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ERIC Number: ED518476
Record Type: Non-Journal
Publication Date: 2010
Pages: 156
Abstractor: As Provided
Reference Count: 0
ISBN: ISBN-978-1-1240-9911-8
ISSN: N/A
Design of a Low-Cost Adaptive Question Answering System for Closed Domain Factoid Queries
Toh, Huey Ling
ProQuest LLC, Ph.D. Dissertation, The Florida State University
Closed domain question answering (QA) systems achieve precision and recall at the cost of complex language processing techniques to parse the answer corpus. We propose a "query-based" model for indexing answers in a closed domain factoid QA system. Further, we use a phrase term inference method for improving the ranking order of related questions. We posit that a query can be used as the unique identifier of an answer, and thus, the recognition of a query allows us to retrieve the correct answer. In instances where a query is unrecognized, we infer synonymous relationships with other queries through the use of a user feedback loop to improve the ranking order of closely related questions, where possible. The goal of this research is to build a prototype as proof-of-concept that will learn domain-specific knowledge with increased usage through time. This study will focus its efforts in researching the feasibility of a lightweight QA learning system that adapts its responses based on the interaction amongst its users. This offers a lightweight approach to a factoid question answering system for domain specific knowledge bases with significantly simplified language processing techniques. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A