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基于社会标签的文本聚类研究 被引量:8

Research on Text Clustering Based on Social Tagging
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摘要 以社会标签在网络资源聚类中的作用为研究目标,筛选标注资源的社会标签作为特征项,采用K-means聚类算法对文本资源进行聚类,并在小规模测试集上得到较好效果。详细讨论基于社会标签的文本聚类中标签筛选、聚类方法等关键技术的实现过程。通过实验证明:基于社会标签的文本聚类是一种较传统关键词进行聚类更为有效的一种聚类方法,能够提高文本聚类的效果。 In this paper, the authors select social tags which are used to annotate resources as feature items. Text clustering is implemented by K - means, a kind of clustering algorithm, and successfully conducted on small data set. The implementation of primary technology, such as tag filtering, clustering algorithm, in text clustering based on social tagging isdiscussed in details. By the experiment, it is concluded that text clustering based on social tags performs better than keywords, which can improve the clustering results.
作者 何文静 何琳
出处 《现代图书情报技术》 CSSCI 北大核心 2013年第7期49-54,共6页 New Technology of Library and Information Service
基金 江苏省社会科学基金"社会化网络资源的组织模式和管理策略研究"(项目编号:12TQC014) 南京农业大学SRT计划"基于社会标签的Folksonomy的技术改造"(项目编号:1219A09)的研究成果之一
关键词 社会标签 特征选择 聚类方法 文本聚类 Social tag Feature selection Clustering algorithm Text clustering
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参考文献12

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