E-mail　messages　can　be　modeled　as　semi-structured　documents　that　consist　of　a　set　of　classes　and　a　number　of　variable　length　free-text.　Thus,　many　text　mining　techniques　can　be　used　to　develop　a　personal　e-mail　filtering　and　management　system.　This　paper　addresses　a　text　mining　agents　based　architecture,　in　which　two　kinds　of　text　mining　agents:　USPC　(uncertainty　sampling　based　probabilistic　classifier)　and　R2L　(rough　relation　learning)　are　used　cooperatively,　for　personal　e-mail　filtering　and　management.　©　Springer-Verlag　Berlin　Heidelberg　2002.