CA3143665A1 - Systemes et procedes pour ameliorer des recommandations de contenu a l'aide d'un modele appris - Google Patents

Systemes et procedes pour ameliorer des recommandations de contenu a l'aide d'un modele appris Download PDF

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Publication number
CA3143665A1
CA3143665A1 CA3143665A CA3143665A CA3143665A1 CA 3143665 A1 CA3143665 A1 CA 3143665A1 CA 3143665 A CA3143665 A CA 3143665A CA 3143665 A CA3143665 A CA 3143665A CA 3143665 A1 CA3143665 A1 CA 3143665A1
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CA
Canada
Prior art keywords
content
recommendations
consumption
model
user
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.)
Pending
Application number
CA3143665A
Other languages
English (en)
Inventor
Lakhan Tanaji KADAM
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 US16/806,995 external-priority patent/US20210274256A1/en
Priority claimed from US16/806,991 external-priority patent/US11551086B2/en
Application filed by Rovi Guides Inc filed Critical Rovi Guides Inc
Publication of CA3143665A1 publication Critical patent/CA3143665A1/fr
Pending legal-status Critical Current

Links

Classifications

    • 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
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/044—Recurrent networks, e.g. Hopfield networks
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/084—Backpropagation, e.g. using gradient descent
    • 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]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
    • H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending 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
    • H04N21/45—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
    • H04N21/4662—Learning process for intelligent management, e.g. learning user preferences for recommending movies characterized by learning algorithms
    • H04N21/4666—Learning process for intelligent management, e.g. learning user preferences for recommending movies characterized by learning algorithms using neural networks, e.g. processing the feedback provided by the user

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Evolutionary Computation (AREA)
  • Signal Processing (AREA)
  • Multimedia (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • General Health & Medical Sciences (AREA)
  • Data Mining & Analysis (AREA)
  • Molecular Biology (AREA)
  • Computational Linguistics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Biophysics (AREA)
  • Biomedical Technology (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)

Abstract

L'invention concerne des systèmes et des procédés conçus pour un moteur de recommandations qui génère des recommandations de contenu à l'aide d'un modèle appris qui est personnalisé d'après les informations correspondant à la consommation de contenu. Les techniques de l'invention fournissent un modèle appris permettant de fournir des recommandations de contenu. Le modèle appris peut avoir été appris à l'aide d'un ensemble prédéfini de données d'apprentissage agnostiques d'un profil d'utilisateur particulier. Un système reçoit des informations correspondant à la consommation de contenu. Le système peut associer les informations correspondant à la consommation de contenu à un profil. Le système génère un modèle personnalisé d'après les informations correspondant à la consommation de contenu et le modèle appris. Le modèle personnalisé peut être associé au profil utilisateur. Le système génère les recommandations de contenu à l'aide du modèle personnalisé. Le système provoque ensuite la fourniture des recommandations de contenu.
CA3143665A 2020-03-02 2020-12-21 Systemes et procedes pour ameliorer des recommandations de contenu a l'aide d'un modele appris Pending CA3143665A1 (fr)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US16/806,995 2020-03-02
US16/806,991 2020-03-02
US16/806,995 US20210274256A1 (en) 2020-03-02 2020-03-02 Systems and methods for improving content recommendations using a trained model
US16/806,991 US11551086B2 (en) 2020-03-02 2020-03-02 Systems and methods for improving content recommendations using a trained model
PCT/US2020/066409 WO2021178024A1 (fr) 2020-03-02 2020-12-21 Systèmes et procédés pour améliorer des recommandations de contenu à l'aide d'un modèle appris

Publications (1)

Publication Number Publication Date
CA3143665A1 true CA3143665A1 (fr) 2021-09-10

Family

ID=74184936

Family Applications (1)

Application Number Title Priority Date Filing Date
CA3143665A Pending CA3143665A1 (fr) 2020-03-02 2020-12-21 Systemes et procedes pour ameliorer des recommandations de contenu a l'aide d'un modele appris

Country Status (2)

Country Link
CA (1) CA3143665A1 (fr)
WO (1) WO2021178024A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114822005B (zh) * 2022-06-28 2022-09-20 深圳市矽昊智能科技有限公司 基于人工智能的遥控意图预测方法、装置、设备及介质

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1867068A (zh) 1998-07-14 2006-11-22 联合视频制品公司 交互式电视节目导视系统及其方法
AR019932A1 (es) 1998-07-17 2002-03-27 United Video Properties Inc Una disposicion de guias de programacion televisiva interactivas que tiene multiples dispositivos dentro de una residencia de un grupo familiar y un método que la emplea
AR020608A1 (es) 1998-07-17 2002-05-22 United Video Properties Inc Un metodo y una disposicion para suministrar a un usuario acceso remoto a una guia de programacion interactiva por un enlace de acceso remoto
US10616625B2 (en) * 2018-05-21 2020-04-07 Hulu, LLC Reinforcement learning network for recommendation system in video delivery system

Also Published As

Publication number Publication date
WO2021178024A1 (fr) 2021-09-10

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