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Medical Information Retrieval Enhanced with User’s Query Expanded with Tag-Neighbors

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Abstract

Under-specified queries often lead to undesirable search results that do not contain the information needed. This problem gets worse when it comes to medical information, a natural human demand everywhere. Existing search engines on the Web often are unable to handle medical search well because they do not consider its special requirements. Often a medical information searcher is uncertain about his exact questions and unfamiliar with medical terminology. To overcome the limitations of under-specified queries, we utilize tags to enhance information retrieval capabilities by expanding users’ original queries with context-relevant information. We compute a set of significant tag neighbor candidates based on the neighbor frequency and weight, and utilize the qualified tag neighbors to expand an entry query. The proposed approach is evaluated by using MedWorm medical article collection and results show considerable precision improvements over state-of-the-art approaches.

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Notes

  1. 1.

    This journal version was previously published at the International Conference on Information Science and Applications (ICISA 2011) [12] and the main differences from previous work to this are: (i) enhancement of related work by including new comparative studies and (ii) extension of evaluation by comparing our results against state-of-the-art approaches.

  2. 2.

    http://www.nlm.nih.gov/mesh/trees.html

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Acknowledgments

This work has been partially supported by FP7 ICT project M-Eco: Medical Ecosystem Personalized Event-Based Surveillance under grant number 247829. This journal is a extended version of previously published paper at the International Conference on Information Science and Applications (ICISA 2011).

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Authors and Affiliations

  1. IWIS- Intelligent Web and Information Systems, Aalborg University, Computer Science Department, Room 2.2.05, Selma Lagerlöfs Vej 300, DK-9220 , Aalborg-East, Denmark

    Frederico Durao, Peter Dolog & Ricardo Lage

  2. CBS - Center for Biological Sequence Analysis, Technical University of Denmark, Department of Systems Biology, Building 208, Room 020, DK-2800 , Kongens Lyngby, Denmark

    Karunakar Bayyapu

  3. Center for Applied Informatics, Victoria University, PO Box 14428, Melbourne, VIC 8001, Australia

    Guandong Xu

Authors
  1. Frederico Durao
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  2. Karunakar Bayyapu
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  3. Guandong Xu
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  4. Peter Dolog
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  5. Ricardo Lage
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Corresponding author

Correspondence to Frederico Durao .

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Editors and Affiliations

  1. Florida Atlantic University Dept. of Computer Science & Engineering, Boca Raton, Florida, USA

    Borko Furht

  2. Department of Computer Science and Engineering, Florida Atlantic University, Boca Raton, Florida, USA

    Ankur Agarwal

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Durao, F., Bayyapu, K., Xu, G., Dolog, P., Lage, R. (2013). Medical Information Retrieval Enhanced with User’s Query Expanded with Tag-Neighbors. In: Furht, B., Agarwal, A. (eds) Handbook of Medical and Healthcare Technologies. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8495-0_2

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  • DOI: https://doi.org/10.1007/978-1-4614-8495-0_2

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  • Online ISBN: 978-1-4614-8495-0

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