Question Answering System
Abstract: Question answering systems have become increasingly popular because they deliver users short; succinct answers instead of overloading them with a large number of irrelevant documents. Question Answering (QA) is a specialized form of information retrieval. Given a collection of documents; a Question Answering system attempts to retrieve the right answers to questions posed in natural language. In order for question answering systems to benefit from this vast store of useful knowledge; they must copy with large volumes of useless data. Question Answering systems (QA) uses natural language processing (NLP) techniques to process a question; then searches for the required information to identify the answer and presents the answer to the user. The Web is vastly larger in size and boasts incredible data redundancy; which renders it amenable to statistical techniques for answer extraction. The data-driven approach can yield high levels of performance and nicely complements traditional question answering techniques driven by information extraction. By organizing these resources and annotating them with natural language; we can successfully incorporate Web knowledge into question answering.
Keywords: Question answering system, Classification, Information retrieval, Answer extraction Information retrieval, databases, crawler, Tokens, Seed URL
How to Cite?: Shekhar Nalawade, Shivraj Kumar, Deepak Tiwari, "Question Answering System", Volume 3 Issue 5, May 2014, International Journal of Science and Research (IJSR), Pages: 439-440, https://www.ijsr.net/getabstract.php?paperid=20131762, DOI: https://dx.doi.org/10.21275/20131762