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IPHITS: An Incremental Latent Topic Model for Link Structure

  • Huifang Ma
  • Weizhong Zhao
  • Zhixin Li
  • Zhongzhi Shi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5839)

Abstract

The structure of linked documents is dynamic and keeps on changing. Even though different methods have been proposed to exploit the link structure in identifying hubs and authorities in a set of linked documents, no existing approach can effectively deal with its changing situation. This paper explores changes in linked documents and proposes an incremental link probabilistic framework, which we call IPHITS. The model deals with online document streams in a faster, scalable way and uses a novel link updating technique that can cope with dynamic changes. Experimental results on two different sources of online information demonstrate the time saving strength of our method. Besides, we make analysis of the stable rankings under small perturbations to the linkage patterns.

Keywords

link analysis incremental learning PHITS IPHITS 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Huifang Ma
    • 1
    • 2
  • Weizhong Zhao
    • 1
    • 2
  • Zhixin Li
    • 1
    • 2
  • Zhongzhi Shi
    • 1
    • 2
  1. 1.Key Lab of Intelligent Information Processing, Institute of Computing TechnologyChinese Academy of SciencesBeijingChina
  2. 2.Graduate University of the Chinese Academy of SciencesBeijingChina

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