| 基于语义相似度的Web文档聚类算法 |
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| 引用本文： | 李毅,王浩,杨静.基于语义相似度的Web文档聚类算法[J].合肥工业大学学报(自然科学版),2009,32(12). |
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| 作者姓名： | 李毅 王浩 杨静 |
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| 作者单位： | 合肥工业大学,计算机与信息学院,安徽,合肥,230009 |
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| 基金项目： | 安徽省自然科学基金资助项目，合肥工业大学科学研究发展基金资助项目 |
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| 摘 要： | 文章提出基于语义相似度的Web文档聚类算法--WDCSS算法,依据文档关键词之间的相似度生成最小树,通过概率统计来确定最小树中相似度阚值,并对最小树中进行切割,同时对较小的子类进行划分合并.实验表明,WECSS不仅能为具有各种不同聚类形状的数据集准确地分析出数据中存在的合理聚类和例外样本,而且避免了用户参数选择所造成聚类质最降低问题.
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| 关 键 词： | Web文档聚类 语义相似度 聚类算法 最小树 |
Web document clustering algorithm based on semantic similarity |
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| LI Yi,WANG Hao,YANG Jing.Web document clustering algorithm based on semantic similarity[J].Journal of Hefei University of Technology(Natural Science),2009,32(12). |
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| Authors: | LI Yi WANG Hao YANG Jing |
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| Abstract: | A Web document clustering algorithm using semantic similarity(WDCSS)is presented in this paper.Firstly,the minimal spanning tree is obtained from the similarity of document key words.Secondly,the smallest similarity threshold is determined based on the analysis of probability and statistics.Finally,the minimal spanning tree is cut.Simultaneously,the subclasses are divided and merged.The experiment indicates that the WDCSS can not only accurately analyze the reasonable clusters and the exceptionaI samples from data sets with different cluster shapes,but it can also avoid the decreasing of the clustering quality influenced by the choice of users'parameters. |
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| Keywords: | Web document clustering semantic similarity clustering algorithm minimal spanning tree |
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