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A framework for knowledge-based temporal abstraction
Abstract A domain-independent knowledge-based infer A domain-independent knowledge-based inference structure is presented, specificto the task of abstracting higher-level concepts from time-stamped data. Theframework includes a model of time, parameters, events, and contexts. A formalspecification of a domain's temporal-abstraction knowledge supportsacquisition, maintenance, reuse, and sharing of that knowledge.The knowledge-based temporal-abstraction method decomposes thetemporal-abstraction task into five subtasks. These subtasks are solved byfive domain-independent temporal-abstraction mechanisms. Thetemporal-abstraction mechanisms depend on four domain-specific knowledge types:structural, classification (functional), temporal-semantic (logical), andtemporal-dynamic (probabilistic) knowledge. Values for the four knowledgetypes are specified when developing a temporal-abstraction system in a newdomain. The knowledge-based temporal-abstraction method has been implemented in theRESUME system and evaluated in several different clinical domains(protocol-based care, monitoring of children's growth, and therapy of diabetes)with encouraging results. rapy of diabetes)with encouraging results.
Author Yuval Shahar +
Bibtype techreport  +
Institution Knowledge Systems, AI Laboratory +
Key KSL-95-29  +
Modification dateThis property is a special property in this wiki. 1 May 2009 14:02:30  +
Month March +
Note Medical Computer Science +
Number KSL-95-29  +
Tag Computer science +
Title A Framework for Knowledge-Based Temporal Abstraction  +
Tr id KSL-95-29  +
Year 1995  +
Categories Technical Report, Publication, KSL Technical Report
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