The hierarchical clustering methods based on vertex similarity have the advantage that global evaluation can be incorporated for community discovery. Vertex similarity metric is the most important part of these methods. However, the existing methods do not perform well for community discovery compared with the state-ofthe-art algorithms. In this paper, we propose a new vertex similarity metric ...

Modern day science presentsmany challenges to data analysts. Advances in data collection provide very large (number of observations and number of dimensions) data sets. In many areas of data analysis an informative task is to find natural separations of data into homogeneous groups, i.e. clusters. In this paper we study the asymptotic behavior of hierarchical clustering in situations where both...

We consider the problem of constructing an an optimal-weight tree from the 3 `

in recent years, underactuated nonlinear dynamic systems trajectory tracking, such as space robots and manipulators with structural flexibility, has become a major field of interest due to the complexity and high computational load of these systems. hierarchical sliding mode control has been investigated recently for these systems; however, the instability phenomena will possibly occur, especia...

This paper introduces a variant of agglomerative hierarchical clustering techniques. The new technique is used for categorizing character shapes (allographs) in large data sets of handwriting into a hierarchical structure. Such a technique may be used as the basis for a systematic naming scheme of character shapes. Problems with existing methods are described and the proposed method is explaine...

We propose a simple clustering framework on graphs encoding pairwise data similarities. Unlike usual similarity-based methods, the approach softly assigns data to clusters in a probabilistic way. More importantly, a hierarchical clustering is naturally derived in this framework to gradually merge lower-level clusters into higher-level ones. A random walk analysis indicates that the algorithm ex...

the main objective of this study was to investigate how months cluster in any thermal regions based on temperature. for this purpose, the mean of daily temperature data have been provided using 620 synoptic and climatology stations. then, mean temperature was converted for any station, based on solar calendar, and maps of mean daily temperature have been interpolated using kriging method. spati...

The organizational structure is usually defined using the best experience and there is a minimum of formal approach involved. This paper shows the possibilities of the theory of concept analysis that can help to understand organizational structure based on solid mathematical foundations. This theory is extended by the concept of knowledge sharing and diversity that enables to evaluate the organ...

Recently a great deal of attention has been paid to the design of hierarchical shared memory cluster system. Cluster computing has made hierarchical computing systems increasingly common as target environment for large-scale scientific computations. This paper proposes hierarchical shared memory cluster architecture with load balancing and fault tolerance. Hierarchies of shared memory and cache...