  Several methods for triclustering three-dimensional data require the cluster
size or the number of clusters in each dimension to be specified. To address
this issue, the Multi-Slice Clustering (MSC) for 3-order tensor finds signal
slices that lie in a low dimensional subspace for a rank-one tensor dataset in
order to find a cluster based on the threshold similarity. We propose an
extension algorithm called MSC-DBSCAN to extract the different clusters of
slices that lie in the different subspaces from the data if the dataset is a
sum of r rank-one tensor (r > 1). Our algorithm uses the same input as the MSC
algorithm and can find the same solution for rank-one tensor data as MSC.
