVICE_ID) and the item.
  • the identifier (ITEM_ID) and the recommended item identifier (RECOMMENDED_ITEM_ID) are combined into one string, and then calculated by applying a hash function to the combined string.
  • the recommendation score for the recommendation item is not included as a variable for calculating the hash value, when the recommendation item list is calculated the next day, even if the recommendation score of the recommendation item is changed, the number of recommended items is changed, If the order does not change, the hash value does not change.
  • the count value indicates the number of recommended items and how many items are recommended for a particular item.
  • the JSON value includes information on the number of recommended items corresponding to the count value.
  • the JSON value may include a recommendation item identifier, a recommendation score, and recommendation algorithm information.
  • the service device 30 (particularly, the recommendation result providing unit 224) performs post-processing on the calculated recommendation result (or recommendation item list), and then recommends to the corresponding web server 20 that has collected user log data.
  • An item list may be provided (S309).
  • FIG. 6 is a diagram illustrating a method of providing a recommendation item list according to an embodiment of the present invention.
  • the service device 30 may perform post-processing on the converted stored recommendation result (or recommendation item list) (S601).
  • Post-processing of the recommendation result refers to an operation of adding, deleting, or changing a recommendation item from the recommendation result (or recommendation item list) or adding, deleting, or changing information items included in the recommendation item list. .
  • This post-processing process may be automatically performed in the service device 30, or may be performed in the service device 30 by a request from the web server 20.
  • the service device 30 may remove the prohibited item from the recommendation result (or the recommended item list). For example, when the administrator of the web server 20 prohibits the recommendation of item B for item A, item B may be removed from the recommended item list for item A. FIG. In addition, in the case of an item that should not be recommended for any item, such as when a certain product is out of stock or when a particular store is no longer in operation, the item may be removed from the list of all recommended items (ie, the recommendation result).
  • the service device 30 When removing the recommended prohibited item from the recommendation result (or recommendation item list), the service device 30 arbitrarily deletes an item to be deleted from the previously generated recommendation result (or recommendation item list), or The recommendation score can be changed to a lower value or a variable value can be adjusted so that a lower value is calculated to remove the prohibited item from the recommendation result (or recommendation item list).
  • the service device 30 may add any item that does not belong to the recommendation result (or the recommendation item list) as the recommendation item. For example, if the administrator of the web server 20 does not like the result of the calculated recommendation item list, or if the recommendation item list for the specific item is not generated, the service device 30 selects the specific item. It may be included in the recommendation result (or recommendation item list) as a recommendation item. Even in this case, the service device 30 arbitrarily adds an item to be added from a previously generated recommendation result (or a recommendation item list), or creates a recommendation item list composed of specific items or recommends an item to be added. You can adjust the value of the variable to change the score to a higher value or to calculate a higher value.
  • the information item constituting the recommendation result may include only the recommendation item identifier, recommendation score, and recommendation algorithm information as shown in the example of Table 9 above, but the service device 30 may also recommend the recommendation result (or It is also possible to add a new information item constituting a list of recommended items.
  • the service device 30 may include a recommended item name, a URL of a thumbnail of the recommended item, price information of the recommended item, and the like in the recommended item list.
  • the web server 20 transmits a message to the service device 30 for requesting a list of recommended items regarding items displayed on the web page to which the terminal 10 accesses (S603).
  • the recommended item list request message includes a service identifier for the requesting web server 20, an item identifier for the requested item, and may further include version information, meta information, and the like.
  • the service device 30 Upon receiving the recommendation item list request message from the web server 20, the service device 30 extracts a recommendation item list for the requested item (S605), and transmits the extracted recommendation item list to the web server 20 (S607). .
  • the service device 30 may transmit the recommendation item list in the format of the recommendation item list generated in the web server 20 (ie, JSON format), or may transmit the recommendation item list in the iframe format.
  • JSON format the format of the recommendation item list generated in the web server 20
  • a list of recommended items should be provided on the web page, whereas in the case of an iframe, the web server 20 does not need additional processing.
  • the web server 20 is a service device in a format such as "http://api.recopick.com/VERSION/recommend/SERVICE_ID/ITEM_ID?OPTIONS".
  • the list of recommended items may be requested at 30.
  • the recommendation item list request message may include a service identifier, an item identifier, version information, and other meta information.
  • the version of the recommended item list is 2, the service identifier is 1, the identifier of the requesting item is 11057, and it indicates a case of additional request for meta information.
