An Ontology-based HIV/AIDS FAQ Retrieval System

Abstract

This paper presents a discussion of the implementation of an ontology-based HIV/AIDS Frequently Asked Question (FAQ) retrieval system. The main purpose of the system is to provide an answer from an existing HIV/AIDS FAQ repository for any question on HIV/AIDS asked by any person. As the identification of the best possible answer requires the understanding of the semantics of both the question and the existing question-answer pairs in the FAQ, the use of ontology is very crucial. Ontologies have been widely used in natural language processing applications especially in Question Answering Systems. The ontology for the HIV/AIDS FAQ retrieval system has been built using Text2Onto tool which has been experimentally evaluated to be the most appropriate tool as reported in our earlier work. Once the ontology is constructed, the next challenge is to make sure that the use of the domain ontology improves the performance of the FAQ retrieval System. For this purpose, we explored a number of approaches for computing semantic similarity between a user query and the existing question-answer pairs in the FAQ. Semantic similarity is computed based on inherent relationships between concepts using ontologies. Specifically, we use the semantic similarity metrics proposed by Thiagarajan et al. based on spreading activation networks (set based spreading). The results show an improvement in accuracy compared to the traditional information retrieval based question answering systems approaches.