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Agrawal, R. and Srikan, R. (1994) Fast Algorithms for Mining Association Rules in Large Databases. Proceedings of Proceedings of 20th International Conference on Very Large Data Bases, Santiago de Chile, 12-15 September 1994, 487-499.
https://rakesh.agrawal-family.com/papers/vldb94apriori.pdf

has been cited by the following article:

• TITLE: Ethics Lines and Machine Learning: A Design and Simulation of an Association Rules Algorithm for Exploiting the Data

  AUTHORS: Patrici Calvo, Rebeca Egea-Moreno

  KEYWORDS: Data Mining, Ethics Lines, Association Rules, Apriori Algorithm, Company

  JOURNAL NAME: Journal of Computer and Communications, Vol.9 No.12, December 23, 2021

  ABSTRACT: Data mining techniques offer great opportunities for developing ethics lines whose main aim is to ensure improvements and compliance with the values, conduct and commitments making up the code of ethics. The aim of this study is to suggest a process for exploiting the data generated by the data generated and collected from an ethics line by extracting rules of association and applying the Apriori algorithm. This makes it possible to identify anomalies and behaviour patterns requiring action to review, correct, promote or expand them, as appropriate.