An attribute can be Boolean or quantitative. There are lots of systems and methods for mining Boolean association rules but few for quantitative. Mapping quantitative attributes into Boolean attributes is a convenient and efficient way. In this paper, a new clustering algorithm is presented. Quantitative attribute values are partitioned into intervals according to the distribution of them in database. Then the intervals are mapped into Boolean attributes. In this way, quantitative rules can be mined by using the techniques of mining Boolean association rules.