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IPHITS: An Incremental Latent Topic Model for Link Structure

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Information Retrieval Technology (AIRS 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5839))

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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.

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Author information

Authors and Affiliations

  1. Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, 100190, Beijing, China

    Huifang Ma, Weizhong Zhao, Zhixin Li & Zhongzhi Shi

  2. Graduate University of the Chinese Academy of Sciences, 100049, Beijing, China

    Huifang Ma, Weizhong Zhao, Zhixin Li & Zhongzhi Shi

Authors
  1. Huifang Ma
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  2. Weizhong Zhao
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  3. Zhixin Li
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  4. Zhongzhi Shi
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, Pohang University of Science and Technology, San 31, Hyoja-dong, Nam-gu, 790-784, Pohang, Korea

    Gary Geunbae Lee

  2. School of Computing, The Robert Gordon University, St Andrew Street, AB25 1HG, Aberdeen, UK

    Dawei Song

  3. Microsoft Reseach Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Chin-Yew Lin

  4. National Institute of Informatics, 2-1-2 Hitotsubashi, Chiyoda-ku, 101-8430, Tokyo, Japan

    Akiko Aizawa

  5. School of Literature, Shirayuri College, 1-25 Midorigaoka, Chofu-shi, 182-8525, Tokyo, Japan

    Kazuko Kuriyama

  6. Graduate School of Information Science and Technology, Hokkaido University, North 14 West 9, Kita-ku. Sapporo-shi, 060-0814, Hokkaido, Japan

    Masaharu Yoshioka

  7. Microsoft Research Asia, 5F Beijing Sigma Center, 49 Zhichun Road, Haidian District, 100190, Beijing, P.R. China

    Tetsuya Sakai

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Ma, H., Zhao, W., Li, Z., Shi, Z. (2009). IPHITS: An Incremental Latent Topic Model for Link Structure. In: Lee, G.G., et al. Information Retrieval Technology. AIRS 2009. Lecture Notes in Computer Science, vol 5839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04769-5_21

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  • DOI: https://doi.org/10.1007/978-3-642-04769-5_21

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04768-8

  • Online ISBN: 978-3-642-04769-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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