Temporal data mining deals with the harvesting of useful information from temporal data.
New initiatives in health care and business organizations have increased the importance of …

ABSTRACT Temporal Data Mining is a rapidly evolving area of research that is at the
intersection of several disciplines, including statistics, temporal pattern recognition, temporal …

With the growth in the size of datasets, data mining has recently become an important
research topic and is receiving substantial interest from both academia and industry. At the …

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

With the increase in the size of data sets, data mining has recently become an important
research topic and is receiving substantial interest from both academia and industry. At the …

Data mining is concerned with analysing large volumes of (often unstructured) data to
automatically discover interesting regularities or relationships which in turn lead to better …

Medical knowledge includes frequently occurring temporal patterns in longitudinal patient
records. These patterns are not easily detectable by human clinicians. Current knowledge …

Large volumes of spatio-temporal data are increasingly collected and studied in diverse
domains, including climate science, social sciences, neuroscience, epidemiology …

Data mining and knowledge discovery have become important issues for research over the
past decade. This has been caused not only by the growth in the size of datasets but also in …

Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …