Sequential pattern mining is an important subfield in data mining. Recently, applications
using time interval-based event data have attracted considerable efforts in discovering …

Episode rules are patterns that can be extracted from a large event sequence, to suggest to
experts possible dependencies among occurrences of event types. The corresponding …

An important data mining task is to discover all high utility sequences in a quantitative
sequence database. Although useful, the number of discovered sequences is often very …

In this paper we consider the problem of discovering sequential patterns by handling time
constraints as defined in the Gsp algorithm. While sequential patterns could be seen as …

Sequential pattern mining is essential in many applications, including computational
biology, consumer behavior analysis, web log analysis, etc. Although sequential patterns …

Mining useful information from large databases has become an important research area in
recent years. Among the classes of knowledge derived, sequential pattern can be applied in …

Constraint-based frequent sequence mining is an important and necessary task in data
mining since it shows results very close to the requirements and interests of users. Most …

Sequential pattern mining and temporal association rule mining techniques are established
techniques to mine insights into the data collected by smart home environments and …

Events prediction in a sequence of events is a challenging task that can be approached with
data mining. In this paper, we focus on the specific case of early prediction of distant events …

In this paper, we present a technique for helping experts in agricultural monitoring, by
mining Satellite Image Time Series over cultivated areas. We use frequent sequential …