Finding frequent patterns in discrete sequences of symbols or events can be useful to
understand data, support decision-making and make predictions. However, many studies on
analyzing event sequence do not consider the duration of events, and thus the complex time
relationships between them (eg an event may start at the same time as another event but
end before). To find frequent sequential patterns in data where events have a start and end
time, an emerging topic is time-interval related pattern (TIRP) mining. Several algorithms …

Finding frequent patterns in discrete sequences of symbols or events can be useful to
understand data, support decision-making and make predictions. However, many studies on
analyzing event sequence do not consider the duration of events, and thus the complex time
relationships between them (eg an event may start at the same time as another event but
end before). To find frequent sequential patterns in data where events have a start and end
time, an emerging topic is timeinterval related pattern (TIRP) mining. Several algorithms …