Author: Steven
L. Lytinen, Noriko
Tomuro and Tom Repede
Journal-ref: Accepted for publication at the workshop on Artificial
Intelligence for Web Search at the 17th National Conference
on Artificial Intelligence (AAAI-2000).
FAQFinder is a Web-based, natural language question-answering system. It answers a user's question by searching the Usenet Frequently Asked Questions (FAQ) files for a similar FAQ question, and displaying its answer to the user. To find the most similar FAQ question, FAQFinder measures similarity in part by using WordNet (Miller, 1990). To increase the accuracy of the similarity metric, we have incorporated an automated WordNet sense tagger into the process. In this paper, we show that the use of this sense tagger improves FAQFinder's matching accuracy. We argue that WordNet sense tagging can also be used in more general Web search tasks.
Paper: Full paper (zip-compressed (345kb), gz-compressed (320kb))