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Micro-blog recommendation method based on user characteristics and network relations

A technology of user characteristics and recommendation methods, applied in data processing applications, special data processing applications, instruments, etc., can solve unfavorable microblogs, improve the accuracy of recommended topics, and recommend algorithms that cannot effectively apply to recommendation systems for microblog topics, etc.

Inactive Publication Date: 2014-03-05
北京交通大学长三角研究院
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AI Technical Summary

Problems solved by technology

[0011] Therefore, the traditional recommendation algorithm cannot be effectively applied to the recommendation system of Weibo topics, which is not conducive to the improvement of the accuracy of Weibo recommended topics.

Method used

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  • Micro-blog recommendation method based on user characteristics and network relations
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  • Micro-blog recommendation method based on user characteristics and network relations

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Experimental program
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Embodiment Construction

[0069] Embodiments of the inventive method comprise the following steps:

[0070] 1) Establishment and update of network topology relationship matrix;

[0071] For m microblog users, the total number of topics published by these users is n, and an n×m matrix is ​​established;

[0072]

[0073] where N j is the total number of microblogs published by the jth user, and t(i, j) represents the number of microblogs belonging to topic i published by user j;

[0074] in It is the initial value of topic i when recommending to user j;

[0075] 2) Update the network topology relationship matrix;

[0076] Establish the attention intensity matrix, the initial attention intensity matrix B is the same as the network topology relationship matrix; that is, B=A;

[0077] a. At time T, if a in the network topology relationship matrix ij (T)=0, the element a of the network topology relationship matrix after a period of time t ij (T+t)>0, then focus on the element b at the correspondin...

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Abstract

The invention relates to a micro-blog recommendation method based on user characteristics and network relations. The method includes the following steps of firstly, building and updating a network topological relation matrix, secondly, updating the network topological relation matrix, thirdly, determining the association degree among different users, and fourthly, finally determining an attention intensity matrix. According to the method, the network relations between the users and topics are built, the association degree between the users and the topics is acquired, behaviors of the users are analyzed according to the change of topic content at a period of time, the association relation is further corrected through an analysis result, topics to which the users pay attention are accurately acquired and recommended to the users, and compared with a traditional recommendation method, the method effectively improves recommendation accuracy of micro-blog topics.

Description

technical field [0001] The invention relates to a data processing technology on the Internet, in particular to a microblog recommendation method based on user characteristics and network relationships. Background technique [0002] With the development of Internet technology, especially Web2.0 network applications, social networks such as Weibo are playing an increasingly important role in people's daily life. Compared with traditional portals, forums, and blogs, social networks such as Weibo have a larger volume of information release and more frequent user interactions. Information such as logs, microblogs, pictures, and status of friends who follow friends in social networks are sent to relevant user homepages in the form of push. This push mode not only strengthens user information interaction, but also brings users the potential of information storm Therefore, personalized recommendation algorithms in social networks will have a significant impact on improving user exp...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/3322G06F16/9535G06Q50/01
Inventor 刘云廉捷熊菲亓大鹏
Owner 北京交通大学长三角研究院
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