Abstract
Medical information is a natural human demand. 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. Under-specified queries often lead to undesirable search results that do not contain the information needed. 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
This journal version was previously published at the International Conference on Information Science and Applications (ICISA 2011) [11] and the main differences from previous work to this are: (i) enhancement of related work by including new comparative studies, (ii) extension of evaluation by comparing our results against state-of-the-art approaches and (iii) execution of an efficiency assessment to demonstrate the retrieval latency when tag neighbors are considered.
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Acknowledgements
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. et al. Expanding user’s query with tag-neighbors for effective medical information retrieval. Multimed Tools Appl 71, 905–929 (2014). https://doi.org/10.1007/s11042-012-1316-5
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DOI: https://doi.org/10.1007/s11042-012-1316-5