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

  • Frederico Durao
  • Karunakar Bayyapu
  • Guandong Xu
  • Peter Dolog
  • Ricardo Lage
Chapter

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.

Keywords

Search Engine Information Retrieval Query Term Query Expansion Mean Average Precision 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

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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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Frederico Durao
    • 1
  • Karunakar Bayyapu
    • 2
  • Guandong Xu
    • 3
  • Peter Dolog
    • 1
  • Ricardo Lage
    • 1
  1. 1.IWIS- Intelligent Web and Information SystemsAalborg University, Computer Science DepartmentAalborg-EastDenmark
  2. 2.CBS - Center for Biological Sequence AnalysisTechnical University of Denmark, Department of Systems BiologyKongens LyngbyDenmark
  3. 3.Center for Applied InformaticsVictoria UniversityMelbourneAustralia

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