Retrieving terms and their variants in a lexicalized unification-based framework

Abstract

Term extraction is a major concern for information retrieval. Terms are not fixed forms and their variations prevent them from being identified by a match with their initial string or inflection. We show that a local syntactic approach to this problem can give good results for both the quality of identification and parsing time. A specific tool, FASTR, is developed which handles an identification of basic terms and a parser of their variations as well. Terms are described by logic rules automatically generated from terms and their categorial structure. Variations are represented by metarules. The parser efficiently processes large size corpora with big dictionaries and mixes lexical identification with local syntactic analysis. We evaluate the accuracy of results produced by these metarules and improve these results with filtering metarules.