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Proceedings Paper

Automatic natural acquisition of a semantic network for information retrieval systems
Author(s): Chantal Enguehard; Pierre Malvache; Philippe Trigano
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Paper Abstract

The amount of information is becoming greater and greater, in industries where complex processes are performed it is becoming increasingly difficult to profit from all the documents produced when fresh knowledge becomes available (reports, experiments, findings). This situation causes a considerable and expensive waste of precious time lost searching for documents or, quite simply, results in outright repeating what has been done. One solution is to transform all paper information into computerized information. We might imagine that we are in a science-fiction world and that we have the perfect computer. We tell it everything we know, we make it read all the books, and if we ask it any question, it will find the response if that response exists. But unfortunately, we are in the real world and the last four decades have taught us to minimize our expectations of computers. During the 1960s, the information retrieval systems appeared. Their purpose is to provide access to any desired documents, in response to a question about a subject, even if it is not known to exist. Here we focus on the problem of selecting items to index the documents. In 1966, Salton identified this problem as crucial when he saw that his system, Medlars, did not find a relevant text because of the wrong indexation. Faced with this problem, he imagined a guide to help authors choose the correct indexation, but he anticipated the automation of this operation with the SMART system. It was stated previously that a manual language analysis for information items by subjects experts is likely to prove impractical in the long run. After a brief survey of the existing responses to the index choice problem, we shall present the system automatic natural acquisition (ANA) which chooses items to index texts by using as little knowledge as possible- -just by learning the language. This system does not use any grammar or lexicon, so the selected indexes will be very close to the field concerned in the texts.

Paper Details

Date Published: 1 March 1992
PDF: 12 pages
Proc. SPIE 1707, Applications of Artificial Intelligence X: Knowledge-Based Systems, (1 March 1992); doi: 10.1117/12.56895
Show Author Affiliations
Chantal Enguehard, CEN Cadarache (France)
Pierre Malvache, CEN Cadarache (France)
Philippe Trigano, Univ. de Technologie de Compiegne (France)


Published in SPIE Proceedings Vol. 1707:
Applications of Artificial Intelligence X: Knowledge-Based Systems
Gautam Biswas, Editor(s)

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