Improving Information Centrality of a Node in Complex Networks by Adding Edges

Abstract

The problem of increasing the centrality of a network node arises in many practical applications. In this paper, we study the optimization problem of maximizing the information centrality Iv of a given node v in a network with n nodes and m edges, by creating k new edges incident to v. Since Iv is the reciprocal of the sum of resistance distance Rv between v and all nodes, we alternatively consider the problem of minimizing Rv by adding k new edges linked to v. We show that the objective function is monotone and supermodular. We provide a simple greedy algorithm with an approximation factor (1 − 1/e) and O(n^3) running time. To speed up the computation, we also present an algorithm to compute (1 − 1/e − epsilon) approximate resistance distance Rv after iteratively adding k edges, the running time of which is Otilde(mk*epsilon^−2) for any epsilon > 0, where the Otilde(·) notation suppresses the poly(log n) factors. We experimentally demonstrate the effectiveness and efficiency of our proposed algorithms.

Cite

Text

Shan et al. "Improving Information Centrality of a Node in Complex Networks by Adding Edges." International Joint Conference on Artificial Intelligence, 2018. doi:10.24963/IJCAI.2018/491

Markdown

[Shan et al. "Improving Information Centrality of a Node in Complex Networks by Adding Edges." International Joint Conference on Artificial Intelligence, 2018.](https://mlanthology.org/ijcai/2018/shan2018ijcai-improving/) doi:10.24963/IJCAI.2018/491

BibTeX

@inproceedings{shan2018ijcai-improving,
  title     = {{Improving Information Centrality of a Node in Complex Networks by Adding Edges}},
  author    = {Shan, Liren and Yi, Yuhao and Zhang, Zhongzhi},
  booktitle = {International Joint Conference on Artificial Intelligence},
  year      = {2018},
  pages     = {3535-3541},
  doi       = {10.24963/IJCAI.2018/491},
  url       = {https://mlanthology.org/ijcai/2018/shan2018ijcai-improving/}
}