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Optimization Techniques for Multiple Centrality Computations

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The Influence of Technology on Social Network Analysis and Mining

Part of the book series: Lecture Notes in Social Networks ((LNSN,volume 6))

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Abstract

A broad range of data has a graph structure, such as the Web link structure, online social networks, or online communities whose members rate each other (reputation systems) or rate items (recommender systems). In these contexts, a common task is to identify important vertices in the graph, e.g., influential users in a social network or trustworthy users in a reputation system, by means of centrality measures. In such scenarios, several centrality computations take place at the same time, as we will explain. With centrality computation being expensive, performance is crucial. While optimization techniques for single centrality computations exist, little attention so far has gone into the computation of several centrality measures in combination. In this paper, we investigate how to efficiently compute several centrality measures at a time. We propose two new optimization techniques and demonstrate their usefulness both theoretically as well as experimentally on synthetic and on real-world data sets.

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Notes

  1. 1.

    www.advogato.org/person/graph.dot

  2. 2.

    www.trustlet.org/datasets/downloaded_epinions/

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Author information

Authors and Affiliations

  1. Digital Enterprise Research Institute (DERI), National University of Ireland, Galway (NUIG), Galway, Ireland

    Christian von der Weth

  2. Institute for Program Structures and Data Organization, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Klemens Böhm & Christian Hütter

Authors
  1. Christian von der Weth
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  2. Klemens Böhm
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  3. Christian Hütter
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Corresponding author

Correspondence to Christian von der Weth .

Editor information

Editors and Affiliations

  1. Department of Computer Engineering, TOBB University, Sogutozu Cad No. 43, Sogutozu Ankara, Turkey

    Tansel Özyer

  2. Computer Science, University of Calgary, University Dr. NW 2500, Calgary, T2N 1N4, Canada

    Jon Rokne

  3. IPSC, European Commission Joint Research Cent., Via Enrico Fermi 2749, Ispra, 21027, Italy

    Gerhard Wagner

  4. De Wetstraat 16, Leiden, 2332 XT, Netherlands

    Arno H.P. Reuser

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von der Weth, C., Böhm, K., Hütter, C. (2013). Optimization Techniques for Multiple Centrality Computations. In: Özyer, T., Rokne, J., Wagner, G., Reuser, A. (eds) The Influence of Technology on Social Network Analysis and Mining. Lecture Notes in Social Networks, vol 6. Springer, Vienna. https://doi.org/10.1007/978-3-7091-1346-2_2

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  • DOI: https://doi.org/10.1007/978-3-7091-1346-2_2

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  • Print ISBN: 978-3-7091-1345-5

  • Online ISBN: 978-3-7091-1346-2

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