Networks are used as highly expressive tools in different disciplines. In recent years, the
analysis and mining of temporal networks have attracted substantial attention. Frequent …

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

For many years, time series data have been considered as one of the most popular
significant data forms in our daily life. Time series exist in many application domains such as …

Temporal network mining tasks are usually hard problems. This is because we need to face
not only a large amount of data but also its non-stationary nature. In this paper, we propose …

The incorporation of temporal semantics into the traditional data mining techniques has
caused the creation of a new area called Temporal Data Mining. This incorporation is …

Periodic pattern mining is an emerging technique for knowledge discovery. Most previous
approaches have aimed to find only those patterns that exhibit full (or perfect) periodic …

Closed sequential patterns have attracted researchers' attention due to their capability of
using compact results to preserve the same expressive power as conventional sequential …

Periodic-frequent pattern mining (PFPM) is an important data mining model having many
real-world applications. However, the successful industrial application of this model has …

In many applications that track and analyze spatiotemporal data, movements obey periodic
patterns; the objects follow the same routes (approximately) over regular time intervals. For …

Technological advances in the field of Information and Communication Technologies (ICTs)
have facilitated organizations to collect, store, and process massive amounts of data. Useful …