摘要
文本聚类是文本挖掘的一种重要方法。基于形式概念分析和概念相似度,给出一种新的多背景文本模糊聚类方法和模型。该方法不仅考虑了多背景关键词之间的语义关系,而且通过非距离计算得到模糊相似矩阵。可根据不同要求得到相应的聚类结果,具有较好的灵活性。最后通过示例说明了所给算法的可行性。
Text clustering is an impotant method in text mining. A novel multi-context text fuzzy clustering method and its model based on formal concept analysis and concept similarity is proposed. The semantic relationships between multi-context key words are taken into account and the fuzzy similarity matrix is derived from non-distance computing in this method. The corresponding clustering results are obtained according to the different requirements and this approach has better flexibility. Finally, the example is given to illustrate the feasibility of the algorithm.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第3期745-747,共3页
Computer Engineering and Design
基金
甘肃省自然科学基金项目(3ZS051-A25-037)
关键词
形式概念分析
概念相似度
模糊聚类方法
多背景
语义关系
formal concept analysis
concept similarity
fuzzy clustering method
multi-context
semantic relationship
