Author : G.Sophana 1
Date of Publication :31st December 2017
Abstract: Data Mining is the process of mining patterns in large databases. Temporal Data Mining (TDM) is the key area to mine the sequence patterns of data. TDM is a rapidly evolving area of research and deals with extremity information from temporal data with the time factor. The application of TDM ranges from the prediction of customer behaviour, marketing, medical, communication, agriculture, weather forecast, finance., The techniques involved in TDM are Apriori, Classification, Clustering, GSP, SPADE and PrefixSPAN. This paper focuses on the area of applications and variety of techniques involved and guide for the selection of applications with appropriate techniques
Reference :
-
- M. Viswambari, Dr. R. Anbu Selvi (2014) : Data Mining Techniques to Predict Weather: A Survey International Journal of Innovative Science, Engineering & Technology, Vol-1 Issue 4
- Rajesh Kumar (2013) : Decision Tree for the Weather Forecasting , International Journal of Computer Applications, Vol-76, Number 2
- Manika Verma, Devarshi Mehta (2014) : Sequential Pattern Mining: A Comparison between GSP, SPADE and Prefix SPAN International Journal of Engineering Development and Research, Vol- 2, Issue 3
- Roshani Patel, Tarunika Chaudhari (2016): A review on sequential pattern mining using pattern growth approach algorithm based on parameter. International Conference on Wireless Communications, Signal Processing and Networking
- Margaret H.Dunham,S.Sridhar :DATA MINING Introductory and Advanced Topics