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...

• Type: Conference
• Year: 2007
• Where: KDD
• Authors: Paul Cotofrei, Kilian Stoffel
• Keywords: Data Mining, KDD 2007, Temporal Data Mining, Temporal Logic Formalism, Temporal Rule