| 基于社团结构的文本聚类算法研究 |
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| 引用本文： | 马力,张娟. 基于社团结构的文本聚类算法研究[J]. 西安邮电学院学报, 2013, 18(2): 111-115 |
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| 作者姓名： | 马力 张娟 |
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| 作者单位： | 1. 西安邮电大学信息中心,陕西西安,710121
2. 西安邮电大学计算机学院,陕西西安,710121 |
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| 摘 要： | 为了提高文本聚类的有效性,提出一种基于网络社团结构的文本聚类算法。基于语义知识库理论,利用文本集与词语间的关系,引入文本相似度概念,再结合Newman社团聚类算法特性,将文本集作为独立社团,用文本相似度表示社团联系的紧密程度,对网络文本进行聚类。实验结果表明,该方法有效可行。
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| 关 键 词： | 社团结构 Newman算法 文本相似度 文本聚类 |
Text clustering algorithm based on community structure |
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| MA Li , ZHANG Juan. Text clustering algorithm based on community structure[J]. Journal of Xi'an Institute of Posts and Telecommunications, 2013, 18(2): 111-115 |
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| Authors: | MA Li ZHANG Juan |
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| Affiliation: | 1. Information Center, Xi＇ an University of Posts and Telecommunications, Xi＇ an 710121, China School of Computer Science and Technology, Xi＇an University of Posts and Telecommunications, Xi＇an 710121, China) |
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| Abstract: | In order to improve the effectiveness of text clustering, a text clustering algorithm based on community structure was proposed in the paper. According to the relationship between text and word, text similarity was introduced based on the theory of semantic knowledge. Text was then regarded as independent community based on the characteristics of Newman community clustering algorithm, and therefore text similarity can be used as the clustering degree of communities. Then the method was used to cluster texts. Experiment results showed that this method was effective and feasible. |
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| Keywords: | community structure Newman text similarity text clustering |
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