Association Rule Mining

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Author(s): Vasudha Bhatnagar (University of Delhi, India)and Sarabjeet Kochhar (University of Delhi, India)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Artificial Intelligence
Source Author(s)/Editor(s): Juan Ramón Rabuñal Dopico (University of A Coruña, Spain), Julian Dorado (University of A Coruña, Spain)and Alejandro Pazos (University of A Coruña, Spain)
DOI: 10.4018/978-1-59904-849-9.ch027

Keywords: Artificial Intelligence / Computer Science & IT / Information Science Reference

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Abstract

Data mining is a field encompassing study of the tools and techniques to assist humans in intelligently analyzing (mining) mountains of data. Data mining has found successful applications in many fields including sales and marketing, financial crime identification, portfolio management, medical diagnosis, manufacturing process management and health care improvement etc.. Data mining techniques can be classified as either descriptive or predictive techniques. Descriptive techniques summarize / characterize general properties of data, while predictive techniques construct a model from the historical data and use it to predict some characteristics of the future data. Association rule mining, sequence analysis and clustering are key descriptive data mining techniques, while classification and regression are predictive techniques. The objective of this article is to introduce the problem of association rule mining and describe some approaches to solve the problem.

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