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Using Random Walks to Generate Associations between Objects

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  • Muhammed A Yildirim
  • Michele Coscia

Abstract

Measuring similarities between objects based on their attributes has been an important problem in many disciplines. Object-attribute associations can be depicted as links on a bipartite graph. A similarity measure can be thought as a unipartite projection of this bipartite graph. The most widely used bipartite projection techniques make assumptions that are not often fulfilled in real life systems, or have the focus on the bipartite connections more than on the unipartite connections. Here, we define a new similarity measure that utilizes a practical procedure to extract unipartite graphs without making a priori assumptions about underlying distributions. Our similarity measure captures the relatedness between two objects via the likelihood of a random walker passing through these nodes sequentially on the bipartite graph. An important aspect of the method is that it is robust to heterogeneous bipartite structures and it controls for the transitivity similarity, avoiding the creation of unrealistic homogeneous degree distributions in the resulting unipartite graphs. We test this method using real world examples and compare the obtained results with alternative similarity measures, by validating the actual and orthogonal relations between the entities.

Suggested Citation

  • Muhammed A Yildirim & Michele Coscia, 2014. "Using Random Walks to Generate Associations between Objects," PLOS ONE, Public Library of Science, vol. 9(8), pages 1-9, August.
  • Handle: RePEc:plo:pone00:0104813
    DOI: 10.1371/journal.pone.0104813
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    References listed on IDEAS

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    1. Yang-Yu Liu & Jean-Jacques Slotine & Albert-László Barabási, 2011. "Controllability of complex networks," Nature, Nature, vol. 473(7346), pages 167-173, May.
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    Cited by:

    1. Alje van Dam, 2019. "Diversity and its decomposition into variety, balance and disparity," Papers 1902.09167, arXiv.org, revised Feb 2019.
    2. Ljubica Nedelkoska & Dario Diodato & Frank Neffke, 2018. "Is Our Human Capital General Enough to Withstand the Current Wave of Technological Change?," CID Working Papers 93a, Center for International Development at Harvard University.
    3. Alje van Dam, 2019. "Diversity and its decomposition into variety, balance and disparity," Papers in Evolutionary Economic Geography (PEEG) 1913, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised May 2019.
    4. Chen, Xue & Jiao, Pengfei & Yu, Yandong & Li, Xiaoming & Tang, Minghu, 2019. "Toward link predictability of bipartite networks based on structural enhancement and structural perturbation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C), pages 1-1.

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