Comparative Studies of Information Retrieval Approaches in User-Centered Health Information System

Abstract

In this paper, a comparative studies of different methods deployed in addressing problems of user-centered health information retrieval systems were investigated. The reason for the comparative studies is to identify the approach that best addressed the readability and vocabulary mismatched issues encountered by laymen patients and their relatives in exploring information extracted from medical discharge documents and clinical reports online. We discussed and presented the performance of information retrieval systems in previous research works. We concentrated on classifying and comparing the three approaches used in health information retrieval which are Vector Space Model (VSM), Language Based Approach Model (LM) and Context Based Approach (CBA). The usefulness of incorporating controlled vocabularies such as Metamap, UMLS, external, MeSH, etc. was extensively discussed. The result shows that the Language Based Approach systems achieved better results as compared to the Vector Space Model Approach and Context Based Approach Systems. The Language Based Approach Systems managed to acquire 0.4146, 0.7560 and 0.7445 for Mean Average Precision, Precision @ 10 and Normalized Discontinued Cumulative Gains @ 10 respectively. Hence, we conclude based on the outcome of the comparative studies and our experimental results that the language modeling models is best suited to be deployed in addressing the problems of returning relevant information by user centered health information retrievals to users.