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Content recommendation method and device

A content recommendation and content technology, applied in the field of data processing, can solve the problems of unable to recommend content, unable to recommend content recommendation methods, etc.

Inactive Publication Date: 2014-10-15
HISENSE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to provide a content recommendation method and device to solve the problem that existing content recommendation methods cannot recommend content for some users or cannot recommend certain content to users

Method used

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  • Content recommendation method and device
  • Content recommendation method and device

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Embodiment Construction

[0021] The technical solutions provided by the embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0022] The content recommendation method provided by the embodiment of the present invention is as follows: figure 1 As shown, it specifically includes the following operations:

[0023] Step 100, obtaining the user's preference value for each content characteristic and the proportion of each content characteristic of the content.

[0024] In the embodiment of the present invention, the content characteristic is a characteristic extracted from the content, which reflects the classification, theme and so on of the content. Taking a video as an example, the content feature may be a topic classification of the video, such as "love", "friendship", "martial arts" and so on.

[0025] A piece of content may include multiple content properties. Assume that in a video, "love" accounts for 20%, "friendship" accounts for...

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Abstract

The invention discloses a content recommendation method and device and aims to solve the problem that content recommendation cannot be performed aiming at certain users or certain contents cannot be recommended to the users by the existing content recommendation method. The method comprises the steps of obtaining a preference value of a user for each content and the proportion of each content feature accounting for the content; determining the preference value of the user for the content according to the preference value of the user for each content and the proportion of the each content feature accounting for the content; performing content recommendation according to the determined preference value of the user for each content. The correlation between the contents or the users does not need to be determined according to the grading of the users, recommendation is performed according to the determined correlation, and the preference value of the user for the content can be determined by adopting the method provided by the embodiment even the user does not grade the content, thus further performing the content recommendation.

Description

technical field [0001] The present invention relates to the technical field of data processing, in particular to a content recommendation method and device. Background technique [0002] Personalized recommendation technology mines user interests based on historical records of user behavior and pushes content. [0003] The method often used in personalized recommendation is the content recommendation method based on collaborative filtering. The main idea of ​​this method is to use the user's rating on the content to calculate the correlation between the content or users, and then use this correlation to recommend. [0004] Using the user's ratings on the content, calculate the relevance between the contents, and then recommend the method as follows: use the user's rating on the content as a reference to determine the relevance between the contents, and then according to the relevance between the contents to the content to group. For example, the average value of all users...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/2457
Inventor 高雪松于旭张帅周翚胡伟凤许丽星谢杰王洁
Owner HISENSE
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