Indian Journal of Science and Technology

Abstract

Background/Objectives: The proposed frame work uses statistical based similarity measure for QAS, which gives short and exact answer to user query. The entire frame work is focusing similarity computation between question and answer pair. Methods/Statistical Analysis: The involvement of similarity computation between question and answer pair should be investigated in this work QAS. Statistical based similarity measure is an important issue as compared to similarity computation in many fields such as, Natural Language Processing, Information Retrieval, Ontology Mapping, Knowledge Acquisition and Question Answering System. Semantic web has been used to present the structure knowledge representation between questions and answer keywords. Ontology can be used as important proposal to enable semantic similarity between keywords present in the question and answer pairs. Findings: The proposed frame work investigate, how the statistical based similarity measure used in these system helps to improve the performance of the QA system for all Wh-questions. We find the keywords having most similar meaning will return the answer as the final answer. The best performance is achieved by extracting the relevant snippets information form Google search engine. The performance of the system will change as the retrieval of the document is increases beyond 15; this could indicate that restriction in the retrieval of document is helps to optimize the performance of the system. Application/Improvements: This frame work is applicable to all type of search engines which helps to finds most relevant answer to user questions. In future, we implement our frame work for questions having more than five keywords.
Keywords: Information Retrieval, Ontology, Question Answering System, Semantic Similarity.