Title

Knowledge Acquisition From Natural Language For Expert Systems Based On Classification Problem-Solving Methods

Abstract

It is shown how certain kinds of domain independent expert systems based on classification problem-solving methods can be constructed directly from natural language descriptions by a human expert. The expert knowledge is not translated into production rules. Rather, it is mapped into conceptual structures which are integrated into long-term memory (LTM). The resulting system is one in which problem-solving, retrieval and memory organization are integrated processes. In other words, the same algorithm and knowledge representation structures are shared by these processes. As a result of this, the system can answer questions, solve problems or reorganize LTM. © 1990 Academic Press Limited.

Publication Date

1-1-1990

Publication Title

Knowledge Acquisition

Volume

2

Issue

2

Number of Pages

107-128

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/S1042-8143(05)80007-X

Socpus ID

0039240899 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0039240899

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