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A Normalized Framework Based on Multiple Relationships for Document Re-ranking

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Information Retrieval (CCIR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10390))

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Abstract

Document re-ranking has been widely adopted in Information Retrieval as a way of improving precision of top documents based on the first round retrieval results. There are methods that use semi-supervised learning based on graphs constructed based on similarities between documents. However, most of them only consider relationships between documents. In this paper, we propose an approach to take the relationships between documents, between words in documents, as well as between documents and words into consideration. We develop a novel generative model which integrates neural language model with latent semantic model, then we incorporate the relationships between documents and words into a normalized framework to re-rank documents based on the initial retrieval results. Experimental results show that the method show significant improvements in comparison with other baseline methods.

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Notes

  1. 1.

    http://www.google.com.

  2. 2.

    http://www.clef-campaign.org.

  3. 3.

    http://www.terrier.org.

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Acknowledgement

The work described in this paper was supported by National Natural Science Foundation of China under Project No. 61300129, Scientific Research Fund of Hunan Provincial Education Department of China under Project No. 16K030, Hunan Provincial Natural Science Foundation of China under Project No. 2017JJ2101, Hunan Provincial Innovation Foundation For Postgraduate under Project No. CX2016B575.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Hunan University of Science and Technology, Xiangtan, 411201, Hunan, China

    Wenyu Zhao & Dong Zhou

Authors
  1. Wenyu Zhao
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  2. Dong Zhou
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Corresponding author

Correspondence to Dong Zhou .

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Editors and Affiliations

  1. Renmin University, Beijing, China

    Jirong Wen

  2. Université de Montréal, Montreal, Canada

    Jianyun Nie

  3. East China University of Science and Technology, Shanghai, China

    Tong Ruan

  4. Tsinghua University, Beijing, China

    Yiqun Liu

  5. Wuhan University, Wuhan, Hubei, China

    Tieyun Qian

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Zhao, W., Zhou, D. (2017). A Normalized Framework Based on Multiple Relationships for Document Re-ranking. In: Wen, J., Nie, J., Ruan, T., Liu, Y., Qian, T. (eds) Information Retrieval. CCIR 2017. Lecture Notes in Computer Science(), vol 10390. Springer, Cham. https://doi.org/10.1007/978-3-319-68699-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-68699-8_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68698-1

  • Online ISBN: 978-3-319-68699-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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