In　this　paper,　a　new　blogger＇s　interest　mining　module　is　proposed,　which　is　based　on　Chinese　text　classification.　In　fact,　the　problem　of　the　interest　mining　is　transformed　into　the　problem　of　Chinese　text　categorization.　Before　the　Chinese　text　categorization,　the　text　is　pre-processed　for　the　text　representation.　The　Chinese　text　is　represented　in　vector　space　model　and　classified　by　support　vector　machine　classification,　while　filter　algorithm　which　filters　the　unrelated　interest　text　is　proposed.　After　the　filtering,　the　text　can　get　it＇s　interest　category.　Finally　the　new　module　has　been　made　use　of　to　carry　out　an　interest　mining　experiment,　and　the　other　experiment　which　has　not　filter　algorithm　is　also　carried　in　order　to　compare　with　the　new　module.　The　two　experimental　results　show　that　the　support　vector　machine　is　a　effective　algorithm,　and　the　comparing　data　of　the　two　experiments　shows　that　new　module　make　the　interest　mining　more　effective.　©　2011　Springer-Verlag　Berlin　Heidelberg.