ABSTRACT
Data mining is a process of identifying suitable, useful, and reasonable patterns in data. It deals with the analysis of large volume of structured and unstructured data for discovering regularities or relationships between them. Temporal data mining concerns with the investigation of events controlled by one or more dimensions of time, whereas spatial data mining considers the alternative path of embedded and entirely spatial constructs based on several static techniques. Spatio-temporal data mining corresponds to the confluence of a number of fields such as database, statistics, and geographic visualization. It is a user-centric and interactive process, where experts work jointly to achieve solutions for a given problem. Spatio-temporal data mining considers multiple states of the spatio-temporal data to find significant spatio-temporal patterns, which is expensive. This paper covers various data mining areas and several algorithms as well as their application in research.
