Incremental Maintenance of Frequent Itemsets in Evidential Databases

Authors:
Mohamed Anis Bach Tobji;Boutheina Ben Yaghlane;Khaled Mellouli
Affiliations:
LARODEC Laboratory, Institut Supérieur de Gestion de Tunis,;LARODEC Laboratory, Institut des Hautes Etudes Commerciales de Carthage,;LARODEC Laboratory, Institut des Hautes Etudes Commerciales de Carthage,
Venue:
ECSQARU '09 Proceedings of the 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty
Year:
2009

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Abstract

In the last years, the problem of Frequent Itemset Mining (FIM) from imperfect databases has been sufficiently tackled to handle many kinds of data imperfection. However, frequent itemsets discovered from databases describe only the current state of the data. In other words, when data are updated, the frequent itemsets could no longer reflect the data, i.e., the data updates could invalidate some frequent itemsets and vice versa, some infrequent ones could become valid. In this paper, we try to resolve the problem of Incremental Maintenance of Frequent Itemsets (IMFI) in the context of evidential data. We introduce a new maintenance method whose experimentations show efficiency compared to classic methods.