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An improved algorithm for weighting keywords in web documents 被引量：1

An improved algorithm for weighting keywords in web documents
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摘要 In this paper, an improved algorithm, web-based keyword weight algorithm （WKWA）, is presented to weight keywords in web documents. WKWA takes into account representation features of web documents and advantages of the TF＊IDF, TFC and ITC algorithms in order to make it more appropriate for web documents. Meanwhile, the presented algorithm is applied to improved vector space model （IVSM）. A real system has been implemented for calculating semantic similarities of web documents. Four experiments have been carried out. They are keyword weight calculation, feature item selection, semantic similarity calculation, and WKWA time performance. The results demonstrate accuracy of keyword weight, and semantic similarity is improved. In this paper, an improved algorithm, web-based keyword weight algorithm （WKWA）, is presented to weight keywords in web documents. WKWA takes into account representation features of web documents and advantages of the TF＊IDF, TFC and ITC algorithms in order to make it more appropriate for web documents. Meanwhile, the presented algorithm is applied to improved vector space model （IVSM）. A real system has been implemented for calculating semantic similarities of web documents. Four experiments have been carried out. They are keyword weight calculation, feature item selection, semantic similarity calculation, and WKWA time performance. The results demonstrate accuracy of keyword weight, and semantic similarity is improved.
作者 孙双 贺樑 杨静 顾君忠
机构地区 Institute of Computer Applications
出处 《Journal of Shanghai University(English Edition)》 CAS 2008年第3期235-239,共5页 上海大学学报（英文版）
基金 Project supported by the Science Foundation of Shanghai Municipal Commission of Science and Technology （Grant No.055115001）
关键词 improved vector space model （IVSM） representation feature feature item keyword weight semantic similarity improved vector space model （IVSM）, representation feature, feature item, keyword weight, semantic similarity
分类号 TP3 [自动化与计算机技术—计算机科学与技术]
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参考文献9

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二级参考文献22

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Journal of Shanghai University(English Edition)
2008年 第3期

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