The　association　categorization　technology　based　on　frequent　patterns　is　recently　presented,　which　build　the　classification　rules　by　frequent　patterns　in　various　categories　and　classify　the　new　text　employing　these　rules.　But　the　current　association　classification　methods　exist　shortage　in　two　aspects　when　it　is　applied　to　classify　text　data:　one　is　the　method　ignored　the　information　about　word＇s　frequency　in　a　text　;　the　other　is　the　method　need　pruning　rules　when　the　mass　rules　are　generated,　but　that　lead　to　the　veracity　of　classifying　dropped.　Therefore,　this　paper　present　a　text　categorization　algorithm　based　on　frequent　pattern　with　term　frequency,　and　obtains　higher　performance　than　other　association　categorization　methods　and　some　current　text　classification　methods.　Our　study　provides　evidence　that　association　rule　mining　can　be　used　for　the　construction　of　fast　and　effective　classifiers　for　automatic　text　categorization.