Dynamic Parallel Mining Algorithm of Association Rules Based on Interval Concept Lattice

Yafeng Yang, Ru Zhang and Baoxiang Liu
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Yafeng Yang: College of Science, North China University of Science and Technology, 21 Bohai Road, Tangshan 063210, China
Ru Zhang: Department of mathematics and information sciences, Tangshan Normal University, No. 156 Jianshe North Road, Tangshan 063009, China
Baoxiang Liu: College of Science, North China University of Science and Technology, 21 Bohai Road, Tangshan 063210, China

Mathematics, 2019, vol. 7, issue 7, 1-12

Abstract: An interval concept lattice is an expansion form of a classical concept lattice and a rough concept lattice. It is a conceptual hierarchy consisting of a set of objects with a certain number or proportion of intent attributes. Interval concept lattices refine the proportion of intent containing extent to get a certain degree of object set, and then mine association rules, so as to achieve minimal cost and maximal return. Faced with massive data, the structure of an interval concept lattice is more complex. Even if the lattice structures have been united first, the time complexity of mining interval association rules is higher. In this paper, the principle of mining association rules with parameters is studied, and the principle of a vertical union algorithm of interval association rules is proposed. On this basis, a dynamic mining algorithm of interval association rules is designed to achieve rule aggregation and maintain the diversity of interval association rules. Finally, the rationality and efficiency of the algorithm are verified by a case study.

Keywords: interval concept lattice; association rules; mining algorithm; vertical union (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2019
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