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Loss Profit Estimation Using Temporal Association Rule Mining

Loss Profit Estimation Using Temporal Association Rule Mining

Reshu Agarwal, Mandeep Mittal, Sarla Pareek
Copyright: © 2016 |Volume: 3 |Issue: 1 |Pages: 13
ISSN: 2334-4547|EISSN: 2334-4555|EISBN13: 9781466693869|DOI: 10.4018/IJBAN.2016010103
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MLA

Agarwal, Reshu, et al. "Loss Profit Estimation Using Temporal Association Rule Mining." IJBAN vol.3, no.1 2016: pp.45-57. http://doi.org/10.4018/IJBAN.2016010103

APA

Agarwal, R., Mittal, M., & Pareek, S. (2016). Loss Profit Estimation Using Temporal Association Rule Mining. International Journal of Business Analytics (IJBAN), 3(1), 45-57. http://doi.org/10.4018/IJBAN.2016010103

Chicago

Agarwal, Reshu, Mandeep Mittal, and Sarla Pareek. "Loss Profit Estimation Using Temporal Association Rule Mining," International Journal of Business Analytics (IJBAN) 3, no.1: 45-57. http://doi.org/10.4018/IJBAN.2016010103

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Abstract

Temporal association rule mining is a data mining technique in which relationships between items which satisfy certain timing constraints can be discovered. This paper presents the concept of temporal association rules in order to solve the problem of classification of inventories by including time expressions into association rules. Firstly, loss profit of frequent items is calculated by using temporal association rule mining algorithm. Then, the frequent items in particular time-periods are ranked according to descending order of loss profits. The manager can easily recognize most profitable items with the help of ranking found in the paper. An example is illustrated to validate the results.

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