Complexity Reduction in Graphs: A User Centric Approach to Graph Exploration

Author Tim Grube, Florian Volk, Max Mühlhäuser, Suhas Bhairav, Vinay Sachidananda, Yuval Elovici
Date October 2017
Kind Inproceedings
Book titleto appear at: 10th International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services
Research Areas CYSEC, privacy trust, Telecooperation, - SST - Area Smart Security and Trust, - SSI - Area Secure Smart Infrastructures, SPIN: Smart Protection in Infrastructures and Networks, Fachbereich Informatik, CRISP
Abstract Human exploration of large graph structures be- comes increasingly difficult with growing graph sizes. A visual representation of such large graphs, for example, social networks and citational networks, has to find a trade-off between showing details in a magnified view and the overall graph structure. Displaying these both aspects at the same time results in an overloaded visualization that is inaccessible for human users. In this paper, we present a new approach to address this issue by combining and extending graph-theoretic properties with com- munity detection algorithms. Our approach is semi-automated and non-destructive. The aim is to retain core properties of the graph while–at the same time–hiding less important side information from the human user. We analyze the results yielded by applying our approach to large real-world network data sets, revealing a massive reduction of displayed nodes and links. 
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