A Framework for Knowledge-Based Temporal Abstraction

Reference: Shahar, Y. A Framework for Knowledge-Based Temporal Abstraction. Knowledge Systems Laboratory, Medical Computer Science, March, 1995.

Abstract: A 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. Values for the four knowledge types are specified when developing a temporal-abstraction system in a new domain. The knowledge-based temporal-abstraction method has been implemented in the RESUME system and evaluated in several different clinical domains (protocol-based care, monitoring of children's growth, and therapy of diabetes) with encouraging results.

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