A Review on Machine Learning – Spatiotemporal Data Mining: Issues, Tasks and Applications

A Review on Machine Learning – Spatiotemporal Data Mining: Issues, Tasks and Applications

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1P. Madhuri, 2Dr.K. Srinivasa Rao, 3Dr. S.K. Yadav

Department of Computer Science and Engineering1, 2, 3

1Research Scholar, Shri Jagdishprasad Jhabarmal Tibrewala University.

2Professor and Principal, MLRIT, Hyderabad.

3Professor, Shri Jagdishprasad Jhabarmal Tibrewala University.

ABSTRACT: Spatiotemporal data generally involves the state o f an object, an occurrence, or a spatial location over a period. In many application areas, such as traffic control, climate monitoring, and weather prediction, a significa nt amount of spatiotemporal data can be

found. These datasets could be gathered in various formats. At different locations at different points of time. Because of the complex nature of spatiotemporal objects and their relationshi ps in both spatial and temporal

dimensions, this raises many difficulties in the representation, c ollection, interpretation, and mining of such datasets. Sometimes, spatio-temporal data sets are very board and hard to interpret and view. In this paper we propose several data mining tasks such a s association rules, classification clusters that are analysed and tested to discover information from

spatiotemporal datasets. System functional criteria are addressed for certain kinds of information discovery. Finally, applications are presented for spatiotempor al data mining.

Keywords: Data Mining, Temporal Data Mining, Spatial Data Mining, Spatio-Temporal Data Mining

1. INTRODUCTION

Naturally the data mining progress has led to the discovery of application domains within which data m ining can be used. As many of these domains

have an inherently temporal or spatial context, to correctly i nterpret the data obtained, the time and/or space dimension must be taken into account in the mining process.

Variable Energy ResourcesAn Architecture for Data MiningPrimary Data Mining Tasks4.1 Mining Temporal Sequences4.1.1 Representation of Temporal Sequence4.1.2 Transformation Based Representations4.2 Temporal Data Mining TasksObjectiveEfficient Support of DBMSSoftwares for Spatial Data MiningThe method of Spatio-Temporal Data miningThe intrinsic feature of spatio-temporal databases is genetics.Cascading Spatiotemporal Pattern discoverySPATIOTEMPORAL DATA MINING SYSTEM REQUIREMENTS AND APPLICATIONSSystem Requirements

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