  • An example of the recommended item list provided by the service device 30 to the web server 20 in response to the request is shown in Table 10 below.
  • Table 10 illustrates a list of recommended items provided in JSON format.
  • the recommendation item list may include a recommendation item identifier (“id”), a recommendation score (“score”), and recommendation algorithm information (“method”).
  • Table 10 illustrates a case in which the service device 30 includes additional meta information in the recommended item list when additional meta information is additionally requested, and image information (“image”) of the recommended item is included as additional meta information. ), And recommended item name information ("title").
  • a service identifier, an item identifier, a frame direction (horizontal or vertical direction), a frame size, version information along with the number of recommended items, and the like may be included.
  • the version of the requested recommendation item list is 2
  • the service identifier is 6
  • the identifier of the requesting item is 59
  • the horizontal direction in the direction of the frame and the number of recommended items is 4.
  • the version of the requested recommendation item list is 2
  • the service identifier is 6
  • the identifier of the requesting item is 59
  • the direction perpendicular to the frame direction and the number of recommended items is 2.
  • FIG. 8 illustrates a list of recommended items provided by the service device 30 to the web server 20 in response to the request.
  • FIG. 7 is a diagram illustrating a list of recommended items provided in an iframe format according to an embodiment of the present invention.
  • the recommended items displayed in the horizontal direction are four recommended items provided by the service device 30.
  • the number of recommended items provided by the service device 30 is two and vertical in response thereto. An example of the recommended item list displayed in the direction is illustrated.
  • FIG. 8 illustrates an example of displaying a recommendation item list provided in an iframe format on a web page according to an embodiment of the present invention.
  • the recommendation item list in the iframe format provided by the service device 30 may be displayed on the web page of the web server 20 in the form provided by the service device 30 as shown in FIG. 7. Can be.
  • the service device 30 provides the list of recommended items to the web server 20 in the form of a banner, the web server 20 may not perform an additional data processing procedure.
  • FIG. 6 illustrates a method of transmitting a recommendation item list at the request of the web server 30 after the service device 30 performs post-processing
  • the service device 30 from the web server 20.
  • the post-processed recommendation item list may be transmitted to the web server 20 after the post-processing is performed on the requested recommendation item list. That is, the step of performing post-processing may be performed between steps S605 and S607.
  • the service device 30 may collect the user's feedback and reflect it in the recommendation (S311).
  • the feedback of the user may be calculated according to the click rate of the user, and the recommended view log data and the user's recommended click log data may be collected to calculate the click rate.
  • FIG. 9 is a diagram illustrating a method of collecting click log data according to an embodiment of the present invention.
  • the terminal 10 when the terminal 10 selects and inputs a specific recommendation item included in the recommendation item list displayed on the web page of the web server 20 (for example, click or touch input) (S901).
  • the terminal 10 requests access to the service device 30 through the link URL of the recommended item. That is, the recommendation item may have URL information for moving to the service device 30 instead of URL information for moving to a web page displaying the corresponding recommendation item.
  • the link URL of each recommendation item includes the version information of the recommendation item list to which the recommendation item belongs, the service identifier, the source item (the item to which the recommendation item is displayed), the target item (the recommendation item selected and clicked by the user). ) Identifier, algorithm information for calculating the selected recommendation item, and the like.
  • the service device 30 stores click log data for the terminal 10 attempting to access the service device 30 (S905).
  • the recommendation item link URL may include version information of the recommendation item list to which the corresponding recommendation item belongs, a service identifier, a source item identifier, a target item identifier, algorithm information for calculating the selected recommendation item, and the like. ) Can determine which recommendation item is clicked by the user from which item on which web server 20 through the URL that the terminal 10 attempts to access, and can confirm that the recommendation item is calculated by which recommendation algorithm. have.
  • the service device 30 transmits the redirect URL to the terminal 10 so that the terminal 10 can reconnect to the web server 20 (S907).
  • the terminal 10 accesses the web server 20 through the received redirect URL (S909).
  • the service device 30 Since the user's click information is transmitted to the service device 30 whenever the user clicks on the recommendation item by using the method as shown in the example of FIG. 9, the service device 30 stores the user's click log data on the recommendation item in real time. Can be stored.
  • a predetermined specific parameter is added to a variable constituting a link of the recommendation item, and if the predetermined specific parameter described above exists in the visit URL information of the user in the user log data collected in step S301, it is added to the recommendation.
