Stochastic processes and temporal data mining

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Stochastic processes and temporal data mining
This article tries to give an answer to a fundamental question in temporal data mining: "Under what conditions a temporal rule extracted from up-to-date temporal data keeps its confidence/support for future data". A possible solution is given by using, on the one hand, a temporal logic formalism which allows the definition of the main notions (event, temporal rule, support, confidence) in a formal way and, on the other hand, the stochastic limit theory. Under this probabilistic temporal framework, the equivalence between the existence of the support of a temporal rule and the law of large numbers is systematically analyzed. Categories and Subject Descriptors H.2.8 [DATABASE MANAGEMENT]: Database Applications-data mining; G.3 [Mathematics of Computing]: PROBABILITY AND STATISTICS--Stochastic processes; F.4.1 [MATHEMATICAL LOGIC AND FORMAL LANGUAGES]: Mathematical Logic-temporal logic General Terms THEORY Keywords Consistency of temporal rules, stochastic limit theory, stochas...
Paul Cotofrei, Kilian Stoffel
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2007
Where KDD
Authors Paul Cotofrei, Kilian Stoffel
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