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Topic PageRank——一种基于主题的搜索引擎 被引量:8

Topic PageRank:a Search Engine Based on Topic
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摘要 通过研究传统的超链分析算法PageRank及其改进算法Hilltop和TSPR的不足,提出了一种新的改进的方法Topic PageRank。这种算法是对每一个页面进行页面分类,然后根据分类的结果分别对每一个主题进行页面等级计算,因此,每一个页面对不同的主题将呈现出不同的页面等级得分,能更加准确地反映出页面的重要性。 To research the shortcomings of the PageRank technique and the improved algorithms, Hilltop and TSPR, which is the traditional algorithm based on analyzing the hyperlinks, this paper brings up a new approach, the Topic PageRank. The new algorithm classifles all of the pages, and then calculates the page ranks about the different topics. Therefore, every page will have some different page ranks about the different topics, and this page ranks can reflect the importance of the pages.
出处 《计算机技术与发展》 2007年第5期238-241,共4页 Computer Technology and Development
关键词 PAGERANK Hilltop TSPR TOPIC PageRank页面分类 PageRank Hilltop TSPR Topic PageRank pages classification
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参考文献5

  • 1宋聚平,王永成,尹中航,滕伟.对网页PageRank算法的改进[J].上海交通大学学报,2003,37(3):397-400. 被引量:40
  • 2Bharat K,Mihaila G A.Hilltop:A Search Engine based on Expert Documents[DB/OL].2000-10[2006-06].http://www.cs.toronto.edu/georgem/hilltop,2000-10/.
  • 3Haveliwala T H.Topic-Sensitive PageRank[DB/OL].2002-02[2006-06].http://net.pku.edu.cn/wbia/2004/public-html/Readings/mining/Topic-Sensitive% 20PageRank.pdf.
  • 4马辉民,李卫华,吴良元.VSM在中文文本聚类中的应用及实证分析[J].武汉理工大学学报(信息与管理工程版),2006,28(4):56-59. 被引量:13
  • 5Brin S,Page L.The anatomy of a large-scale hypertextual web search engine[DB/OL].1998-07[2006-06].http://www-db.stanford.edu/%7Ebackrub/google.html.

二级参考文献13

  • 1鲁松 白硕 等.文本中词语权重计算方法的改进[A]..2000 International Conference on Multilingual Information Processing[C].,2000.31-36.
  • 2Freeman R T,Yin H J.Tree View Self-organisation of Web Content[J].Neurocomputing,2005(63):415-446.
  • 3Salton G,Wong A,Yang C S.A Vector Space Model for Automatic Indexing[J].Communications of the ACM,1975 (18):613-620.
  • 4Mao W L,Chu W W.Free-text Medical Document Retrieval via Phrase-based Vector Space Model[A].Proceedings of AMIA Annual Symposium[C].2002.46-51.
  • 5Jiang F,Littman M L.Approximate Dimension Equalization in Vector-based Information Retrieval[A].Proceedings of the Seventeenth International Conference on Machine Learning[C].2000.98-104.
  • 6Oren Zamir, Oren Etzioni. Grouper: a dynamic clustering interface to Web search results [J]. Computer Networks, 1999, 31:58-63.
  • 7Brin S, Page L. The anatomy of a large-scale hypertextual Web-search engine [A]. Proc 7th International World Wide Web Conference[C]. Brisbane:SIGIR, 1998. 146-164.
  • 8Jughoo Cho, Hector G M, Lawrence P. Efficient crawling through URL ordering[A]. Proc 7th International World Wide Web Conference[C]. Brisbane:SIGIR, 1998. 220-235.
  • 9DeBra P, Post R. Information retrieval in the World-Wide Web: making client-based searching feasible[A]. Proc 1st Internatonal World Wide Web Conference[C]. Geneva: CERN, 1994. 45-55.
  • 10Hersovici M, Jacovi M, Maarek Y, et al. The shark-search algorithm-an application: tailored Web site mapping[J]. Computer Networks and ISDN System, 1998, 30:256-264.

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