INVESTIGATION OF ISSUES, TASKS & APPLICATIONS OF TEMPORAL DATA MINING IN IT INDUSTRIES

Authors

  • REENA DHULL Research Scholar
  • Er. Urvashi Garg Assistant Professor

Keywords:

Spatiotemporal data mining issues, spatiotemporal data mining tasks, KMean, Neural Network spatiotemporal data mining applications

Abstract

In our research problems & challenges related to spatiotemporal data representation, analysis, mining & visualization of knowledge have been presented. Many type of data mining tasks like association rules, classification clustering for discovering knowledge from spatiotemporal datasets are examined & reviewed. System functional requirements for such kind of knowledge discovery & database structure are discussed. So applications of spatiotemporal data mining are presented. Such applications are related to huge data of processed within IT industries. Temporal Data Mining is a rapidly evolving area of research that is at intersection of several disciplines, consisting statistics, temporal pattern recognition, temporal databases, optimization, visualization, high-performance computing & parallel computing. Spatiotemporal data generally consists states of an object and event or a position within space over a period of time.

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Published

30-06-2016

How to Cite

REENA DHULL, & Er. Urvashi Garg. (2016). INVESTIGATION OF ISSUES, TASKS & APPLICATIONS OF TEMPORAL DATA MINING IN IT INDUSTRIES. International Journal for Research Publication and Seminar, 7(3). Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/816

Issue

Vol. 7 No. 3 (2016): April - June 2016

Section

Original Research Article

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Copyright (c) 2016 International Journal for Research Publication and Seminar

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