  • recopick METHOD may be added to the link variable of the recommendation item, and if recopick exists in the user's visit URL in the user log data, this may be determined as a click by recommendation.
  • the source item identifier may be checked using the item identifier (ITEM_ID).
  • the reference address information has the URL of the service device 30, it may not be determined as a recommended click because it is already collected as click log data in the first method.
  • the service device 30 described above may collect click log data using the first method and / or the second method, and store the collected click log data.
  • Table 11 illustrates the format of the click log data.
  • the click log data may include a log type (click or view), version information on the recommendation item list, service identifier, click item information, source item information, recommendation algorithm, click time information, and the like.
  • the service device 30 may obtain and store the view log data through the recommendation item list provided whenever the web server 20 requests the recommendation item list.
  • Table 12 illustrates the format of view log data.
  • the click log data may include a log type (click or view), version information for the recommendation item list, service identifier, click item information, source item information, recommendation list, recommendation algorithm, click time information, and the like. Can be.
  • the service device 30 that collects the click log data and the view log data may calculate the click rate using the click log data and the view log data.
  • the service device 30 may add up the total number of views exposed to a specific item by date, and also add up the number of times a user clicks, and then calculate a click rate between each source item and each recommendation item.
  • Table 13 illustrates the clickthrough rate.
  • the service device 30 may calculate a click rate between each source item and each recommendation item, and then designate the item as a prohibited item if the click rate is below a certain threshold (or below) for a predetermined period of time. That is, if the recommended item B for item A is less than 1% for 7 days, item B may be removed from the recommended item list for item A. In addition, the service device 30 may designate a prohibition item when the number of click counts between each source item and each recommendation item is less than (or less than) a certain threshold for a predetermined period.
  • the service device 30 When removing the recommended prohibited item from the recommendation result (or recommendation item list), the service device 30 arbitrarily deletes an item to be deleted from the previously generated recommendation result (or recommendation item list), or The recommendation score can be changed to a lower value or a variable value can be adjusted so that a lower value is calculated to remove the prohibited item from the recommendation result (or recommendation item list).
  • This feedback process may be automatically performed in the service device 30.
  • the service device 30 provides the web server 20 with the click rate information of the corresponding item and the click rate information or the number of clicks between the recommended item and the recommended item for each item serviced by the web server 20, and the web server 20.
  • the feedback processing may be performed in the service device 30 according to a request from the service device 30.
  • FIG. 10 is a diagram illustrating a click rate for each recommended item according to an embodiment of the present invention.
  • the service device 30 may provide the web server 20 with information about the source item 101 and schedule information about the source item 101 such as the name of the source item 101 and average click-through rate information for a predetermined period of time.
  • the overall referral clickthrough rate 102 may be provided for a period of time.
  • the recommendation item list 103 for the source item 101, a name, an algorithm, a recommendation score, a click rate between the source items, an operation input button, and the like may be provided for each recommendation item.
  • the administrator of the web server 20 may check the clickthrough rate of the source item 101 along with the clickthrough rate of the source item 101 for each recommendation item by date. In the case of FIG.
  • the click rate of the recommendation item 104 displayed at the bottom stays at about 0% for a certain period.
  • the web server 20 administrator selects the prohibition of recommendation button for the recommendation item having a low clickthrough rate
  • the web server 20 transmits it to the service device 30 so that the service device 30 transmits the recommendation item to the source item.
  • Recommendation 101 may be prohibited.
  • the web server 20 administrator selects the first exposure button separately, the web server 20 transmits it to the service device 30, so that the service device 30 recommends a score (score) of the selected recommendation item.
  • the recommendation item list may be generated to display the corresponding recommendation item at the highest priority (for example, at the top or the leftmost side).
  • the service device 30 may automatically select the most suitable algorithm for each web server 20 in consideration of click rate information or click count information.
  • the service device 30 In order to apply the algorithm having the highest efficiency (that is, the highest click rate or the highest number of clicks) for each service provided by the web server 20, the service device 30 generates a plurality of user log data in a certain condition or arbitrarily. It is divided into groups and provides a list of recommended items calculated by different algorithms for each group. For example, the service device 30 arbitrarily divides the user log data into groups A and B (for example, group A when the odd user identifier is odd, group B when the even number is odd), and recommends algorithm 1 to the group A. , The group B may calculate a recommendation using algorithm 2, and provide the web server 20 with a list of recommended items.
