计算机与现代化Issue(5)：13-16,20,5.DOI:10.3969/j.issn.1006-2475.2015.05.003
融合差分进化和 SOM 的组合文本聚类算法
A Novel Assembled Text Clustering Algorithm Using Differential Evolution and SOM
摘要
Abstract
Self-organizing map ( SOM) is an important clustering model , which can effectively improve the accuracy of search en-gine.But it is sensitive to the initial connection weights .After analyzing the drawbacks of the self-organizing map algorithm , a novel assembled text clustering algorithm ( IDE-SOM ) based on improved differential evolution and self-organizing map is pro-posed.Firstly, the improved differential evolution is introduced to realize coarse clustering in the document feature set with the purpose of getting an optimized initial connection weights .Then the SOM algorithm is initialized to realize fine clustering using the initial connection weights .Finally, the experiment is conducted and the results illustrate the better clustering performance of the proposed hybrid approach in terms of the value of F-measure and entropy .关键词
改进差分进化算法/自组织映射/组合文本聚类Key words
improved differential evolution algorithm/self-organizing map (SOM)/assemble text clustering分类
信息技术与安全科学引用本文复制引用
姜凯,苑金海..融合差分进化和 SOM 的组合文本聚类算法[J].计算机与现代化,2015,(5):13-16,20,5.基金项目
山东省教育厅科研计划项目 （）
