EP3286711A1 - Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias - Google Patents

Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Info

Publication number
EP3286711A1
EP3286711A1 EP16719697.1A EP16719697A EP3286711A1 EP 3286711 A1 EP3286711 A1 EP 3286711A1 EP 16719697 A EP16719697 A EP 16719697A EP 3286711 A1 EP3286711 A1 EP 3286711A1
Authority
EP
European Patent Office
Prior art keywords
media asset
user
preference information
preference
media
Prior art date
Legal status (The legal status 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 status listed.)
Withdrawn
Application number
EP16719697.1A
Other languages
German (de)
English (en)
Inventor
Craig Carmichael
Sashikumar Venkataraman
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Adeia Guides Inc
Original Assignee
Rovi Guides Inc
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
Priority claimed from US14/694,912 external-priority patent/US10003836B2/en
Priority claimed from US14/694,933 external-priority patent/US20160314404A1/en
Priority claimed from US14/694,934 external-priority patent/US20160314410A1/en
Priority claimed from US14/694,925 external-priority patent/US10575057B2/en
Application filed by Rovi Guides Inc filed Critical Rovi Guides Inc
Priority to EP18206866.8A priority Critical patent/EP3480766A1/fr
Priority to EP18206868.4A priority patent/EP3480767A1/fr
Publication of EP3286711A1 publication Critical patent/EP3286711A1/fr
Withdrawn legal-status Critical Current

Links

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
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40—Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • 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
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • 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
    • H04N21/4508—Management of client data or end-user data
    • H04N21/4532—Management of client data or end-user data involving end-user characteristics, e.g. viewer profile, preferences
    • 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
    • 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
    • H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
    • 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
    • H04N21/47—End-user applications
    • H04N21/475—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data
    • H04N21/4755—End-user interface for inputting end-user data, e.g. personal identification number [PIN], preference data for defining user preferences, e.g. favourite actors or genre

