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Mixed-Level Knowledge Representations and Variable-Depth Inference in Natural Language Processing


Hess, M (1997). Mixed-Level Knowledge Representations and Variable-Depth Inference in Natural Language Processing. International Journal on Artificial Intelligence Tools (IJAIT), 6(4):481-509.

Abstract

A system is described that uses a mixed-level knowledge representation based on standard Horn Clause Logic to represent (part of) the meaning of natural language documents. A variable-depth search strategy is outlined that distinguishes between the different levels of abstraction in the knowledge representation to locate specific passages in the documents. A detailed description of the linguistic aspects of the system is given. Mixed-level representations as well as variable-depth search strategies are applicable in fields outside that of NLP.

Abstract

A system is described that uses a mixed-level knowledge representation based on standard Horn Clause Logic to represent (part of) the meaning of natural language documents. A variable-depth search strategy is outlined that distinguishes between the different levels of abstraction in the knowledge representation to locate specific passages in the documents. A detailed description of the linguistic aspects of the system is given. Mixed-level representations as well as variable-depth search strategies are applicable in fields outside that of NLP.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:410 Linguistics
000 Computer science, knowledge & systems
Date:December 1997
Deposited On:15 Jun 2009 06:38
Last Modified:06 Dec 2017 19:55
Publisher:World Scientific Publishing
ISSN:0218-2130
Publisher DOI:https://doi.org/10.1142/S0218213097000256

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