DPClusSBO: An integrated software for clustering of simple and bipartite graphs

oleh: Mohammad Bozlul Karim, Shigehiko Kanaya, Md. Altaf-Ul-Amin

Format: Article
Diterbitkan: Elsevier 2021-12-01

Deskripsi

Network analysis particularly graph clustering has become a useful and important technique in data mining applications. It provides a global view of data structure where densely connected objects are grouped based on their common properties. Over the past decade, various simple graph clustering and biclustering techniques have been widely used but the implementation of those algorithms remains limited. In this work, we present a new integrated software implementing the DPClusO and BiClusO algorithms using Java to be utilized for simple and bipartite graph clustering. Our aim is to provide an open-source tool with lots of user-friendly options to delve into network data. This tool will provide the user with GUI based facilities for simple and bipartite graph clustering along with filtering and amalgamation of clusters, hierarchical node analysis, node distribution among cluster set and visualization of all or partial portion of a big cluster set. We name this tool DPClusSBO because this can be used to perform Density Periphery based Clustering of Simple and Bipartite graphs with Overlapping property.