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News recommendation method based on hypergraph sequencing

A recommendation method and graph sorting technology, applied in special data processing applications, using information identifiers to retrieve web data, instruments, etc., can solve the problems of accurate depiction of user interest, diversity, division, rationality, scalability, etc.

Active Publication Date: 2014-10-08
SOUTH CHINA UNIV OF TECH
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AI Technical Summary

Problems solved by technology

This type of method is of great significance to the practical application of news recommendation, but it still does not solve the essence of accurate description of user interest, the rationality of diversity division and the scalability of recommendation.

Method used

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  • News recommendation method based on hypergraph sequencing
  • News recommendation method based on hypergraph sequencing
  • News recommendation method based on hypergraph sequencing

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Embodiment Construction

[0053] The present invention will be further described below in conjunction with specific examples.

[0054] The news recommendation method based on hypergraph sorting described in this embodiment considers that the following four factors can tap the user's interest in news:

[0055] (1) The synergy of users' reading associations to news collections. That is, mining the user's reading pattern of news.

[0056] (2) Users' preference for named entities of past historical news. News named entities refer to places, people, event names, etc. that appear in the news, that is, to mine users' reading preferences for these entities.

[0057] (3) User preference for news category.

[0058] (4) Similarity between news categories.

[0059] This news recommendation method proposes to use these basic elements as points of the hypergraph, and the relationship between elements as hyperedges to construct a hypergraph model, and perform ranking analysis on the hypergraph model to obtain use...

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Abstract

The invention discloses a news recommendation method based on hypergraph sequencing. The method comprises the following steps: 1) pre-processing; 2) creating hypergraph; 3) building a matrix; 4) sequencing; 5) acquiring the sequencing result; 6) acquiring the recommendation result. According to the method, the hypergraph model is used to mine the internal relations and sequencing relations of a user and the contents of news, and thus a complex processing system of news recommendation is simplified to be a simple and clear association framework. The method is characterized in that the preprocessing of news recommendation is simplified, and a recommendation list is directly provided. With the adoption of the method, the accuracy of the recommendation result and user preference can be ensured well, and meanwhile, the variety of the recommendation result is also ensured on the premise that additional secondary selection for the recommendation result is saved.

Description

technical field [0001] The invention relates to the technical field of news recommendation, in particular to a news recommendation method based on hypergraph sorting. Background technique [0002] Today, with the rapid development of China's economy and the Internet, more and more people choose to use the Internet or mobile terminals to read news. However, abundant news information will also bring the problem of information overload. Therefore, the application of personalized news recommendation has practical significance. There are mainly two existing personalized news recommendation methods: 1) recommendation based on content analysis of historically browsed news, that is, content-based recommendation. This type of method uses the user's previous browsing news records, and according to the analysis of the content factors of the news, recommends news information similar to historical news to the user. This type of method has high accuracy, but it is not easy to expand, th...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/955
Inventor 董守斌古万荣袁华
Owner SOUTH CHINA UNIV OF TECH
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