TY - JOUR
T1 - A framework for knowledge-based temporal abstraction
AU - Shahar, Yuval
N1 - Funding Information:
This work has been supportedi n part by grant HS06330 from the Agency for Health Care Policy and Research, by grants LM05157, LMO5305, LMO5708, and LM06245 from the National Library of Medicine, and by grants IRI-9257578 and IRI-9528444 from the National Science Foundation. I thank Mark Musen, Richard Fikes, and Barbara Hayes-Roth for technical advice and support.I had many useful discussions with Samson Tu, Amar Das, and Michael Kahn.
PY - 1997/1/1
Y1 - 1997/1/1
N2 - 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 RÉSUMÉ 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.
AB - 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 RÉSUMÉ 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.
KW - Knowledge acquisition
KW - Knowledge representation
KW - Temporal abstraction
KW - Temporal reasoning
UR - http://www.scopus.com/inward/record.url?scp=0031069719&partnerID=8YFLogxK
U2 - 10.1016/s0004-3702(96)00025-2
DO - 10.1016/s0004-3702(96)00025-2
M3 - Article
AN - SCOPUS:0031069719
SN - 0004-3702
VL - 90
SP - 79
EP - 133
JO - Artificial Intelligence
JF - Artificial Intelligence
IS - 1-2
ER -
