Knowledge-Based Information Retrieval From Semi-Structured Text

This paper 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) and natural language processing techniques to improve its ability to match question and answer. We describe an evaluation of the system's performance against a corpus of user questions, and show that a combination of techniques from information retrieval and natural language processing works better than any single approach. Introduction In the vast information space of the Internet, individuals and small groups have created small pockets of order, organized around their particular interests and hobbies. For the most..