Mining association rules and mining sequential patterns both are to discover customer purchasing behaviors from a transaction database, such that the quality of business decision ...
To efficiently find global patterns from a multi-database, information in each local database must first be mined and summarized at the local level. Then only the summarized infor...
The issue addressed in this paper concerns the discovery of frequent multi-dimensional patterns from relational sequences. The great variety of applications of sequential pattern m...
Floriana Esposito, Nicola Di Mauro, Teresa Maria A...
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...
Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mini...
Clinical databases store large amounts of information about patients and their medical conditions. Data mining techniques can extract relationships and patterns holding in this we...
Michele Berlingerio, Francesco Bonchi, Fosca Giann...
In this paper we consider the problem of the incremental mining of sequential patterns when new transactions or new customers are added to an original database. We present a new a...
Previous studies on mining sequential patterns have focused on temporal patterns specified by some form of propositional temporal logic. However, there are some interesting sequen...
Sandra de Amo, Daniel A. Furtado, Arnaud Giacomett...
We propose a new kind of sequential pattern which we call Generalized Sequential Pattern, and we introduce the problem of mining generalized sequential patterns over temporal datab...
The main drawbacks of sequential pattern mining have been its lack of focus on user expectations and the high number of discovered patterns. However, the solution commonly accepted...