Data mining has been recognised as an essential element of decision support, which has increasingly become a focus of the database industry. Like all computationally expensive data...
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm...
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...