Definitions

  • control circuitry may provide the error value and data associated with the error value to a model and update the model based on the error value and the data associated with the error value. For example, the control circuitry may associate the error value with other data that can update the model to be more accurate when calculating media asset similarity values. The control circuitry may transmit the error value and the data to the model in order to improve the model's accuracy.
  • the control circuitry may then determine, using the normalized first preference information and the normalized second preference information, a user's level of enjoyment with respect to a media asset based on the common metric, where the first preference information and the second preference information each comprise data describing the user's indicated level of enjoyment of the media asset. For example, the control circuitry may have determined based on the first preference information from the first data space that a user's level of enjoyment of a movie named "Pirates of the Caribbean" is 7 on a scale of 1 to 10 where 10 is the highest level of enjoyment.
  • control circuitry may receive as part of the second data space users' ratings of media assets that the users have consumed.
  • the ratings may be in the form of a scaled number (e.g., from 1 to 10) and/or they may be in the form of text (e.g., user's review of a media asset).
  • levels of enjoyment that are expressly input by users may be referred to as "ratings.”
  • the control circuitry may transform the second preference information to second consumption layer preference information, where the second consumption layer preference information includes specific attributes that are indicative of users' preferences. For example, the control circuitry may determine that a user rated "Terminator” as a 9 on a scale of 1 to 10. The control circuitry may also determine that the user rated "Rambo” and "Pirates of the Caribbean” as an 8. The control circuitry may use the consumption model in order to determine, for example, that the user likes action movies.
  • the quality value associated with a sentimental similarity may be based on a number of users who have expressly input their level of enjoyment with respect to the two media assets. For example, if one data space only includes information based on monitoring whether users watched a specific movie and another data space includes information on whether the user watched a movie, what part of the movies the user watched, and if the user watched any other movie in the same sitting, the control circuitry may assign a higher quality value to the second data space.
  • the control circuitry may transform the preference information to consumption layer preference information, where the consumption layer preference information comprises attributes that are indicative of users' preferences. For example, the control circuitry may determine that preference information is in the form of monitored user interactions of the plurality of users with respect to the plurality of media assets. The control circuitry may then determine that a specific user has watched "Terminator,” "Rambo,” and "The Pirates of the Caribbean.” The control circuitry may use the consumption model in order to determine, for example, that the user likes action movies. Additionally or alternatively, the control circuitry may determine that the user likes thrillers based on the user watching
  • a model may be used to determine the user's expected level of enjoyment with respect to a media asset based on the user's preference information with respect to other media assets.
  • the media guidance application may provide a display screen with media guidance data organized in one of several ways, such as by time and channel in a grid, by time, by channel, by source, by content type, by category (e.g., movies, sports, news, children, or other categories of programming), or other predefined, user-defined, or other organization criteria.
  • FIG. 1 shows illustrative grid of a program listings display 100 arranged by time and channel that also enables access to different types of content in a single display.
  • listings for these content types may be included directly in grid 102. Additional media guidance data may be displayed in response to the user selecting one of the navigati onal i cons 120. (Pressing an arrow key on a user input device may affect the display in a similar manner as selecting navigational icons 120.)
  • Display 100 may also include video region 122, advertisement 124, and options region 26.
  • Video region 122 may allow the user to view and/or preview programs that are currently available, will be available, or were available to the user.
  • the content of video region 122 mav correspond to, or be independent from, one of the listings displayed in grid 102.
  • Grid displays including a video region are sometimes referred to as picture-in-guide (PIG) displays.
  • PIG displays and their functionalities are described in greater detail in Satterfield et al . U.S. Patent No. 6,564,378, issued May 13, 2003 and Yuen et ai. U.S. Patent No. 6,239,794, issued May 29, 2001, which are hereby incorporated by reference herein in their entireties.
  • PIG displays may be included in other media guidance application display screens of the embodiments described herein.
  • Display 312 may be one or more of a monitor, a television, a liquid crystal display (LCD) for a mobile device, amorphous silicon display, low temperature poly silicon display, electronic ink display, electrophoretic display, active matrix display, electro-wetting display, electrofluidic display, cathode ray tube display, light-emitting diode display, electroluminescent display, plasma display panel, high-performance addressing display, thin-film transistor display, organic light-emitting diode display, surface-conduction electron-emitter display (SED), laser television, carbon nanotubes, quantum dot display, interferometric modulator display, or any other suitable equipment for displaying visual images.
  • display 3 2 may be HDTV-capable.
  • the user may also set various settings to maintain consistent media guidance application settings across in-home devices and remote devices.
  • Settings include those described herein, as well as channel and program favorites, programming preferences that the guidance application utilizes to make programming recommendations, display preferences, and other desirable guidance settings. For example, if a user sets a channel as a favorite on, for example, the web site www.allrovi.com on their personal computer at their office, the same channel would appear as a favorite on the user's in-home devices (e.g., user television equipment and user computer equipment) as well as the user's mobile devices, if desired. Therefore, changes made on one user equipment device can change the guidance experience on another user equipment device, regardless of whether they are the same or a different type of user equipment device. In addition, the changes made may be based on settings input by a user, as well as user activity monitored by the guidance application.
  • NBC is a trademark owned by the National Broadcasting
  • Media guidance data source 418 may provide media guidance data, such as the media guidance data described above.
  • Media guidance data may be provided to the user equipment devices using any suitable approach.
  • the guidance application may be a stand-alone interactive television program guide that receives program guide data via a data feed (e.g., a continuous feed or trickle feed).
  • Program schedule data and other guidance data may be provided to the user equipment on a television channel sideband, using an in-band digital signal, using an out-of-band digital signal, or by any other suitable data transmission technique.
  • Program schedule data and other media guidance data may be provided to user equipment on multiple analog or digital television channels.
  • Content and/or media guidance data delivered to user equipment devices 402, 404, and 406 may be over-the-top (OTT) content.
  • OTT content delivery allows Internet-enabled user devices, including any user equipment device described above, to receive content that is transferred over the Internet, including any content described above, in addition to content received over cable or satellite connections.
  • OTT content is delivered via an Internet connection provided by an Internet service provider (ISP), but a third party distributes the content.
  • ISP Internet service provider
  • the ISP may not be responsible for the viewing abilities, copyrights, or redistribution of the content, and may only transfer IP packets provided by the OTT content provider.
  • Examples of OTT content providers include YOUTUBE, NETFLIX, and HULU, which provide audio and video via IP packets.
  • the media guidance application may gain access to the first data space via different methods.
  • a content provider such as Netflix® may provide a file transfer protocol ("FTP") site that would allow for downloading the user preference information within the Netflix® data space.
  • FTP file transfer protocol
  • the preference information may be stripped of all user identifying data and user identification numbers may be assigned to each user. Additionally or alternatively, the preference information may be downloaded by crawling the Internet with a special application in order to retrieve the user preference information.
  • the complete data space may also be spread over several files that may need to be merged in order to access the complete data space.
  • the second preference information is associated with a second data space, describes preferences of a second plurality of users with respect to a second plurality of media assets, and is computed using a different metric than a metric that the first preference
  • a content provider like Hulu® may also have its own user preference information. That preference information may be obtained in the same manner as the first preference information.
  • control circuitry 304 generates for display items 564, 566, and 568 in display 550 to represent the amount of time that an average user watched the respective movies together with the total time of the movie. For example, control circuitry 304 determines that an average user watched "Avatar" for 140 minutes out of 150 minutes.
  • control circuitry 304 may normalize the first preference information and the second preference information such that both the first preference information and the second preference information are converted to a scheme on which a common metric may be applied.
  • Control circuitry 304 may convert the star ratings 508, 510, and 512 in display 550 as well as numerical ratings 558, 560, and 562 to one metric.
  • control circuitry 304 may access each data space and determine what kinds of preference information exist within each data space.
  • the term "kind of preference information" refers to user preference information items as listed in the definition of user preference information.
  • User preference information may come in various forms. For example, binary information may be part of user preference information (e.g., whether the user consumed a media asset).
  • 11 hasViewedfu, i) represents data on whether user u has consumed at least a part of media asset i . This may be a binar representation.
  • tuneins(u, i) represents the number of tune-ins for EPG
  • d represents a data space identifier for a data space that includes users' indicated levels of enjoyment with respect to media assets
  • q u ' i ⁇ d) represents a quality of an estimated user u' s indicated level of enjoyment with respect to media asset i in data space d based on user u' s monitored interactions with media asset i
  • r* (d) represents user u' s indicated level of enjoyment with respect to media asset i in data space d r'.
  • (d) represents user u' s estimated level of enj oyment with respect to media asset i in data space d based on user u's monitored interactions with media asset i

