Reading　and　literature　exploration　are　important　tasks　of　scientific　research.　However,　conventional　retrieval　systems　provide　limited　support　for　these　tasks　by　concentrating　on　identifying　relevant　materials.　New　generation　systems　should　provide　additional　support　functionality　by　focusing　on　analyzing　and　organizing　the　retrieved　materials.　A　framework　of　literature　exploration　support　systems　is　proposed.　Techniques　of　granular　computing　are　used　to　construct　granular　knowledge　structures　from　the　contents,　structures,　and　usages　of　scientific　documents.　The　granular　knowledge　structures　provide　a　high　level　understanding　of　scientific　literature　and　hints　regarding　what　has　been　done　and　what　needs　to　be　done.　As　a　demonstration,　we　examine　granular　knowledge　structures　obtained　from　an　analysis　of　papers　from　two　rough　sets　related　conferences.