Memory-based planning knowledge schema acquisition from natural language explanation = 자연어 표현에서 계층적 기억 구조를 이용한 계획 지식 스키마의 습득

A natural language understanding system requires extensive knowledge about the world. Since most systems simply have the built-in knowledge schemata, it is appropriate to consider how to acquire these knowledge schemata automatically. In this thesis, the problem of acquiring planning knowledge schema from natural language explanation is addressed by constructing a computer model which analyzes narratives containing planning knowledge. The system attempts to construct the causal structure of the narrative in terms of the goals and their plans. It acquires the planning knowledge schema if there exists. This approach is not the inductive but one trial learning. The acquired schemata contain processing knowledge which is useful in dealing with the kinds of planning, and serve as episodic memory structure indexing scheme.
Advisors
Kim, Gil-Changresearcher김길창researcher
Publisher
한국과학기술원
Issue Date
1986
Identifier
65154/325007 / 000841294
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전산학과, 1986.2, [ [iv], 36 p. ]

Keywords

계획 기반.; 자연 언어 처리.

URI
http://hdl.handle.net/10203/33684
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=65154&flag=t
Appears in Collection
CS-Theses_Master(석사논문)
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