Recognition of abstract objects: a decision theory approach within natural language processing

Authors:
Gerhard Knorz
Affiliations:
Fachbereich Informatik, FG Datenverwal tungssys teme II, Technische Hochschule Darmstadt, Darmstadt, W-Germany
Venue:
COLING '82 Proceedings of the 9th conference on Computational linguistics - Volume 1
Year:
1982

Citing 3
Cited 1

Foundations of Probabilistic and Utility-Theoretic Indexing

Journal of the ACM (JACM)
Probabilistic models of indexing and searching

SIGIR '80 Proceedings of the 3rd annual ACM conference on Research and development in information retrieval
A decision theory approach to optimal automatic indexing

SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval

A decision theory approach to optimal automatic indexing

SIGIR '82 Proceedings of the 5th annual ACM conference on Research and development in information retrieval

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Abstract

The DAISY/ALIBABA-system developed within the WAI-project represents both a specific solution to the automatic indexing problem and a general framework for problems in the field of natural language processing, characterized by fuzziness and uncertainty. The WAI approach to the indexing problem has already been published [3], [5]. This paper however presents the underlying paradigm of recognizing abstract objects. The basic concepts are described, including the decision theory approach used for recognition.