A FRAMEWORK FOR KNOWLEDGE-BASED TEMPORAL ABSTRACTION

A new domain-independent knowledge-based inference structure is presen ted, specific to the task of abstracting higher-level concepts from ti me-stamped data. The framework includes a model of time, parameters, e vents, and contexts. A formal specification of a domain's temporal abs traction knowledge supports acquisition, maintenance, reuse, and shari ng of that knowledge. The knowledge-based temporal abstraction method decomposes the temporal abstraction task into five subtasks. These sub tasks are solved by five domain-independent temporal abstraction mecha nisms. The temporal abstraction mechanisms depend on four domain-speci fic knowledge types: structural, classification (functional), temporal semantic (logical), and temporal dynamic (probabilistic) knowledge. D omain values for all knowledge types are specified when a temporal abs traction system is developed, The knowledge-based temporal abstraction method has been implemented in the RESUME system, and has been evalua ted in several clinical domains (protocol-based care, monitoring of ch ildren's growth, and therapy of diabetes) and in an engineering domain (monitoring of traffic control), with encouraging results. (C) 1997 E lsevier Science B.V.