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A framework for knowledge-based temporal abstraction

delete1997-02-01
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Yuval Shaḥar
DOI:10.1016/S0004-3702(96)00025-2delete
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Abstract

Abstract

En 中文
A new domain-independent knowledge-based inference structure is presented, specific to the task of abstracting higher-level concepts from time-stamped data. The framework includes a model of time, parameters, events, and contexts. A formal specification of a domain's temporal abstraction knowledge supports acquisition, maintenance, reuse, and sharing of that knowledge. The knowledge-based temporal abstraction method decomposes the temporal abstraction task into five subtasks. These subtasks are solved by five domain-independent temporal abstraction mechanisms. The temporal abstraction mechanisms depend on four domain-specific knowledge types: structural, classification (functional), temporal semantic (logical), and temporal dynamic (probabilistic) knowledge. Domain values for all knowledge types are specified when a temporal abstraction system is developed, The knowledge-based temporal abstraction method has been implemented in the RESUME system, and has been evaluated in several clinical domains (protocol-based care, monitoring of children's growth, and therapy of diabetes) and in an engineering domain (monitoring of traffic control), with encouraging results. (C) 1997 Elsevier Science B.V.
Keywords:
temporal reasoning
temporal abstraction
knowledge acquisition
knowledge representation
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Journal

Artificial Intelligence Review cover
Artificial Intelligence Review
IF:
13.9
Papers:
6.1K
Citations:
1.9W

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