Аннотация:This technical report describes FAQ Finder, a natural language question answering system that uses files of frequently asked questions as its knowledge base. Unlike AI question-answering systems that focus on the generation of new answers, FAQ Finder retrieves existing ones found in frequently-asked question files. Unlike information retrieval approaches that rely on a purely lexical metric of similarity between query and document, FAQ Finder uses a semantic knowledge base (WordNet) to improve its ability to match question and answer. We describe the design and the current implementation of the system and its support components, including results from an evaluation of the system''s performance against a corpus of user questions. An important finding was that a combination of semantic and statistical techniques works better than any single approach. We analyze failures of the system and discuss future research aimed at addressing them.
