Question-driven information retrieval systems

An approach is presented to building question-driven information retrieval systems to answer natural language questions from collections of free-text question-answer pairs.; The question-answering task is conceptualized as the retrieval of answers to questions similar to a submitted question. Similarity decisions are made by combining numerical techniques of information retrieval with scalable, knowledge- based approaches of natural language processing. Answer retrieval is based on the identification of terms' content-bearing capacities from the sequential structure of free text and the recognition of critical semantic relations among terms through a general-purpose semantic network.; An approach is outlined for embedding question-driven information retrieval systems into information sources such as organizations. A question-driven information retrieval system is embedded in a source when it has some knowledge of the source's structure and relies on it to answer questions submitted to the source. Feedback from the source is solicited and utilized after retrieval failures. New answers produced by the source are indexed for reuse under the questions that initiated their production.; These ideas are implemented in two question-driven information retrieval systems, FAQ Finder and the Chicago Information Exchange (CIE). FAQ Finder answers questions from a collection of Usenet files of frequently asked questions. CIE is embedded into the University of Chicago's Computer Science Department to answer questions on certain topics of computer science.