关键词: 量化关联规则, MPSQAR算法, 语义信息损失

Abstract: During the process of mining quantitative association rules， the semantics may be lost due to the discretization of quantitative values. To avoid the loss of semantic information， a novel algorithm， MPSQAR （mining preserving semantic quantitative association rule）， is proposed to handle the quantitative association rules mining. The main contributions include： （1） Propose a new method to normalize the quantitative values； （2） Propose a method to assign a weight for each attribute to reflect the values distribution； （3） Extend the weight-based association model to tackle the quantitative values in association rules without partition； （4） Design a integrated and uniform method to mine the traditional Boolean association rules and quantitative association rules； Experiments show the effectiveness and linear scalability of the new method on time consuming.

Key words: quantitative association rule, MPSQAR algorithm, loss of semantic information