Date of Award

12-2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Engineering and Sciences

First Advisor

Barry Webster

Second Advisor

Luis Daniel Otero

Third Advisor

William Arrasmith

Fourth Advisor

Munevver Subasi

Abstract

In this era of information explosion, people generally rely on the Internet, and more precisely, the search engines to get answers to their questions. However, what a search engine can do is just retrieve documents. Given some keywords, it only returns the relevant ranked documents that contain the keywords. Although users often want a precise answer to a question, they are left to extract answers from the documents themselves. This is where Automatic Question Answering (AQA) systems come into play. An AQA system takes questions in natural language as input and searches related answers in the set of documents and extracts the precise answer to natural language questions rather than retrieving full documents or best matching passages, as most information retrieval systems currently do. In this work, an AQA system has been developed that can provide precise answers to any general-purpose questions. This paper provides a novel and efficient framework to find proper results for the user based on the question.

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