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Using Link-Based Content Analysis to Measure Document Similarity Effectively

  • Pei Li
  • Zhixu Li
  • Hongyan Liu
  • Jun He
  • Xiaoyong Du
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5446)

Abstract

Along with a massive amount of information being placed online, it is a challenge to exploit the internal and external information of documents when assessing similarity between them. A variety of approaches have been proposed to model the document similarity based on different foundations, but usually they are not applicable for combining internal and external information. In this paper, we introduce a link-based method into content analysis, which is based on random walk on graphs. By defining similarity as the meeting probability of two random surfers, we propose a computational model for content analysis, which can also be integrated with external information of documents. Empirical study shows that our method achieves good accuracy, acceptable performance and fast convergent rate in multi-relational document similarity measuring.

Keywords

link graph content analysis document similarity 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Pei Li
    • 1
    • 2
  • Zhixu Li
    • 1
    • 2
  • Hongyan Liu
    • 3
  • Jun He
    • 1
    • 2
  • Xiaoyong Du
    • 1
    • 2
  1. 1.Key Labs of Data Engineering and Knowledge EngineeringMinistry of EducationChina
  2. 2.School of InformationRenmin University of ChinaBeijingChina
  3. 3.Department of Management Science and EngineeringTsinghua UniversityBeijingChina

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