Online Algorithm for Clustering with Capacity Constraints

The set of objects having same characteristics are organized in groups and clusters of these objects reformed known as Data Clustering. It is an unsupervisedlearning technique for classification of data. K-means algorithm is widely used and famous ...

Applying graph theory to clustering, we propose a partitional clustering method and a clustering tendency index. No initial assumptions about the data set are requested by the method. The number of clusters and the partition that best fits the data set, ...

In the Categorical Clustering problem, we are given a set of vectors (matrix) $\mathbf{A}=\{{\mathbf{a}}_1,\dots ,{\mathbf{a}}_n\}$ over ${\Sigma }^m$, where $\Sigma$ is a finite alphabet, and integers k and B. The task is to partition $\mathbf{A}$ into k clusters such that the median objective of the clustering in ...${}_{\mathrm{}}{}_{}$$\mathrm{}$${\mathbf{}}_{\mathrm{}}{\mathbf{}}_{}{}^{}$${}_{\mathrm{}}^{}{}_{{}_{}}{}_{}{\mathbf{}}_{}{\mathbf{}}_{}$${}_{}\mathbf{}\mathbf{}$$\mathbf{}$$\mathbf{}$$\mathrm{}\mathrm{}$${\mathrm{}}^{\mathcal{}}{}^{\mathcal{}\mathrm{}}$${}_{}$$\mathrm{}$${\mathrm{}}^{\mathcal{}}{}^{}{}^{\mathcal{}\mathrm{}}$