Social relation-perceiving IPTV user behavioral modeling and program recommendation method

A social relationship and program recommendation technology, applied in the field of IPTV services, can solve problems such as errors, achieve the effect of optimizing recommendation results and improving the tensor decomposition model

Active Publication Date: 2018-11-02
陕西识代运筹信息科技股份有限公司
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  • Application Information

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Problems solved by technology

Therefore, people living in rural areas and cities have different viewing preferences in different time contexts. If a unified standard is used for program recommendation, there may be errors

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  • Social relation-perceiving IPTV user behavioral modeling and program recommendation method
  • Social relation-perceiving IPTV user behavioral modeling and program recommendation method
  • Social relation-perceiving IPTV user behavioral modeling and program recommendation method

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Embodiment Construction

[0066] As one of the most important applications in the "triple play integration", IPTV already has a large number of users. Through the IPTV service, users can watch any TV program they are interested in at any time, which greatly increases the flexibility for users to choose TV programs. However, users often face information overload when choosing from thousands of movies, TV series or other programming. Moreover, users living in different regions have different lifestyles (such as production methods, living standards, daily routines, etc.), and people have different interests in watching TV programs. People living in rural areas and cities are different in terms of occupation, lifestyle, educational level, and ideas. The main mode of production of users living in rural areas is farming and animal husbandry, with strong seasonality, relatively loose time, and relatives and neighbors. , then their viewing time is related to the time of farming activities, and the time is rel...

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Abstract

The invention discloses a social relation-perceiving IPTV user behavioral modeling and program recommendation method, having the main works comprising: (1) analyzing the behavior of an IPTV user baseson a historical viewing log, and constructing viewing preference models of the user and a group to which the user belongs by combining the user group clustering result; (2) avoiding harmful effects brought by data sparsity to recommendation by using dense program category similarity matrixes, improving tensor decomposition models, and optimizing the recommendation result; and (3) realizing user oriented personalized IPTV program recommendation by comprehensively considering the viewing preferences of the IPTV user and the group to which the user belongs. Compared with the existing recommendation algorithm, the method provided by the invention obviously improves the recommendation accuracy, the recall rate, and the like.

Description

technical field [0001] The invention relates to the field of IPTV services, in particular to a social relationship-aware IPTV user behavior modeling and program recommendation method. Background technique [0002] In recent years, under the impetus of the Internet, IPTV, as one of the most typical applications of "triple play", has already had a large number of users. IPTV provides users with personalized interactive services, such as live TV, video on demand and time-shifted playback. Live TV, users can watch the video content being broadcast by various TV stations through this service. Compared with traditional broadcast TV, through IPTV, users can watch richer channel content, and there are high-definition channels for users to choose from. Video on demand, users can watch massive video resources recorded in advance at any time according to their personal preferences, usually movies, TV dramas, and variety shows. Time-shifted look-back, allowing users to watch video co...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04N21/25H04N21/258H04N21/466
CPCH04N21/251H04N21/252H04N21/25891H04N21/4668
Inventor 尹小燕米晓倩徐成刘浩王华王薇徐丹汤战勇陈峰房鼎益
Owner 陕西识代运筹信息科技股份有限公司
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