关键词: 改进差分进化算法, 自组织映射, 组合文本聚类

Abstract: Self-organizing map (SOM) is an important clustering model, which can effectively improve the accuracy of search engine. 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 proposed. 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.

Key words: improved differential evolution algorithm, self-organizing map (SOM), assemble text clustering