Mining frequent patterns and association rules using similarities

作者：Rodriguez Gonzalez Ansel Y^*; Fco Martinez Trinidad Jose; Carrasco Ochoa Jesus A; Ruiz Shulcloper Jose

来源：Expert Systems with Applications, 2013, 40(17): 6823-6836.

DOI：10.1016/j.eswa.2013.06.041

• Data mining
• Frequent patterns
• Association rules
• Mixed data
• Similarity functions
• Downward closure property

Most of the current algorithms for mining association rules assume that two object subdescriptions are similar when they are exactly equal, but in many real world problems some other similarity functions are used. Commonly these algorithms are divided in two steps: Frequent pattern mining and generation of interesting association rules from frequent patterns. In this work, two algorithms for mining frequent similar patterns using similarity functions different from the equality are proposed. Additionally, the GenRules Algorithm is adapted to generate interesting association rules from frequent similar patterns. Experimental results show that our algorithms are more effective and obtain better quality patterns than the existing ones.

• 出版日期2013-12-1