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Double bounded rough set, tension measure, and social link prediction
, S.K. Pal
Published in Institute of Electrical and Electronics Engineers Inc.
2018
Volume: 5
   
Issue: 3
Pages: 841 - 853
Abstract
This paper describes a new approach of viewing a social relation as a string with various forces acting on it. Accordingly, a tension measure for a relation is defined. Various component forces of the tension measure are identified based on the structural information of the network. A new variant of rough set, namely, double bounded rough set, is developed in order to define these forces mathematically. It is revealed experimentally with synthetic and real-world data that positive and negative tension characterizes, relatively, the presence and absence of a physical link between two nodes. An algorithm based on tension measure is proposed for link prediction. Superiority of the algorithm is demonstrated on nine real-world networks, which include four temporal networks. The source code for calculating tension measure and link prediction algorithm is publicly available at https://gitlab.com/suman5/social-tension-measure. © 2014 IEEE.
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Figures & Tables (17)
  • Figure-0
    Fig. 1. Illustration: double bounded rough set.
  • Figure-1
    Fig. 2. Example network.
  • Figure-2
    Fig. 4. Network with T (p, q) = (−1).
  • Figure-3
    Fig. 3. Network with T (p, q) = 1.
  • Figure-4
    Fig. 5. Distribution of T . (a) Linked pairs of data ... Expand
  • Figure-5
    TABLE I SYNTHETIC DATA SETS
  • Figure-6
    Fig. 6. Distribution of different forces. (a) Linked pairs ... Expand
  • Figure-7
    TABLE II REAL-WORLD DATA SETS
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About the journal
JournalData powered by SciSpaceIEEE Transactions on Computational Social Systems
PublisherData powered by SciSpaceInstitute of Electrical and Electronics Engineers Inc.
ISSN2329924X