A Survey on Condensed Representations for Frequent Sets

Abstract. Solving inductive queries which have to return complete collections of patterns satisfying a given predicate has been studied extensively the last few years. The specific problem of frequent set mining from potentially huge boolean matrices has given rise to tens of efficient solvers. Frequent sets are indeed useful for many data mining tasks, including the popular association rule mining task but also feature construction, association-based classification, clustering, etc. The research in this area has been boosted by the fascinating concept of condensed representations w.r.t. frequency queries. Such representations can be used to support the discovery of every frequent set and its support without looking back at the data. Interestingly, the size of condensed representations can be several orders of magnitude smaller than the size of frequent set collections. Most of the proposals concern exact representations while it is also possible to consider approximated ones, i.e., to...

• Type: Conference
• Year: 2004
• Where: CINQ
• Authors: Toon Calders, Christophe Rigotti, Jean-François Boulicaut
• Keywords: CINQ 2004, Condensed Representation, Database, Frequent Set Mining, Frequent Sets