Abstract

L'invention concerne des procédés et des systèmes de détermination d'une valeur d'erreur sur la base de la comparaison d'une valeur de similitude de biens multimédias prévue correspondant à un premier bien multimédia et à un deuxième bien multimédia, telle qu'elle est déterminée au moyen d'un modèle, à une valeur de similitude de biens multimédias déterminée à partir d'informations de préférence d'utilisateur associées à plusieurs espaces de données. Des informations de préférence d'utilisateur sont reçues de deux espaces de données qui sont gérés par des prestataires de contenu différents. Les informations de préférence d'utilisateur provenant des deux espaces de données sont normalisées et une indication de similitude entre deux biens multimédias est déterminée. L'indication de similitude est comparée à une valeur de similitude prévue reçue d'un modèle et une valeur d'erreur est déterminée sur la base de la comparaison de la valeur de similitude attendue et de la valeur de similitude.
EP16719697.1A 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias Withdrawn EP3286711A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
EP18206866.8A EP3480766A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias
EP18206868.4A EP3480767A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US14/694,912 US10003836B2 (en) 2015-04-23 2015-04-23 Systems and methods for improving accuracy in media asset recommendation models based on users' levels of enjoyment with respect to media assets
US14/694,933 US20160314404A1 (en) 2015-04-23 2015-04-23 Systems and methods for improving accuracy in media asset recommendations based on data from multiple data spaces
US14/694,934 US20160314410A1 (en) 2015-04-23 2015-04-23 Systems and methods for improving accuracy in media asset recommendations based on data from one data space
US14/694,925 US10575057B2 (en) 2015-04-23 2015-04-23 Systems and methods for improving accuracy in media asset recommendation models
PCT/US2016/028587 WO2016172306A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Related Child Applications (2)

Application Number Title Priority Date Filing Date
EP18206866.8A Division EP3480766A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias
EP18206868.4A Division EP3480767A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Publications (1)

Publication Number Publication Date
EP3286711A1 true EP3286711A1 (fr) 2018-02-28

Family

ID=55861261

Family Applications (3)

Application Number Title Priority Date Filing Date
EP18206866.8A Withdrawn EP3480766A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias
EP16719697.1A Withdrawn EP3286711A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias
EP18206868.4A Withdrawn EP3480767A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Family Applications Before (1)

Application Number Title Priority Date Filing Date
EP18206866.8A Withdrawn EP3480766A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Family Applications After (1)

Application Number Title Priority Date Filing Date
EP18206868.4A Withdrawn EP3480767A1 (fr) 2015-04-23 2016-04-21 Systèmes et procédés d'amélioration de la précision dans les modèles de recommandation de biens multimédias

Country Status (6)

Country Link
EP (3) EP3480766A1 (fr)
JP (2) JP2018518722A (fr)
CN (1) CN106471819B (fr)
AU (1) AU2016252645A1 (fr)
CA (1) CA2954133A1 (fr)
WO (1) WO2016172306A1 (fr)

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Also Published As

Publication number Publication date
EP3480766A1 (fr) 2019-05-08
CN106471819B (zh) 2020-10-20
CA2954133A1 (fr) 2016-10-27
JP2018518722A (ja) 2018-07-12
EP3480767A1 (fr) 2019-05-08
WO2016172306A1 (fr) 2016-10-27
JP2021048611A (ja) 2021-03-25
AU2016252645A1 (en) 2017-01-19
CN106471819A (zh) 2017-03-01

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