|Table of Contents|

Concerned objects multi-community detection based on improved complete subgraph model

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2016年06期
Page:
674-
Research Field:
Publishing date:

Info

Title:
Concerned objects multi-community detection based on improved complete subgraph model
Author(s):
Feng HongqiLei ChenyangShen TianyuYang Changchun
School of Information Science and Engineering,Changzhou University,Changzhou 213164,China
Keywords:
complete subgraph model concerned objects multi-classification threshold division data mining algorithm
PACS:
TP31
DOI:
10.14177/j.cnki.32-1397n.2016.40.06.006
Abstract:
A multi-community detection method based on improved complete subgraph model is proposed using threshold division for multi-community division of users and concerned objects,because complete subgraph model cannot divide users and concerned objects based on multi-classification.Experiment result shows that compared with classical data mining algorithm K-medoids,this method is more accurate.

References:

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Last Update: 2016-12-30