Research of Text Clustering Based on Ant Colony Algorithm

ZHANG Hai-tao; ZHOU Ai-wu

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Research of Text Clustering Based on Ant Colony Algorithm

更新时间：2026-09-04

- Research of Text Clustering Based on Ant Colony Algorithm
- Vol. 33, Issue 1, Pages: 81-84(2016)
- 作者机构：
  
  安徽大学计算机科学与技术学院,安徽,合肥,230601
- 作者简介：
- 基金信息：
- DOI：
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- Published：2016
- 稿件说明：
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张海涛, 周爱武. 蚁群算法在文本聚类中的应用研究[J]. 微电子学与计算机, 2016, 33(1): 81-84, 89.

ZHANG Hai-tao, ZHOU Ai-wu. Research of Text Clustering Based on Ant Colony Algorithm[J]. 2016, 33(1): 81-84.
张海涛, 周爱武. 蚁群算法在文本聚类中的应用研究[J]. 微电子学与计算机, 2016, 33(1): 81-84, 89. DOI：

ZHANG Hai-tao, ZHOU Ai-wu. Research of Text Clustering Based on Ant Colony Algorithm[J]. 2016, 33(1): 81-84. DOI：

摘要

为提高文本聚类结果的精度和文本聚类的收敛速度

对蚁群文本聚类算法进行了改进

改进的措施主要包括修改迭代终止条件、动态调整蚂蚁观察半径、改变蚂蚁移动策略

并且在复旦大学中文文本分类语料库上进行了仿真实验.实验结果表明

改进后的蚁群文本聚类算法不仅加快了文本聚类的收敛速度

而且提高了文本聚类结果的精度.

Abstract

In order to improve the accuracy of text clustering and clustering of convergence

Ant Colony clustering algorithm was improved. Measures for improvement consists of 3 main aspects

namely modified linear iteration stopping conditions

dynamic adjustment of ants observed radius

change ants moving strategy. An experiment was finished in Fudan University on the Chinese text corpus.Eexperimental results show that the improved Ant Colony clustering algorithm can speed up the convergence of the text clustering and improved the accuracy of text clustering.

关键词

Keywords

references

唐东明. 聚类分析及其应用研究[D]. 四川: 电子科技大学, 2010.

Hong Jiang, YuQing-song, Gong Yu. An improved ant colony clustering algorithm[C]// Biomedical Engineering and Informatics (BMEI), 2010 3rd International Conference on pages. Yantai: IEEE: 2010: 2368-2372.

Dorigo M, Bonabeau E, Theralulaz G. Ant algorithms and stig-mergy[J]. Future Generation Computer System, 2000, 16(8): 851-871. DOI: 851

段海滨. 蚁群算法原理及应用[M]. 北京: 科学出版社, 2005

王小华, 沈杰, 王荣波. 一种新的基于蚁群和凝聚的混合聚类算法[J]. 杭州电子科技大学学报, 2012, 30(1): 26-29. DOI: 26

吴夙慧, 成颖, 郑彦宁, 等. 文本聚类中文本表示和相似度计算研究综述[J]. 情报科学, 2012, 30(4): 622-627 DOI: 622

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