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.
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.
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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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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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