<p style='text-indent:20px;'>This work proposes a novel technique for clustering multimodal data according to their information content. Statistical correlations present in that contain similar are exploited perform the task. Specifically, multiset canonical correlation analysis is equipped with norm-one regularization mechanisms identify clusters within different types of share same A pe...

Knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. Due to properly converting the task of optimization to an equivalent...

One of the most important issues in urban planning is developing sustainable public transportation. The basic condition for this purpose is analyzing current condition especially based on data. Data mining is a set of new techniques that are beyond statistical data analyzing. Clustering techniques is a subset of it that one of it’s techniques used for analyzing passengers’ trip. The result of...

In this paper, a new method is proposed for solving the data clustering problem using Cat Swarm Optimization (CSO) algorithm based on chaotic behavior. The problem of data clustering is an important section in the field of the data mining, which has always been noted by researchers and experts in data mining for its numerous applications in solving real-world problems. The CSO algorithm is one ...