A model for reasoning about persistence and causation
Computational Intelligence
Two views of belief: belief as generalized probability and belief as evidence
Artificial Intelligence
What is Dempster-Shafer's model?
Advances in the Dempster-Shafer theory of evidence
Finding interesting rules from large sets of discovered association rules
CIKM '94 Proceedings of the third international conference on Information and knowledge management
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Evidence Theory and Its Applications
Evidence Theory and Its Applications
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Current Approaches to Handling Imperfect Information in Data and Knowledge Bases
IEEE Transactions on Knowledge and Data Engineering
Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences
IEEE Transactions on Knowledge and Data Engineering
Designing a Kernel for Data Mining
IEEE Expert: Intelligent Systems and Their Applications
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Probabilistic temporal reasoning with endogenous change
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
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An {\it Event History} consists of a series of events where each event has an associated time of occurrence; events mark the start or end of a {\it spell}. An episode is a sequence of spells, which is a subset of the sequence of all spells that an individual undergoes; the full set constitutes the Event History. In this paper we are concerned with rule discovery for such Event Histories. Frequently interest focuses not only on the episodes which comprise of sequences of spells but also on the spell durations. We have provided a methodology for discretising such durations which utilises phase-type distributions where the phases correspond to the discretised classes. We also discuss how the Dempster-Shafer Theory of Evidence may be utilised to provide a methodology for inducing rules from such data when they contains partial values. These are caused by spells which are incomplete, frequently because at the current time point there are spells still in progress. Our approach is illustrated using data concerning event histories for 6994 geriatric patients.