International audienceAn approximate discovery of closed itemsets is usually based on either setting a frequency threshold or computing a sequence of projections. Both approaches, being incremental, do not provide any estimate of the size of the next output and do not ensure that "more interesting patterns" will be generated first. We propose to generate closed item-sets incrementally, w.r.t. the size of the smallest (cardinality-minimal or minimum) generators and show that this approach (i) exhibits anytime property, and (ii) generates itemsets of decreasing quality
In this paper, we study efficient closed pattern mining in a general framework of set systems, which...
ABSTRACT. In this paper, we address the problem of the usefulness of the set of discovered asso-ciat...
International audienceAssociation rules are conditional implications between requent itemsets. The p...
International audienceMining gradual rules of the form −"the more A, the more B"− is more and more g...
The generators and the unique closed pattern of an equivalence class of itemsets share a common set ...
International audienceIn this paper, we address the problem of finding frequent itemsets in a databa...
Abstract. We investigate the computational complexity of some deci-sion and counting problems relate...
AbstractAssociation rule mining from a transaction database (TDB) requires the detection of frequent...
International audienceCondensed representations have been studied extensively for 15 years. In parti...
AbstractAn incremental algorithm to construct a lattice from a collection of sets is derived, refine...
International audienceIn this paper, we address the problem of the usefulness of the set of discover...
International audienceIn this paper, we address the problem of the understandability and usefulness ...
Past observations have shown that a frequent item set mining algorithm are alleged to mine the close...
Pattern Mining is one of the most researched topics in the data mining community. Literally hundreds...
International audienceCondensed representations have been studied extensively for 15 years. In parti...
In this paper, we study efficient closed pattern mining in a general framework of set systems, which...
ABSTRACT. In this paper, we address the problem of the usefulness of the set of discovered asso-ciat...
International audienceAssociation rules are conditional implications between requent itemsets. The p...
International audienceMining gradual rules of the form −"the more A, the more B"− is more and more g...
The generators and the unique closed pattern of an equivalence class of itemsets share a common set ...
International audienceIn this paper, we address the problem of finding frequent itemsets in a databa...
Abstract. We investigate the computational complexity of some deci-sion and counting problems relate...
AbstractAssociation rule mining from a transaction database (TDB) requires the detection of frequent...
International audienceCondensed representations have been studied extensively for 15 years. In parti...
AbstractAn incremental algorithm to construct a lattice from a collection of sets is derived, refine...
International audienceIn this paper, we address the problem of the usefulness of the set of discover...
International audienceIn this paper, we address the problem of the understandability and usefulness ...
Past observations have shown that a frequent item set mining algorithm are alleged to mine the close...
Pattern Mining is one of the most researched topics in the data mining community. Literally hundreds...
International audienceCondensed representations have been studied extensively for 15 years. In parti...
In this paper, we study efficient closed pattern mining in a general framework of set systems, which...
ABSTRACT. In this paper, we address the problem of the usefulness of the set of discovered asso-ciat...
International audienceAssociation rules are conditional implications between requent itemsets. The p...