Work

Topological Filtering for Visual Data Mining and Analysis of Complex Networks

Year: 2023

Type: preprint

Abstract: The discovery of small world and scale free properties of many real world networks has revolutionized the way we study, analyze, model and process networks. An important way to analyze these complex networks is to visualize them using graph layout algorithms. Due to their large size and complex connectivity, it is difficult to make deductions from the visual representation of these networks. In this paper, we present a method for interactive analysis of large graphs based on topological filtering, network metrics and visualization. We analyze a number of real world networks and draw interesting conclusions using the proposed method.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2304.01896

Author: Zaidi, Faraz

Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Centre Inria de l'université de Bordeaux, Laboratoire Bordelais de Recherche en Informatique

Language: English

Topic: Data Visualization and Analytics

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W4362656033

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