Concept recognition in an automatic text-processing system for the life sciences

Abstract

This article describes a natural-language text-processing system designed as an automatic aid to subject indexing at BIOSIS. The intellectual procedure the system should model is a deep indexing with a controlled vocabulary of biological concepts — Concept Headings (CHs). On the average, ten CHs are assigned to each article by BIOSIS indexers. The automatic procedure consists of two stages: (1) translation of natural-language biological titles into title-semantic representations which are in the constructed formalized language of Concept Primitives, and (2) translation of the latter representations into the language of CHs. The first stage is performed by matching the titles against the system's Semantic Vocabulary (SV). The SV currently contains approximately 15,000 biological natural-language terms and their translations in the language of Concept Primitives. For the ambiguous terms, the SV contains the algorithmical rules of term disambiguation, rules based on semantic analysis of the contexts. The second stage of the automatic procedure is performed by matching the title representations against the CH definitions, formulated as Boolean search strategies in the language of Concept Primitives. Three experiments performed with the system and their results are described. The most typical problems the system encounters, the problems of lexical and situational ambiguities, are discussed. The disambiguation techniques employed are described and demonstrated in many examples. © 1987 John Wiley & Sons, Inc.