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Feedback Model for Microblog Retrieval

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Book cover Database Systems for Advanced Applications (DASFAA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9049))

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Abstract

Information searching in microblog services has become common and necessary for social networking. However, microblog retrieval is particularly challenging compared to web page retrieval because of serious vocabulary mismatch problem and non-uniform temporal distribution of relevant documents. In this paper, we propose a feedback model, which includes a feedback language model and a query expansion model considering both lexical expansions and temporal expansions. Experiments on TREC data sets have shown that our proposed model improves search effectiveness over standard baselines, lexical only expansion model and temporal only retrieval model.

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Author information

Authors and Affiliations

  1. School of EECS, Peking University, Beijing, 100871, China

    Ziqi Wang & Ming Zhang

Authors
  1. Ziqi Wang
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  2. Ming Zhang
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Corresponding author

Correspondence to Ming Zhang .

Editor information

Editors and Affiliations

  1. Universität München, München, Germany

    Matthias Renz

  2. University of Southern California, Los Angeles, USA

    Cyrus Shahabi

  3. University of Queensland, Brisbane, Australia

    Xiaofang Zhou

  4. Monash University, Clayton, Australia

    Muhammad Aamir Cheema

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Wang, Z., Zhang, M. (2015). Feedback Model for Microblog Retrieval. In: Renz, M., Shahabi, C., Zhou, X., Cheema, M. (eds) Database Systems for Advanced Applications. DASFAA 2015. Lecture Notes in Computer Science(), vol 9049. Springer, Cham. https://doi.org/10.1007/978-3-319-18120-2_31

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  • DOI: https://doi.org/10.1007/978-3-319-18120-2_31

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18119-6

  • Online ISBN: 978-3-319-18120-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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