email granulation based on distributed-interval type-2 fuzzy set methodologies
Hooman Tahayori, Andrea Visconti, Giovanni Degli Antoni · 2007 IEEE International Conference on Granular Computing (GRC 2007) · 2007
This paper proposes a dynamic model to classify incoming emails into five granules namely, spam, suspicious-spam, suspicious, suspicious-non-spam and non-spam, using distributed-interval type-2 fuzzy set methodologies. Toward this end we have used the concept of general intervals and applied the distributed intervals in interval type-2 fuzzy sets. The method confirmed that, the process of spam filtering is rather intellectual than statistical and moreover some different methods should be used complementarity to get to the higher precision.