Rough, fuzzy, interval clustering for web usage mining

Fuzzy C-means (FCM) and Rough K-means (RKM) algorithms are two popular soft clustering algorithms that allow for overlapping clusters. The overlapping clusters can be useful in applications where restrictions imposed by crisp clustering that force assignment of every object to a unique cluster may not be practical. Likewise RKM and FCM, interval set representation of clusters would also generate overlapping clusters. We present and discuss the interval set K-means algorithm (IKM). This paper applies RKM, FCM and IKM algorithms for clustering web visits to an educational site. The experimental comparison highlights various features of these three soft computing algorithms.