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Accelerating computation of distance based centrality measures for spatial networks

conference contribution
posted on 2023-05-23, 12:10 authored by Ohara, K, Saito, K, Kimura, M, Motoda, H
In this paper, by focusing on spatial networks embedded in the real space, we first extend the conventional step-based closeness and betweenness centralities by incorporating inter-nodes link distances obtained from the positions of nodes. Then, we propose a method for accelerating computation of these centrality measures by pruning some nodes and links based on the cut links of a given spatial network. In our experiments using spatial networks constructed from urban streets of cities of several types, our proposed method achieved about twice the computational efficiency compared with the baseline method. Actual amount of reduction in computation time depends on network structures. We further experimentally show by examining the highly ranked nodes that the closeness and betweenness centralities have completely different characteristics to each other.

History

Publication title

Proceedings of the 19th International Conference on Discovery Science (DS 2016)

Editors

T Calders, M Ceci & D Malerba

Pagination

376-391

ISBN

978-3-319-46306-3

Department/School

School of Engineering

Publisher

Springer International Publishing

Place of publication

Switzerland

Event title

19th International Conference on Discovery Science 2016 (DS 2016)

Event Venue

Bari, Italy

Date of Event (Start Date)

2016-10-19

Date of Event (End Date)

2016-10-21

Rights statement

Copyright 2016 Springer International Publishing

Repository Status

  • Restricted

Socio-economic Objectives

Information systems, technologies and services not elsewhere classified

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