  • groups A and B for example, group A when the odd user identifier is odd, group B when the even number is odd
  • the group B may calculate a recommendation using algorithm 2, and provide the web server 20 with a list of recommended items.
  • the service device 20 is a user connected to the web server 20 through the mobile terminal and the group connected to the web server 20 through the fixed terminal using the user agent information of the web browser in the user log data.
  • the web server 20 may provide a list of recommended items by dividing log data and calculating recommendations through different algorithms.
  • the service device 30 may calculate the recommendation by selecting the algorithm having the highest click rate or the algorithm having the highest number of clicks as the algorithm of the corresponding service by separately calculating the click rate for each group.
  • the feedback process may also be automatically performed by the service device 30, and the service device 30 may provide the web server 20 with click rate information or click count information for each user group (that is, for each algorithm). 20, and a feedback process may be performed in the service device 30 by a request from the web server 20.
  • FIG. 11 is a diagram illustrating a recommendation rate for each algorithm according to an embodiment of the present invention.
  • the service device 30 recommends an algorithm for the web server 20 that provides the service. Can be selected.
  • Embodiments according to the present invention may be implemented by various means, for example, hardware, firmware, software, or a combination thereof.
  • an embodiment of the present invention may include one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), FPGAs ( field programmable gate arrays), processors, controllers, microcontrollers, microprocessors, and the like.
  • ASICs application specific integrated circuits
  • DSPs digital signal processors
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGAs field programmable gate arrays
  • processors controllers, microcontrollers, microprocessors, and the like.
  • an embodiment of the present invention is implemented in the form of a module, a procedure, a function, etc. for performing the above-described functions or operations, so that the recording medium can be read by various computer means.
  • the recording medium may include a program command, a data file, a data structure, etc. alone or in combination.
  • Program instructions recorded on the recording medium may be those specially designed and constructed for the present invention, or they may be of the kind well-known and available to those having skill in the computer software arts.
  • the recording medium may be magnetic media such as hard disks, floppy disks and magnetic tapes, optical disks such as Compact Disk Read Only Memory (CD-ROM), digital video disks (DVD), Magnetic-Optical Media, such as floppy disks, and hardware devices specially configured to store and execute program instructions, such as ROM, random access memory (RAM), flash memory, and the like. do.
  • program instructions may include high-level language code that can be executed by a computer using an interpreter as well as machine code such as produced by a compiler.
  • Such hardware devices may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.
  • the device or the terminal according to the present invention may be driven by a command that causes one or more processors to perform the functions and processes described above.
  • such instructions may include interpreted instructions, such as script instructions such as JavaScript or ECMAScript instructions, or executable instructions or other instructions stored on a computer readable medium.
  • the device according to the present invention may be implemented in a distributed manner over a network, such as a server farm, or may be implemented in a single computer device.
  • a computer program (also known as a program, software, software application, script or code) mounted on an apparatus according to the invention and executing a method according to the invention comprises a compiled or interpreted language or a priori or procedural language. It can be written in any form of programming language, and can be deployed in any form, including stand-alone programs or modules, components, subroutines, or other units suitable for use in a computer environment. Computer programs do not necessarily correspond to files in the file system.
  • a program may be in a single file provided to the requested program, in multiple interactive files (eg, a file that stores one or more modules, subprograms, or parts of code), or part of a file that holds other programs or data. (Eg, one or more scripts stored in a markup language document).
  • the computer program may be deployed to run on a single computer or on multiple computers located at one site or distributed across multiple sites and interconnected by a communication network.
  • the present invention recommends other items related to items served by a web site. Accordingly, it can be applied directly to its own service without additional development on the web site that provides various contents, products or services, and feedback is reflected in the recommendation results based on the click / view log data generated from the user. By providing more suitable items can be recommended. That is, the method of providing the recommendation result of the present invention can be applied to various wired / wireless communication systems. This has industrial applicability because it is not only sufficient marketable or business possibility, but also practically evident.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • General Business, Economics & Management (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Physics & Mathematics (AREA)
  • Economics (AREA)
  • General Physics & Mathematics (AREA)
  • Development Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Information Transfer Between Computers (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)

