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Trends in Social Network Analysis pp 189–205Cite as

Unsupervised Link Prediction Based on Time Frames in Weighted–Directed Citation Networks

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

Abstract

Link prediction is one of the key rolling issues in the analysis of weighted and directed social network’s evolution according to the temporal information. It tends to guess the likelihood of the connections occurrence between nodes. In addition the link prediction aims to determine the missing links in the network, which uses the state of the network up to a given time for predicting the new links in future. Most of the previous works have deployed to unweighted or undirected networks and for computing the proximity scores only the current state of the network has considered without taking any temporal information into account, which can be point as a limitation in link prediction studies. In this study we try to overcome the above mentioned limitation by analyzing the development of topological measures in a weighted–directed citation network on a specific period of time. For achieving this aim, a time frame based score is proposed for pairs of nodes in different frames of time in the network. Experiments implemented by using unsupervised learning strategy on a weighted–directed citation network show that the proposed method finds satisfactory results and are promising.

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Author information

Authors and Affiliations

  1. Department of Computer Engineering, Fırat University, Elazığ, Turkey

    Mehmet Kaya, Mujtaba Jawed & Ertan Bütün

  2. Department of Computer Science, University of Calgary, Calgary, AB, Canada

    Reda Alhajj

Authors
  1. Mehmet Kaya
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  2. Mujtaba Jawed
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  3. Ertan Bütün
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  4. Reda Alhajj
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Corresponding author

Correspondence to Mehmet Kaya .

Editor information

Editors and Affiliations

  1. Department of Computer Science & Engineering, University of Quebec in Outaouais, Gatineau, QC, Canada

    Rokia Missaoui

  2. Department of Computer Science and Networks, Telecom ParisTech, Paris, France

    Talel Abdessalem

  3. UPMC Univ Paris 06, CNRS LIP6 UMR 7606, Sorbonne Universitès, Paris, France

    Matthieu Latapy

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Kaya, M., Jawed, M., Bütün, E., Alhajj, R. (2017). Unsupervised Link Prediction Based on Time Frames in Weighted–Directed Citation Networks. In: Missaoui, R., Abdessalem, T., Latapy, M. (eds) Trends in Social Network Analysis. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-53420-6_8

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  • DOI: https://doi.org/10.1007/978-3-319-53420-6_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53419-0

  • Online ISBN: 978-3-319-53420-6

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