Rule schemas and interesting association action rules mining

Angelina A. Tzacheva

International Journal of Data Mining, Modelling and Management, 2012, vol. 4, issue 3, 244-254

Abstract: One of the central problems in knowledge discovery in databases, relies on the very large number of rules that classic rule mining systems extract. This problem is usually solved by means of a post-processing step, that alters the entire volume of extracted rules, in order to output only a few potentially interesting ones. This article presents a new approach that allows the user to explore action rules space locally, without the need to extract and post-process all action rules from a database. This solution is based on rule schemas, a new formalism designed to improve the representation of user beliefs and expectations, and on a novel algorithm for local action rules mining based on schemas.

Keywords: action rules; knowledge discovery; rule schemas; data mining; rules mining; association rules; user beliefs; user expectations. (search for similar items in EconPapers)
Date: 2012
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