Probabilistic abstraction of uncertain temporal data for multiple subjects

Authors:
Michael Ramati;Yuval Shahar
Affiliations:
Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, Beer-Sheva, Israel;Medical Informatics Research Center, Department of Information Systems Engineering, Ben-Gurion University, Beer-Sheva, Israel
Venue:
SARA'05 Proceedings of the 6th international conference on Abstraction, Reformulation and Approximation
Year:
2005

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Abstract

Several Systems have been designed to solve the task of abstraction of time-stamped raw data into domain-specific meaningful concepts and patterns. All approaches had to some degree severe limitations in their treatment of incompleteness and uncertainty that typically underlie the raw data, on which the temporal reasoning is performed, and have generally narrowed their interest to a single subject. We have designed a new probability-oriented methodology to overcome these conceptual limitations. The new method includes also a practical parallel computational model that is geared specifically for implementing our probabilistic approach.