Authors: Ilyes Khennak Habiba Drias
Publish Date: 2017/01/04
Volume: 41, Issue: 2, Pages: 34-
Abstract
With the increasing amount of medical data available on the Web looking for health information has become one of the most widely searched topics on the Internet Patients and people of several backgrounds are now using Web search engines to acquire medical information including information about a specific disease medical treatment or professional advice Nonetheless due to a lack of medical knowledge many laypeople have difficulties in forming appropriate queries to articulate their inquiries which deem their search queries to be imprecise due the use of unclear keywords The use of these ambiguous and vague queries to describe the patients’ needs has resulted in a failure of Web search engines to retrieve accurate and relevant information One of the most natural and promising method to overcome this drawback is Query Expansion In this paper an original approach based on Bat Algorithm is proposed to improve the retrieval effectiveness of query expansion in medical field In contrast to the existing literature the proposed approach uses Bat Algorithm to find the best expanded query among a set of expanded query candidates while maintaining low computational complexity Moreover this new approach allows the determination of the length of the expanded query empirically Numerical results on MEDLINE the online medical information database show that the proposed approach is more effective and efficient compared to the baseline
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