Spatial clustering is an active research area in spatial data mining with various methods reported. In this paper, we compare two density-based methods, DBSCAN and DBRS. First, we ...
The goal of spatial co-location pattern mining is to find subsets of spatial features frequently located together in spatial proximity. Example co-location patterns include servi...
Clustering partitions a collection of objects into groups called clusters, such that similar objects fall into the same group. Similarity between objects is defined by a distance ...
Venkatesh Ganti, Raghu Ramakrishnan, Johannes Gehr...
Clustering algorithms are employed in many bioinformatics tasks, including categorization of protein sequences and analysis of gene-expression data. Although these algorithms are r...
Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous e...