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Content recommending method and system

A content recommendation and content technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of recommendation system dependence, inaccurate recommendation results, etc., to improve the use value and recommendation effect, and score accurately Effect

Active Publication Date: 2014-01-29
TCL CORPORATION
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In view of the deficiencies in the prior art above, the purpose of the present invention is to provide a method and system for content recommendation, aiming to solve the problem that existing recommendation systems rely on user ratings and inaccurate recommendation results

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  • Content recommending method and system
  • Content recommending method and system

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Embodiment Construction

[0046] The present invention provides a content recommendation method and system. In order to make the purpose, technical solution and effect of the present invention more clear and definite, the present invention will be further described in detail below. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0047] see figure 1 , figure 1 The flow chart of a preferred embodiment of the recommended method for the content of the present invention, as shown in the figure, includes steps:

[0048] S101. Collect user original behavior data through an interactive program script, and perform statistics on the collected user original behavior data to obtain quantified user quantitative behavior data;

[0049] S102. Obtain the time coefficient of user behavior by simulating the activity of human life;

[0050]S103. According to the time coefficient of the user behavior and the quant...

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Abstract

The invention discloses a content recommending method and system. The method comprises the steps of collecting user original behavior data through an interactive program script and conducting statistics on the collected user original behavior data to obtain quantized user quantitative behavior data; obtaining a time factor of user behaviors by simulating human life activity; scoring how much the user likes an attended content to obtain the scoring situation; inputting the scoring condition into the collaborative filtering recommendation to obtain a recommended result, and pushing the recommended result to the user.

Description

technical field [0001] The present invention relates to the field of information recommendation, in particular to a content recommendation method and system based on a time coefficient simulating human life activity and implicit user behavior scoring. Background technique [0002] With the development of the Internet, in the current era of information overload, users need to spend a lot of time screening out the content of interest in the face of massive amounts of information. Recommender systems are considered to be the most effective way to solve the above problems. The recommendation system provides personalized services for users, that is, recommends products, videos, music, news, etc. that may be of interest to users according to their needs or preferences. It plays an important role in improving user experience and enhancing user loyalty. important role. Taking video as an example, almost all large video sites such as Hulu and Netflix are providing personalized reco...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 岳麓杨劼郑巧玲
Owner TCL CORPORATION
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