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Cotofrei, Paul
Nom
Cotofrei, Paul
Affiliation principale
Fonction
Maître d'enseignement et de recherche
Email
paul.cotofrei@unine.ch
Identifiants
Résultat de la recherche
Voici les éléments 1 - 2 sur 2
- PublicationMétadonnées seulementFirst-Order Logic Based Formalism for Temporal Data MiningIn this article we define a formalism for a methodology that has as purpose the discovery of knowledge, represented in the form of general Horn clauses, inferred from databases with a temporal dimension. To obtain what we called temporal rules, a discretisation phase that extracts events from raw data is applied first, followed by an induction phase, which constructs classification trees from these events. The theoretical framework we proposed, based on first-order temporal logic, permits us to define the main notions (event, temporal rule, constraint) in a formal way. The concept of consistent linear time structure allows us to introduce the notions of general interpretation and of confidence. These notions open the possibility to use statistical approaches in the design of algorithms for inferring higher order temporal rules, denoted temporal meta-rules.
- PublicationMétadonnées seulementRule Extraction from Time Series Databases using Classification TreesDue to the wide availability of huge data collection comprising multiple sequences that evolve over time, the process of adapting the classical data-mining techniques, making them capable to work into this new context, becomes today a strong necessity. Having as a final goal the extraction of temporal rules from time series databases, we proposed in this article a methodology permitting the application of a classification tree on sequential raw data by the use of a flexible approach of the main terms as “classification class”, “training set”, “attribute set”, etc. We described also a first implementation of this methodology and presented some results on a synthetic time series database.