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DOI: 10.14569/IJACSA.2020.0111274
PDF

Agent Mining Framework for Analyzing Moroccan Olive Oil Datasets

Author 1: Belabed Imane
Author 2: Jaara El Miloud
Author 3: Belabed Abdelmajid
Author 4: Talibi Alaoui Mohammed

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 12, 2020.

  • Abstract and Keywords
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Abstract: Data mining and intelligent agents have become two promising research areas. Each intelligent agent functions independently while cooperating with other agents, to perform effectively assigned tasks. The main goal of this research, is to provide a mining implementation that can help biological researchers for discovering parameters that affect the cost of olive oil in Morocco. To solve this problem, we used a method involving two data mining techniques, clustering of variables, quantitative association rules and multi-agent system to fuse these two techniques. Therefore, we have developed a multi-agent framework that has been validated by using concrete data from the Provincial Direction of Agriculture of Berkane, Morocco. To prove the performance of our framework, we tested the proposed multi-agent tool using three datasets from different fields. Conforming to biological researchers, our method generates a clear knowledge because the framework proposes high-confidence rules that can correctly identify olive oil factors.

Keywords: Quantitative association rules; clustering of variables; multi-agent system

Belabed Imane, Jaara El Miloud, Belabed Abdelmajid and Talibi Alaoui Mohammed, “Agent Mining Framework for Analyzing Moroccan Olive Oil Datasets” International Journal of Advanced Computer Science and Applications(IJACSA), 11(12), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0111274

@article{Imane2020,
title = {Agent Mining Framework for Analyzing Moroccan Olive Oil Datasets},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0111274},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0111274},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {12},
author = {Belabed Imane and Jaara El Miloud and Belabed Abdelmajid and Talibi Alaoui Mohammed}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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