Retrieving NASA problem reports: a case study in natural language information retrieval

Authors:
Sebastian van Delden;Fernando Gomez
Affiliations:
School of Computer Science, University of Central Florida, Orlando, FL;School of Computer Science, University of Central Florida, Orlando, FL
Venue:
Data & Knowledge Engineering - NLDB2002
Year:
2004

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Abstract

A system that retrieves problem reports from a NASA database is described. The database is queried with natural language questions. Part-of-speech tags are first assigned to each word in the question using a rule-based tagger. A partial parse of the question is then produced with independent sets of deterministic finite state automata. Using partial parse information, a look up strategy searches the database for problem reports relevant to the question. A bigram stemmer and irregular verb conjugates have been incorporated into the system to improve accuracy. The system is evaluated by a set of 55 questions posed by NASA engineers. A discussion of future research is also presented.