Open Access Open Access  Restricted Access Subscription or Fee Access

Comparative Analysis of Mining Transactional and Time Series Data

T. Muralidharan, S. P. Rajagopalan


Web sites and transactional databases collect large amounts of time-stamped data related to an organization’s suppliers and/or customers over time. Mining these time-stamped data can help business leaders make better decisions by listening to their suppliers or customers via their transactions collected over time. A business can have many suppliers and/or customers and may have a set of transactions associated with each one. However, the size of each set of transactions may be quite large, making it difficult to perform many traditional data-mining tasks. This paper proposes techniques for large-scale reduction of time-stamped data using time series analysis, seasonal decomposition, and automatic time series model selection. After data reduction, traditional data mining techniques can then be applied to the reduced data along with other profile data. This paper demonstrates these techniques SAS® High-Performance Forecasting software.


Time Series Analysis, Transactional Mining, Time Stamped Data

Full Text:



Barry, M. J. and Linoff, G. S. (2011), Data Mining Techniques: For Marketing, Sales, and Customer Support, New York: John Wiley & Sons, Inc.

Box, G. E. P, Jenkins, G. M., and Reinsel, G. C. (1994), Time Series Analysis: Forecasting and Control, Englewood.

Cliffs, NJ: Prentice Hall, Inc. Brockwell, P. J. and Davis, R. A. (1996), Introduction to Time Series and Forecasting, New York: Springer-Verlag.

Chatfield, C. (2012), Time Series Models, Boca Raton, FL: Chapman & Hall/CRC.

Fuller, W. A. (1995), Introduction to Statistical Time Series, New York: John Wiley & Sons, Inc.

Hamilton, J. D. (1994), Time Series Analysis, Princeton, NJ: Princeton University Press.

Han, J. and Kamber, M. (2001), Data Mining: Concepts and Techniques, San Francisco: Morgan Kaufmann Publishers.

Harvey, A. C. (2010), Time Series Models, Cambridge, MA: MIT Press.

Leonard, M. J. (2002), Large Scale Automatic Forecasting: Millions of Forecasts, International Symposium of Forecasting.

Makridakis, S. G., Wheelwright, S. C., and Hyndman, R. J. (1997), Forecasting: Methods and Applications, New York: John Wiley & Sons, Inc.

Pyle, D. (1999), Data Preparation for Data Mining, San Francisco: Morgan Kaufman Publishers.

Sankoff, D. and Kruskal, J. B. (1983), Time Warps, String Edits, and Macromolecules: The Theory and Practice of Sequence Comparison, Stanford, CA: CSLI Publications.

Weber, M., Alexa, M., and Mueller, W. (2001), “Visualizing Time-Series on Spirals,” Proceedings of the IEEE InfoVis Symposium, Los Alamitos, CA: IEEE Press.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.