Community discovery method and system

A technology for community discovery and community, applied in the field of community discovery methods and systems, it can solve problems such as loose structure, inaccurate results, and inappropriate data, and achieve the effect of improving accuracy

Inactive Publication Date: 2013-09-25
NAT UNIV OF DEFENSE TECH
View PDF4 Cites 31 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, although many existing graph clustering methods have combined the structure of the network and the attribute characteristics of nodes (or node attributes or node attribute information) (for example, constructing new graph clustering methods by weighting attributes and structures) network, and perform community division on the new network), but the results of these clusters often have communities that are not structurally close or not related, which leads to inaccurate results of community discovery; moreover, the time complexity of these methods High, not suitable for processing large-scale data

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Community discovery method and system
  • Community discovery method and system
  • Community discovery method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0038] For the convenience of the following description, the following concepts are first introduced:

[0039] 1. Network diagram

[0040] Given a network graph G=(V,E), where V={v 1 ,v 2 ,...v n} represents the set of nodes in the network, E={e 1 ,e 2 ,...,e m} represents a set of edges. and |V|=n and |E|=m. Usually, you can use i ,v j > represents node v i and v j The edges connected between, where, 1≤i≤n, 1≤j≤n, i≠j. Therefore, the edge can also be expressed as e k =i ,v j >, 1≤k≤m. In a social network, an edge can represent that its connected nodes (users) are friends, fans, etc., depending on the goal of the analysis. The network graph involved in the text is an undirected graph, and the edges represented by the node pairs in G are out of order, that is, i ,v j > and j ,v i > indicates the same edge.

[0041] 2. Netw...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a community discovery method. The community discovery method includes the steps that community division is conducted on a plurality of nodes in a network based on modularity maximization, and community boundary nodes obtained in the last step are adjusted based on community property entropy minimality. The community discovery method further includes the steps that if the community division obtained after adjustment meets an end condition, the community division will be used as final community division; otherwise, the communities obtained after adjustment will be used as nodes, community division will be conducted on the nodes again, and the community boundary nodes need to be readjusted. According to the community discovery method, the structure of the network and the attributive characters of the nodes are taken into account at the same time, and the degree of accuracy of community discovery is improved. In addition, the community discovery method is close to be linear in time complexity and suitable for large-scale on-line social network data.

Description

technical field [0001] The invention relates to the fields of complex network analysis and data mining, in particular to a community discovery method and system. Background technique [0002] With the in-depth study of the nature and mathematical characteristics of social networks, researchers have found that many networks have a common feature - community structure, that is to say, the network is composed of several "groups" or "groups", each The connections between nodes in a "cluster" are very tight, while the connections between "clusters" are relatively sparse. The discovery of network communities can help people understand the structural characteristics of the network more effectively, so as to provide more effective and personalized services. For example: for information recommendation, user classification, and Internet group behavior analysis. On online social networks, the self-media nature of individuals often produces a large amount of text content, which reflec...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/00G06F17/30
Inventor 徐冰莹贾焰杨树强周斌韩伟红李爱平韩毅李莎莎
Owner NAT UNIV OF DEFENSE TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap