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Proceedings Paper

Neural network approach to text processing
Author(s): S. Sunthankar
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Paper Abstract

There is a great need for fast accurate text retrieval systems to support many intelligent activities. The text search problem can be broken down into two main tasks; database searching and message routing. Database searching consists of searching through a large database of text from certain key words, phrases, or other simple functions of strings. Message routing is classifying incoming messages and sending them to the appropriate `mail box.'' These are actually very similar tasks. Both are really just pattern matching tasks. What matters are the methods used. In addition to searching and classifying, it would be nice to perform other tasks such as inferencing and prediction, so these are discussed briefly. We discuss and compare current leading edge solutions to this problem and introduce some new ideas based on recent neural network theories and experiments. All text-search and retrieval technology is predicted on the assumption that the semantic content of text can be predictd from its syntactic properties: specifically, the existence, frequency, or absence of certain character strings or words; the relationship clustering among words and phrases; the occurrence of particular patterns in particular fields within the document.

Paper Details

Date Published: 1 August 1992
PDF: 9 pages
Proc. SPIE 1661, Machine Vision Applications in Character Recognition and Industrial Inspection, (1 August 1992); doi: 10.1117/12.130295
Show Author Affiliations
S. Sunthankar, Kingston Polytechnic (United Kingdom)

Published in SPIE Proceedings Vol. 1661:
Machine Vision Applications in Character Recognition and Industrial Inspection
Donald P. D'Amato; Wolf-Ekkehard Blanz; Byron E. Dom; Sargur N. Srihari, Editor(s)

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