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1. WO2022030714 - USER CLASSIFICATION BASED ON USER CONTENT VIEWED

Publication Number WO/2022/030714
Publication Date 10.02.2022
International Application No. PCT/KR2021/001561
International Filing Date 05.02.2021
IPC
H04N 21/466 2011.1
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
NPICTORIAL COMMUNICATION, e.g. TELEVISION
21Selective content distribution, e.g. interactive television or video on demand
40Client devices specifically adapted for the reception of, or interaction with, content, e.g. STB ; Operations thereof
45Management 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 or resolving scheduling conflicts
466Learning process for intelligent management, e.g. learning user preferences for recommending movies
H04N 21/442 2011.1
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
NPICTORIAL COMMUNICATION, e.g. TELEVISION
21Selective content distribution, e.g. interactive television or video on demand
40Client devices specifically adapted for the reception of, or interaction with, content, e.g. STB ; Operations thereof
43Processing 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 synchronizing decoder's clock; Client middleware
442Monitoring 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 or the storage space available from the internal hard disk
G06N 3/04 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
G06N 3/08 2006.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
CPC
G06N 20/00
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
20Machine learning
G06N 3/0445
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0445Feedback networks, e.g. hopfield nets, associative networks
G06N 3/0481
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0481Non-linear activation functions, e.g. sigmoids, thresholds
G06N 3/049
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
049Temporal neural nets, e.g. delay elements, oscillating neurons, pulsed inputs
G06N 3/082
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
082modifying the architecture, e.g. adding or deleting nodes or connections, pruning
H04N 21/251
HELECTRICITY
04ELECTRIC COMMUNICATION TECHNIQUE
NPICTORIAL COMMUNICATION, e.g. TELEVISION
21Selective content distribution, e.g. interactive television or video on demand [VOD]
20Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
25Management 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
251Learning process for intelligent management, e.g. learning user preferences for recommending movies
Applicants
  • SAMSUNG ELECTRONICS CO., LTD. [KR]/[KR]
Inventors
  • PALCZEWSKI, Tomasz Jan
  • PRATURY, Praveen
  • LEE, Hyunchul
  • KIM, Hyunwoo
Agents
  • Y.P.LEE, MOCK & PARTNERS
Priority Data
16/985,16104.08.2020US
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) USER CLASSIFICATION BASED ON USER CONTENT VIEWED
(FR) CLASSIFICATION D'UTILISATEUR SUR LA BASE D'UN CONTENU D'UTILISATEUR VISUALISÉ
Abstract
(EN) A method implemented by one or more computing systems includes accessing content viewing data associated with a first user account, wherein the first user account is associated with one or more client devices. The content viewing data includes temporal-based content viewing data. The method further includes determining, using one or more sequence models, a set of content viewing features based on the temporal-based content viewing data, and concatenating the content viewing features into a single computational array. The method further includes providing, through one or more dense layers of a deep-learning model, the single computational array to an output layer of the deep-learning model, and calculating, based on the output layer, one or more probabilities for one or more labels for the first user account. Each label includes a predicted attribute for the first user account.
(FR) Un procédé mis en œuvre par un ou plusieurs systèmes informatiques consiste à accéder à des données de visualisation de contenu associées à un premier compte utilisateur, le premier compte utilisateur étant associé à un ou plusieurs dispositifs clients. Les données de visualisation de contenu comprennent des données de visualisation de contenu à base temporelle. Le procédé consiste en outre à déterminer, à l'aide d'un ou de plusieurs modèles de séquence, un ensemble de caractéristiques de visualisation de contenu sur la base des données de visualisation de contenu à base temporelle, et à concaténer des caractéristiques de visualisation de contenu en un réseau de calcul unique. Le procédé consiste en outre à fournir, à travers une ou plusieurs couches denses d'un modèle d'apprentissage profond, le réseau de calcul unique à une couche de sortie du modèle d'apprentissage profond, et à calculer, sur la base de la couche de sortie, une ou plusieurs probabilités concernant une ou plusieurs étiquettes relatives au premier compte utilisateur. Chaque étiquette comprend un attribut prédit pour le premier compte utilisateur.
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