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The diversity of health information seekers signifies the enormous variety of information needs by numerous users. The existing health information retrieval systems failed to address the information needs of both medical expert and laymen patients. This study focused on designing an enhanced information retrieval approach using the concept based approach that would address the information needs of both medical experts and laymen patients. We evaluated and compared the performance of the proposed enhanced concept based approach with the existing approaches namely: concept based approach (CBA), query likelihood model (QLM) and latent semantic indexing (LSI) approach using Diagnosia 7, Medical Subject Heading (MeSH), Khresmoi Project 6 and Genetic Home Reference datasets. The experimental results obtained shows that the proposed enhanced concept based approach manage to score similarity scores of 1.0 (100%) in respect to maxSim values for all the runs in all the four datasets and idf weighting values of between 3.82 – 3.86 for all the runs in all the four datasets. While the existing approaches (CBA, QLM, LSI) scored the maxSim scores of 0.5 (50%) for all their runs in all the four dataset and idf weighting values of between 1.40 – 1.47 for all the four dataset, as a result of their inability to generate and display medical search results in both medical experts and layman’s forms. These results shows that the proposed enhanced concept based approach is the best approach suited to be used in addressing presentation issues.

An Enhanced Concept based Approach for User Centered Health Information Retrieval to Address Presentation Issues