We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
This paper describes an approach to temporal pattern mining
using the concept of user dened temporal prototypes to dene the
nature of the trends of interests. The temporal patt...
Vassiliki Somaraki, Deborah Broadbent, Frans Coene...
Finding patterns in temporal data is an important data analysis task in many domains. Static visualizations can help users easily see certain instances of patterns, but are not sp...
Spatio-temporal patterns extracted from historical trajectories of moving objects reveal important knowledge about movement behavior for high quality LBS services. Existing approac...
Abstract Large temporal Databases (TDBs) usually contain a wealth of data about temporal events. Aimed at discovering temporal patterns with during relationship (during-temporal pa...