Link prediction system and method for social network

A social network and prediction system technology, applied in the fields of link prediction and user relationship analysis for social networks, can solve problems such as link prediction reflecting network structure, and achieve the goal of improving topic expression ability, reducing complexity and improving accuracy. Effect

Active Publication Date: 2017-05-10
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

In addition, the LDA model does not fully reflect the contribution of the network structure to link prediction. In fact, there is a certain

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  • Link prediction system and method for social network
  • Link prediction system and method for social network
  • Link prediction system and method for social network

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[0026] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0027] The technical scheme that the present invention solves the problems of the technologies described above is:

[0028] Since the establishment of links between users is affected by both internal and external factors of users. Internal factors are specifically reflected in user behavior, which can be expressed as user interest and information interaction; while external factors are expressed as the influence of co-neighboring users on links between users. Therefore, the present invention starts from the three aspects of user's interest attention, information interaction and co-neighboring users, and aims at the potential interest relationship between user behavior information in the network and the de...

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Abstract

The invention provides a link prediction system and method for a social network, and belongs to the field of data mining and social network analysis. On the basis of online users and a user friendly relational network, a social network link prediction model is constructed from the three aspects of user focused interests, information interaction and common adjacency users. The method comprises the steps that firstly, for multiple interest label characteristics of users in a social network, an LDA theme model is used for performing modeling on the users, and theme distribution for user behaviors is obtained; secondly, Gaussian weighting is used for modifying standard LDA, and the theme expression ability is improved; finally, by introducing a common adjacency user contribution algorithm defined by hidden naive Bayes, link prediction is performed on synthesis user behavior characteristics and network structure characteristics. The correlative dependence of the common adjacency users is more sufficiently considered, link prediction is performed on synthesis user behavior characteristics and network structure characteristics, and key factors built by links are found.

Description

technical field [0001] The invention relates to the fields of data mining and social network analysis, and user relationship analysis, in particular to a social network-oriented link prediction method. Background technique [0002] With the continuous development of computer information technology and the rapid popularization of the Internet, social networks have gained more and more people's participation and attention. In recent years, social networking sites have gradually become an important channel for information dissemination and sharing. The relevant information left by users has made social networking a huge information platform, and the mining of these massive data has become a research hotspot. Among them, the research on user relationship analysis in social networks can help people better explain the evolution and discovery of network structures. [0003] At this stage, there are different aspects of research on user relationship analysis in social networks, mai...

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Application Information

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IPC IPC(8): G06F17/30G06Q10/04G06Q50/00
CPCG06F16/9535G06Q10/04G06Q50/01
Inventor 肖云鹏李茜曦刘宴兵柳靓云李晓娟张克毅赵金哲孙华超
Owner CHONGQING UNIV OF POSTS & TELECOMM
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