This work presents the use of sensor stream reduction algorithms in clustered wireless sensor networks (WSNs), where the cluster head node is responsible to reduce the amount of d...
-This paper describes the use of a Fuzzy Cognitive Map (FCM) to model disaster reconstruction, based on data collected from the cities of BAM and Baravat. The extended fuzzy cognit...
Abstract. Clustering is a widely used unsupervised data analysis technique in machine learning. However, a common requirement amongst many existing clustering methods is that all p...
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Semi-supervised clustering uses the limited background knowledge to aid unsupervised clustering algorithms. Recently, a kernel method for semi-supervised clustering has been introd...