{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,25]],"date-time":"2025-10-25T12:27:56Z","timestamp":1761395276739},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,7]]},"abstract":"<jats:p>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 \u2212 1\/e) and O(n^3) running time. To speed up the computation, we also present an algorithm to compute (1 \u2212 1\/e \u2212 epsilon) approximate resistance distance Rv after iteratively adding k edges, the running time of which is Otilde(mk*epsilon^\u22122) for any epsilon &gt; 0, where the Otilde(\u00b7) notation suppresses the poly(log n) factors. We experimentally demonstrate the effectiveness and efficiency of our proposed algorithms.<\/jats:p>","DOI":"10.24963\/ijcai.2018\/491","type":"proceedings-article","created":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:49:10Z","timestamp":1530755350000},"page":"3535-3541","source":"Crossref","is-referenced-by-count":13,"title":["Improving Information Centrality of a Node in Complex Networks by Adding Edges"],"prefix":"10.24963","author":[{"given":"Liren","family":"Shan","sequence":"first","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"},{"name":"School of Computer Science, Fudan University"}]},{"given":"Yuhao","family":"Yi","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"},{"name":"School of Computer Science, Fudan University"}]},{"given":"Zhongzhi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Shanghai Key Laboratory of Intelligent Information Processing, Fudan University"},{"name":"School of Computer Science, Fudan University"}]}],"member":"10584","event":{"number":"27","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"acronym":"IJCAI-2018","name":"Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}","start":{"date-parts":[[2018,7,13]]},"theme":"Artificial Intelligence","location":"Stockholm, Sweden","end":{"date-parts":[[2018,7,19]]}},"container-title":["Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2018,7,5]],"date-time":"2018-07-05T01:53:22Z","timestamp":1530755602000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2018\/491"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2018,7]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2018\/491","relation":{},"subject":[],"published":{"date-parts":[[2018,7]]}}}