基于局部模块度社团划分算法的文本概念聚类新方法  

A New Method for Text Concept Clustering based on Detecting Community Structures by Local Modularity in Complex Network

作　　者：刘绍海 安娜 祁越 

机构地区：[1]武警警种学院训练部,北京102202 [2]装备学院航天装备系,北京101416

出　　处：《装备制造技术》2017年第1期12-15,共4页Equipment Manufacturing Technology

摘　　要：提出一种将概念格和社团划分方法两种理论结合的文本聚类方法,首先将节点特征值权值按照从大到小的顺序映射到形式背景中,然后通过计算出形式背景中概念相似度的大小,构造L网络,最后根据局部模块度社团划分算法规则对待聚类文本进行聚类。This paper gives a new text clustering method which takes the advantages of concept lattice and complex network. The algorithm firstly computes the weights of the key words and then the formal context is constructed in terms of key words which have the proper weight. Secondly, building L network ,the similarities between concepts are computed, clustering the text of cluster by detecting community structures by local modularity algorithm rule, clustering results can be received.

关 键 词：复杂网络 文本聚类 综合特征值 局部模块度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]