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Metadata-Based Automatic Query Suggestion in Digital Library Using Pattern Mining

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Digital Libraries at the Crossroads of Digital Information for the Future (ICADL 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11853))

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Abstract

This paper presents a Query Auto-Completion (QAC) framework that aims at assisting users in a digital library to specify their search intent with reduced effort. The proposed system suggests metadata-based facets to users as they specify their queries into the system. In this work, we model the facet-based QAC problem as frequent pattern mining problem where the system aims at leveraging association among different facet combinations. Among several frequent pattern mining algorithms, the present work make use of FP-Growth to discover facet patterns at large-scale. These facet patterns represented in form of association rules are used for online query auto-completion or suggestion. A prototype QAC augmented digital library search system is implemented by considering a limited bibliographic dataset (35K resources) of the National Digital Library of India (NDLI: https://ndl.iitkgp.ac.in) portal. We perform extensive experiments to measure the quality of query suggestions and QAC augmented retrieval performance. Significant improvement over baseline search system is observed in both the aspects mentioned above.

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Notes

  1. 1.

    http://lucene.apache.org/solr/.

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Acknowledgement

This work is supported by IBM Research through Shared University Research grant and Ministry of Human Resource Development, Government of India the National Digital Library of India project.

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Authors and Affiliations

  1. Indian Institute of Technology, Kharagpur, 721302, India

    Susmita Sadhu & Plaban Kumar Bhowmick

Authors
  1. Susmita Sadhu
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  2. Plaban Kumar Bhowmick
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Corresponding authors

Correspondence to Susmita Sadhu or Plaban Kumar Bhowmick .

Editor information

Editors and Affiliations

  1. Kyoto University, Kyoto, Japan

    Adam Jatowt

  2. Ritsumeikan University, Kusatsu, Japan

    Akira Maeda

  3. The Catholic University of America, Washington, DC, USA

    Sue Yeon Syn

Appendix: List of Tasks for Assessment

Appendix: List of Tasks for Assessment

Table 1. List of ten search tasks used in evaluation
Full size table

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Sadhu, S., Bhowmick, P.K. (2019). Metadata-Based Automatic Query Suggestion in Digital Library Using Pattern Mining. In: Jatowt, A., Maeda, A., Syn, S. (eds) Digital Libraries at the Crossroads of Digital Information for the Future. ICADL 2019. Lecture Notes in Computer Science(), vol 11853. Springer, Cham. https://doi.org/10.1007/978-3-030-34058-2_20

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  • DOI: https://doi.org/10.1007/978-3-030-34058-2_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34057-5

  • Online ISBN: 978-3-030-34058-2

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