We propose a way of extracting high-confidence association rules from datasets consisting of unlabeled trees. The antecedents are obtained through a computation akin to a hypergrap...
Abstract. In this paper we aim at extending the non-derivable condensed representation in frequent itemset mining to sequential pattern mining. We start by showing a negative examp...
This paper surveys some genetic-fuzzy data mining techniques for mining both membership functions and fuzzy association rules. The motivation from crisp mining to fuzzy mining wil...
Abstract. The effective construction of many association rule bases requires the computation of both frequent closed and frequent generator itemsets (FCIs/FGs). However, only few m...
Abstract. This paper proposes a novel approach named AGM to eciently mine the association rules among the frequently appearing substructures in a given graph data set. A graph tran...