Natural Language Processing techniques for text-mining and information retrieval are finding application in the analysis of many kinds of documentation, from technical documentation to World Wide Web. Particularly, Functional Analysis techniques are based on the extraction of the interactions between the entities described in the document: these interactions are expressed as Subject-Action-Object (SAO) triples (obtainable using a suitable syntactic parser) which represent a concept in its most synthesizing form. In this work, the techniques developed for a functional analysis of patents and their implementation in the PAT-Analyzer tool are presented. The same technique has been properly tailored and applied to the analysis of software requirements documents. Current work in the direction of the development of a SAO-based Content Analysis of technical documentation is presented. © Springer-Verlag 2004.

Natural language processing of patents and technical documentation

CASCINI, GAETANO;
2004-01-01

Abstract

Natural Language Processing techniques for text-mining and information retrieval are finding application in the analysis of many kinds of documentation, from technical documentation to World Wide Web. Particularly, Functional Analysis techniques are based on the extraction of the interactions between the entities described in the document: these interactions are expressed as Subject-Action-Object (SAO) triples (obtainable using a suitable syntactic parser) which represent a concept in its most synthesizing form. In this work, the techniques developed for a functional analysis of patents and their implementation in the PAT-Analyzer tool are presented. The same technique has been properly tailored and applied to the analysis of software requirements documents. Current work in the direction of the development of a SAO-based Content Analysis of technical documentation is presented. © Springer-Verlag 2004.
2004
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Computer Science (all); Biochemistry, Genetics and Molecular Biology (all); Theoretical Computer Science
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1023613
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