the final dissimilarity between trajectories that can be further used for clustering or classification tasks. In … the derived dissimilarity yielded good clustering results comparable to DTW. We also demonstrate using real medical data …

clustering procedure aiming at discovering data structures from a multicriteria perspective by defining a dissimilarity measure … clustering expresses a way of grouping objects according to the preference relation used. A good quality final clustering is … obtained by combining the clusterings generated previously using a clustering ensemble technique. …

In this paper, we present a clustering heuristic for solving demand covering models where the objective is to determine …

Clustering is applied in wireless sensor networks for increasing energy efficiency. Clustering methods in wireless … sensor networks are different from those in traditional data mining systems. This paper proposes a novel clustering algorithm … clustering in wireless sensor networks and several evaluation metrics are given. MSTME performs better than already known …

clustering. Preliminary computational experience is given to illustrate the approach. This methodology is part of our current …