Indexing of Semantic Web for Efficient Question Answering System

Abstract

Search engine is a program that performs a search in the documents for finding out the response to the user’s query in form of keywords. It then provides a list of web pages comprising of those keywords. Search engines cannot differentiate between the variable documents and spams. Some search engine crawler retrieves only document title not the entire text in the document. The major objective of Question Answering system is to develop techniques that not only retrieve documents, but also provide exact answers to natural language questions. Many Question Answering systems developed are able to carry out the processing needed for attaining higher accuracy levels. However, there is no major progress on techniques for quickly finding exact answers. Existing Question Answering system is unable to handle variety of questions and reasoning-based question. In case of absence of data sources, QA system fails to answer the query. This paper investigates a novel technique for indexing the semantic Web for efficient Question Answering system. Proposed techniques include manual constructed question classifier based on <Subject, Predicate, Object>, retrieval of documents specifically for Question Answering, semantic type answer extraction, answer extraction via manually constructed index for every category of Question.