Community discovery method capable of combining links to attribute information

A technology of attribute information and community discovery, applied in the field of social network and data mining, can solve problems such as not using calculations and high algorithm complexity, and achieve the effect of high accuracy and low complexity

Inactive Publication Date: 2018-07-27
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0005] Li Yafang and others proposed a non-negative matrix method (refer to Li Yafang, Jia Caiyan, Yu Jian. A review of community discovery methods using non-negative matrix factorization models [J]. Computer Science and Exploration, 2016, 10(01): 1- 13.), can use the data network data of connection information and attribute information for community analysis, but the algorithm complexity of this method is high, and it does not use calculation

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  • Community discovery method capable of combining links to attribute information
  • Community discovery method capable of combining links to attribute information
  • Community discovery method capable of combining links to attribute information

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Embodiment Construction

[0052] The community discovery method combining links and attribute information of the present invention will be further described below in conjunction with specific embodiments and specific experimental data sets, such as figure 1 Shown, the present invention comprises the following steps:

[0053] S1. Input social network data, and construct an adjacency matrix based on link information and an attribute matrix based on attribute information;

[0054] S2. Designing a joint Bayesian probability model by using the adjacency matrix and the attribute matrix;

[0055] S3. According to the joint Bayesian probability model, calculate the node membership matrix implied by the adjacency matrix and the attribute matrix according to the joint matrix decomposition method, calculate the maximum membership degree of the nodes in the membership matrix, and perform preliminary non-overlapping community division ;

[0056] S4. Calculate the absolute membership of the nodes in the membership...

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Abstract

The invention relates to the field of social network and data mining, and provides a community discovery method capable of combining links to attribute information mainly comprises the following steps: inputting social network data with links and attribute information, and constructing an adjacent matrix which takes a link relation as a basis and an attribute matrix which takes the attribute information as a basis; constructing a combined Bayesian probability model according to two data matrixes; calculating the maximum attribution ratio of nodes by using a non-negative matrix decomposition method to obtain preliminary community division; and calculating absolute attribution ratio of the nodes according to attribution conditions of the nodes to obtain an overlapped community structure. Link information in the social network is combined to the attribute information, the using ratio of data in community detection is increased favorably, the accuracy and efficiency of community discoverycan be improved, and the community discovery method is suitable for being applied to discovering a topical community with attributes and link information.

Description

technical field [0001] The invention relates to the fields of social network and data mining, in particular to a community discovery method combining link and attribute information. Background technique [0002] As the main carrier of information transmission, social network has important research significance for the amount of information it covers in today's society. From individuals to groups, from the small world to the big society, there are always implicit connections in real life that link people together. Community discovery is often used to analyze structural characteristics among social groups. [0003] The graph topology and node attributes have great reference value in social networks. It is obviously not convincing to study the structural characteristics of communities only from one point. Usually, a community represents a set with the same attributes. If there is A direct connection indicates that the social relationship link between two adjacent nodes is clos...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/00
CPCG06F16/951G06Q50/01
Inventor 黄海辉王欣禹果余浩周秀秀
Owner CHONGQING UNIV OF POSTS & TELECOMM
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