Many　data　mining　techniques　have　been　proposed　for　mining　useful　patterns　in　text　documents.　However,　how　to　effectively　use　and　update　discovered　patterns　is　still　an　open　research　issue,　especially　in　the　domain　of　text　mining.　Since　most　existing　text　mining　methods　adopted　term-based　approaches,　they　all　suffer　from　the　problems　of　polysemy　and　synonymy.　Over　the　years,　people　have　often　held　the　hypothesis　that　pattern　(or　phrase)-based　approaches　should　perform　better　than　the　term-based　ones,　but　many　experiments　do　not　support　this　hypothesis.　This　paper　presents　an　innovative　and　effective　pattern　discovery　technique　which　includes　the　processes　of　pattern　deploying　and　pattern　evolving,　to　improve　the　effectiveness　of　using　and　updating　discovered　patterns　for　finding　relevant　and　interesting　information.　Substantial　experiments　on　RCV1　data　collection　and　TREC　topics　demonstrate　that　the　proposed　solution　achieves　encouraging　performance.