Since advanced technologies via social media, internet, virtual communities and networks internet of things (IoT), there are more multi-view data to be collected. Multi-view clustering is a substantial tool as natural design for data. K-means (KM) (single-view) had been extended handling data, called KM (MV-KM). In the literature, most MV-KM algorithms reported influenced by initializations als...

-In this paper targeted a variety of techniques, tactics and distinctive areas of the studies that are useful and marked because the crucial discipline of information mining technologies. The overall purpose of the system of statistics mining is to extract beneficial facts from a large set of information and changing it right into a shape that is comprehensible for in addition use. Clustering i...

In this paper, we propose a new clustering algorithm to cluster data. The proposed algorithm adopts a new non-metric measure based on the idea of “symmetry”. The detected clusters may be a set of clusters of different geometrical structures. Three data sets are tested to illustrate the effectiveness of our proposed algorithm.

The Cooperative Target Observation (CTO) problem has been of great interest in the multi-agents and robotics literature due to the problem being at the core of a number of applications including surveillance. In CTO problem, the observer agents attempt to maximize the collective time during which each moving target is being observed by at least one observer in the area of interest. However, mos...

In this paper, we evaluate the player segmentation for trajectory estimation in soccer games. In order to estimate the field trajectories of players in soccer games, we should accurately locate the foot positions of players in each soccer image and transform them into those in the soccer field. However, we cannot always segment the players completely, since players are often motion-blurred due ...

In this paper, the well-known k-means algorithm for searching for a locally 12 optimal partition of the setA ⊂ R is analyzed in the case if some data points occur on the 13 border of two or more clusters. For this special case, a useful strategy by implementation 14 of the k-means algorithm is proposed. 15