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一种改进的web文档关键词权重计算方法
引用本文:孙双,贺樑,杨静,顾君忠. 一种改进的web文档关键词权重计算方法[J]. 上海大学学报(英文版), 2008, 12(3): 235-239. DOI: 10.1007/s 11741-008-0309-2
作者姓名:孙双  贺樑  杨静  顾君忠
作者单位:SUN Shuang(Institute of Computer Applications, East China Normal University, Shanghai 200062, P. R. China) HE Liang(Institute of Computer Applications, East China Normal University, Shanghai 200062, P. R. China) YANG Jing(Institute of Computer Applications, East China Normal University, Shanghai 200062, P. R. China) GU Jun-zhong(Institute of Computer Applications, East China Normal University, Shanghai 200062, P. R. China)
摘    要:

关 键 词:improved vector space model (IVSM)  representation feature  feature item  keyword weight  semantic similarity  改进  文档  关键词  权重  计算方法  keywords  weighting  semantic similarity  results  accuracy  time  performance  features  item  selection  calculation  Four  experiments  real system  improved algorithm
收稿时间:2007-06-22
修稿时间:2007-06-22

An improved algorithm for weighting keywords in web documents
Shuang Sun,Liang He,Jing Yang,Jun-zhong Gu. An improved algorithm for weighting keywords in web documents[J]. Journal of Shanghai University(English Edition), 2008, 12(3): 235-239. DOI: 10.1007/s 11741-008-0309-2
Authors:Shuang Sun  Liang He  Jing Yang  Jun-zhong Gu
Affiliation:Institute of Computer Applications, East China Normal University, Shanghai 200062, P. R. China
Abstract: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.
Keywords:improved vector space model (IVSM)   representation feature   feature item   keyword weight   semantic similarity
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