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European Conference on Information Retrieval

ECIR 2019: Advances in Information Retrieval pp 353–368Cite as

An Experimental Study of Index Compression and DAAT Query Processing Methods

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11437))

Abstract

In the last two decades, the IR community has seen numerous advances in top-k query processing and inverted index compression techniques. While newly proposed methods are typically compared against several baselines, these evaluations are often very limited, and we feel that there is no clear overall picture on the best choices of algorithms and compression methods. In this paper, we attempt to address this issue by evaluating a number of state-of-the-art index compression methods and safe disjunctive DAAT query processing algorithms. Our goal is to understand how much index compression performance impacts overall query processing speed, how the choice of query processing algorithm depends on the compression method used, and how performance is impacted by document reordering techniques and the number of results returned, keeping in mind that current search engines typically use sets of hundreds or thousands of candidates for further reranking.

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Notes

  1. 1.

    https://github.com/ot/ds2i.

  2. 2.

    https://github.com/lemire/FastPFor.

  3. 3.

    https://github.com/andrewtrotman/JASSv2.

  4. 4.

    https://github.com/mpetri/partitioned_ef_ans.

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Acknowledgments

This research was supported by NSF Grant IIS-1718680 and a grant from Amazon.

Author information

Authors and Affiliations

  1. Computer Science and Engineering, New York University, New York, USA

    Antonio Mallia, Michał Siedlaczek & Torsten Suel

Authors
  1. Antonio Mallia
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  2. Michał Siedlaczek
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  3. Torsten Suel
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Corresponding authors

Correspondence to Antonio Mallia , Michał Siedlaczek or Torsten Suel .

Editor information

Editors and Affiliations

  1. University of Strathclyde, Glasgow, UK

    Leif Azzopardi

  2. Bauhaus Universität Weimar, Weimar, Germany

    Benno Stein

  3. Universität Duisburg-Essen, Duisburg, Germany

    Norbert Fuhr

  4. GESIS - Leibniz Institute for the Social Sciences, Cologne, Germany

    Philipp Mayr

  5. Delft University of Technology, Delft, The Netherlands

    Claudia Hauff

  6. University of Twente, Enschede, The Netherlands

    Djoerd Hiemstra

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Mallia, A., Siedlaczek, M., Suel, T. (2019). An Experimental Study of Index Compression and DAAT Query Processing Methods. In: Azzopardi, L., Stein, B., Fuhr, N., Mayr, P., Hauff, C., Hiemstra, D. (eds) Advances in Information Retrieval. ECIR 2019. Lecture Notes in Computer Science(), vol 11437. Springer, Cham. https://doi.org/10.1007/978-3-030-15712-8_23

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  • DOI: https://doi.org/10.1007/978-3-030-15712-8_23

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