The analysis on model of association rules mining based on concept lattice and Apriori algorithm
Xuegang Hu, Dexing Wang, Xiaoping Liu, Jun Hai Guo, Hao Wang · 2005
Concept lattice represents knowledge with the relationships between the intension and the extension of concepts, and the relationship between the generalization and the specialization of concepts, thus it is properly applied to the description of association rules mining in database. The quantitative extended concept lattice (QECL) evolves from concept lattice by introducing equivalent relationships to its intension and quantity to its extension, based on it, we can mine association rules, compared with the well-known Apriori algorithm, without calculating frequent itemsets, easily obtain interesting association rules, in the meantime a lot of redundant rules are reduced, thus the efficiency and veracity of the mining rules are improved.