Episode mining is a research area in data mining, where the aim is to discover interesting
episodes, that is, subsequences of events, in an event sequence. The most popular episode …

Frequent Episode Mining (FEM), which aims at mining frequent sub-sequences from a
single long event sequence, is one of the essential building blocks for the sequence mining …

Frequent episode mining is a popular data mining task for analyzing a sequence of events. It
consists of identifying all subsequences of events that appear at least minsup times. Though …

High utility episode mining consists of finding episodes (sub-sequences of events) that have
a high importance (eg high profit) in a sequence of events with quantities and weights …

Episode rule mining is a popular data mining task for analyzing a sequence of events or
symbols. It consists of identifying subsequences of events that frequently appear in a …

A large event sequence can generate episode rules that are patterns which help to identify
the possible dependencies existing among event types. Frequent episodes occurring in a …

Event prediction in sequence databases is an important and challenging data mining task.
We focus on the specific case of prediction of distant events. Our aim is to mine sequential …

Firms perform environmental surveillance to identify important events and their
developments. To alleviate the stringent information processing and analysis requirements …

An episode rule mining to extract useful and important patterns or episodes from large event
sequences represents the temporal implication of associating the antecedent and …

Episode discovery from an event is a popular framework for data mining tasks and has many
real-world applications. An episode is a partially ordered set of objects (eg, item, node), and …