Abstract

La présente invention porte sur un procédé pour fournir un élément de recommandation, un support d'enregistrement pour enregistrer un programme correspondant, et un appareil correspondant. En détail, des données de journal d'utilisateur concernant un site web sont collectées auprès d'un terminal qui a accédé à un site web par l'intermédiaire d'un script introduit dans le site web, un résultat de recommandation pour un ou plusieurs éléments de recommandation en rapport avec chaque élément source fourni par le site web est calculé à l'aide d'un algorithme de recommandation sur la base des données de journal d'utilisateur, et une liste d'éléments de recommandation en rapport avec un élément source demandé à partir du résultat de recommandation est extraite en réponse à une requête de liste d'éléments de recommandation reçue en provenance d'un serveur web du site web, et est transmise au serveur web.
PCT/KR2014/002552 2013-05-03 2014-03-26 Procede pour fournir un element de recommandation, et support d'enregistrement pour enregistrer un programme et appareil associes WO2014178536A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
KR10-2013-0049968 2013-05-03
KR1020130049968A KR101678659B1 (ko) 2013-05-03 2013-05-03 추천 아이템 제공 방법, 이를 위한 프로그램을 기록한 기록 매체 및 장치

Publications (1)

Publication Number Publication Date
WO2014178536A1 true WO2014178536A1 (fr) 2014-11-06

Family

ID=51843622

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/KR2014/002552 WO2014178536A1 (fr) 2013-05-03 2014-03-26 Procede pour fournir un element de recommandation, et support d'enregistrement pour enregistrer un programme et appareil associes

Country Status (2)

Country Link
KR (1) KR101678659B1 (fr)
WO (1) WO2014178536A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019226935A1 (fr) * 2018-05-25 2019-11-28 Target Brands, Inc. Tableau de bord de surveillance de recommandation en temps réel
US11132733B2 (en) 2018-05-25 2021-09-28 Target Brands, Inc. Personalized recommendations for unidentified users based on web browsing context

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2018128254A1 (fr) * 2017-01-04 2018-07-12 주식회사 다이퀘스트 Procédé et dispositif de recommandation de groupe d'utilisateurs pour un nouvel utilisateur

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050076093A1 (en) * 2003-06-04 2005-04-07 Stefan Michelitsch Content recommendation device with user feedback
KR101051804B1 (ko) * 2010-12-16 2011-07-25 전자부품연구원 웹 기반의 미디어 콘텐츠를 위한 선호도 정보 관리 시스템
KR20120052024A (ko) * 2010-11-15 2012-05-23 주식회사 케이티 사용자 피드백을 이용한 아이피티브이 컨텐츠 추천 시스템 및 그 방법
KR20120075515A (ko) * 2010-11-19 2012-07-09 주식회사 케이티 사용자 선호 콘텐츠 추천 시스템 및 방법
US20120191844A1 (en) * 2010-12-18 2012-07-26 Boyns Mark R Methods and systems for managing device specific content

