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Web community dividing method based on importance degrees and separation degrees of nodes

A node importance, web community technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of only considering the density of the community, the reliability of community division is not high, and ignoring the sparseness of the community. Reliable partitioning, rationality and improved accuracy

Active Publication Date: 2018-03-30
山西朔铭科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Existing methods mainly use aggregation density, densely connected clusters in the network, and strongly connected cores as the characteristics of community possibility, only considering the density within the community, but ignoring the sparsity between communities, resulting in community division. The reliability is not high

Method used

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  • Web community dividing method based on importance degrees and separation degrees of nodes
  • Web community dividing method based on importance degrees and separation degrees of nodes
  • Web community dividing method based on importance degrees and separation degrees of nodes

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Embodiment Construction

[0034] Specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] The network community discovery method described in the present invention is implemented by a computer program, figure 1 Shown is a computer-implemented system structure diagram. The following will follow figure 2 The implementation process shown in this example is combined with a specific web network (such as image 3 Shown), detail the specific implementation of the technical solution proposed by the present invention. exist image 3 In the shown Web network, circular nodes represent pages in the Web network, and lines between nodes represent links between Web pages, including a total of 39 Web pages and 80 links between them. Using the method of the present invention will image 3 The shown Web network is divided into K=3 communities, and its implementation mainly includes the following key contents:

[0036] Step 1. Express t...

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Abstract

The invention discloses a Web community dividing method based on importance degrees and separation degrees of nodes, and belongs to the technical field of Web data mining. The method includes the following steps of firstly, representing a Web network in the form of a figure, representing Web pages through the nodes in the figure, and representing the links between the Web pages through sides between the nodes; secondly, calculating the degree of each node in the figure and the similarity among the nodes; thirdly, calculating the separation degree of each node through the importance degree of the node and the similarity among the nodes; fourthly, calculating the representation degree of each node through the importance degree and the separation degree of the node; fifthly, sequencing all the nodes in the network according to the importance degrees, and selecting a central node of the network community according to the representation degrees of the nodes; sixthly, determining a communitylabel of each network node based on the importance degree and the similarity of the nodes; seventhly, putting the Web pages represented by the nodes with the same community labels in the same community to complete community division.

Description

technical field [0001] The invention relates to the technical field of Web data mining, in particular to a method for dividing Web communities based on node importance and separation. Background technique [0002] With the continuous development of the Internet, people are publishing and obtaining information more and more on the Internet. The Web has become the main platform for information manufacturing, processing, processing and publishing. This platform provides news, finance, advertising, business, culture, Education and other information services. Compared with traditional data, Web data has the characteristics of massive scale, unorganized, heterogeneous, decentralized, and dynamic. These characteristics make people have many difficulties in the use of Web data. How to summarize and upgrade the data on the Web into knowledge and facilitate users to search and query has become an important issue in the development of Internet technology. Although the Web is disorder...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q50/00
CPCG06Q50/01G06F16/9535
Inventor 杜航原白亮
Owner 山西朔铭科技有限公司
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