A Survey on Temporal Data Clustering

Abstract: Temporal data clustering provides underpinning techniques for discovering the intrinsic structure and condensing information over temporal data. To classify data mining problems and algorithms used two dimensions: data type and type of mining operations. One of the main issue that arise during the data mining process is treating data that contains temporal information. Temporal data representations are generally classified into two categories: piecewise and global representations the area of temporal data mining has very much attention in the last decade because from the time related feature of the data, one can extract much significant information which cannot be extracted by the general methods of data mining. Many interesting techniques of temporal data clustering were proposed and shown to be useful in many applications. Since temporal data clustering brings together techniques from different fields such as databases, statistics and machine learning the literature is scattered among many different sources. In this paper, present a survey on temporal data clustering.

Keywords: Temporal Data, Data Mining, Clustering