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050076093A1 (en) * 2003-06-04 2005-04-07 Stefan Michelitsch Content recommendation device with user feedback
KR20120052024A (ko) * 2010-11-15 2012-05-23 주식회사 케이티 사용자 피드백을 이용한 아이피티브이 컨텐츠 추천 시스템 및 그 방법
KR20120075515A (ko) * 2010-11-19 2012-07-09 주식회사 케이티 사용자 선호 콘텐츠 추천 시스템 및 방법
KR101051804B1 (ko) * 2010-12-16 2011-07-25 전자부품연구원 웹 기반의 미디어 콘텐츠를 위한 선호도 정보 관리 시스템
US20120191844A1 (en) * 2010-12-18 2012-07-26 Boyns Mark R Methods and systems for managing device specific content

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2019226935A1 (fr) * 2018-05-25 2019-11-28 Target Brands, Inc. Tableau de bord de surveillance de recommandation en temps réel
US11074635B2 (en) 2018-05-25 2021-07-27 Target Brands, Inc. Real-time recommendation monitoring dashboard
US11132733B2 (en) 2018-05-25 2021-09-28 Target Brands, Inc. Personalized recommendations for unidentified users based on web browsing context
US11580586B2 (en) 2018-05-25 2023-02-14 Target Brands, Inc. Real-time recommendation monitoring dashboard

Also Published As

Publication number Publication date
KR20140131088A (ko) 2014-11-12
KR101678659B1 (ko) 2016-12-06

Similar Documents

Publication Publication Date Title
WO2020138928A1 (fr) Procédé de traitement d'informations, appareil, dispositif électrique et support d'informations lisible par ordinateur
US8862777B2 (en) Systems, apparatus, and methods for mobile device detection
WO2012091360A2 (fr) Procédé et système de fourniture de contenu personnalisé par l'utilisateur
WO2016032287A1 (fr) Procédé permettant la fourniture de fonctions supplémentaires sur la base d'informations
KR101978301B1 (ko) 추천 아이템 제공을 위한 장치
EP3314482A1 (fr) Procédé et dispositif de marquage de liens inclus dans une capture d'écran de page web
WO2016003219A1 (fr) Dispositif électronique et procédé de fourniture de contenu sur un dispositif électronique
WO2011007935A1 (fr) Système et procédé de fourniture d'un service consolidé destiné à une page d'accueil
WO2016035970A1 (fr) Systeme publicitaire utilisant une recherche de publicite
WO2020022819A1 (fr) Communication par le biais d'un utilisateur simulé
WO2021177787A1 (fr) Procédé et système de fourniture de contenu via une architecture de base de données efficiente pour une gestion de temps individualisée
WO2014178536A1 (fr) Procede pour fournir un element de recommandation, et support d'enregistrement pour enregistrer un programme et appareil associes
US9398105B2 (en) Method for providing a third party service associated with a network-accessible site using a single scripting approach
WO2016171361A1 (fr) Système et procédé de prestation d'avantages basés sur un service mo
WO2017082551A1 (fr) Système de distribution d'informations en temps réel basée sur une chaîne de chiffres utilisant un terminal intelligent et procédé de distribution d'informations
WO2013051844A1 (fr) Système publicitaire plurilingue interactif et procédé de commande associé
WO2021033834A1 (fr) Système de traitement et de fourniture d'informations personnalisées sur la base de données de questionnaire, et procédé associé
WO2016117818A1 (fr) Procédé et appareil pour réaliser un reciblage efficace
WO2010030146A2 (fr) Système de réseau de collaboration de contenu et procédé de collaboration de contenu
WO2023286970A1 (fr) Serveur d'agence publicitaire en ligne, procédé d'agence publicitaire en ligne pour changer sélectivement des informations d'option de fonctionnement incluses dans des informations de campagne, et programme informatique pour exécuter ce procédé
WO2018043860A1 (fr) Dispositif de recommandation d'article de location au moyen d'un groupe de propension similaire et procédé d'utilisation associé
WO2014119959A1 (fr) Système de recherche de page et procédé correspondant
WO2017104922A1 (fr) Procédé et appareil pour fournir des contenus recommandés
WO2015126043A1 (fr) Procédé d'affichage de publicité, procédé de fourniture de publicité, et appareil appliqué à ceux-ci
WO2016148528A1 (fr) Dispositif électronique et procédé de traitement d'informations dans un dispositif électronique

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 14792304

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 14792304

Country of ref document: EP

Kind code of ref document: A1