Efficient Algorithm for Mining Temporal Association Rule

Improving Efficiency in Mining Temporal Association Rules from Data Streams

Authors

  • Ruchi Sharma

Keywords:

efficient algorithm, mining, temporal association rule, data mining, abnormalities, patterns, relationships, large data collections, predict outcomes, revenue, cost reduction, customer relationships, risk reduction, data streams, high utility item sets

Abstract

Data mining is the way toward discovering abnormalities, examples and relationships inside enormous dataal collections to foresee results. Utilizing a wide scope of strategies, you can utilize this data to expand incomes, cut expenses, improve client connections, and decrease dangers and that's only the tip of the iceberg. This paper investigates the effective calculation for mining fleeting high utility item sets from data streams.

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Published

2019-02-01

How to Cite

[1]
“Efficient Algorithm for Mining Temporal Association Rule: Improving Efficiency in Mining Temporal Association Rules from Data Streams”, JASRAE, vol. 16, no. 2, pp. 895–898, Feb. 2019, Accessed: Dec. 25, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/10243

Issue

Vol. 16 No. 2 (2019): Journal of Advances and Scholarly Researches in Allied Education (JASRAE)

Section

Articles

How to Cite

[1]
“Efficient Algorithm for Mining Temporal Association Rule: Improving Efficiency in Mining Temporal Association Rules from Data Streams”, JASRAE, vol. 16, no. 2, pp. 895–898, Feb. 2019, Accessed: Dec. 25, 2025. [Online]. Available: https://ignited.in/index.php/jasrae/article/view/10243