Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11779/1148
Title: | An efficient linear programming based method for the influence maximization problem in social networks | Authors: | Güney, Evren | Keywords: | Influence maximization Stochastic optimization Sample average approximation Pipage method |
Publisher: | Elsevier | Source: | Güney, E. (November 01, 2019). An efficient linear programming based method for the influence maximization problem in social networks. Information Sciences, 503, 589-605. | Abstract: | The influence maximization problem (IMP) aims to determine the most influential individuals within a social network. In this study first we develop a binary integer program that approximates the original problem by Monte Carlo sampling. Next, to solve IMP efficiently, we propose a linear programming relaxation based method with a provable worst case bound that converges to the current state-of-the-art 1-1/e bound asymptotically. Experimental analysis indicate that the new method is superior to the state-of-the-art in terms of solution quality and this is one of the few studies that provides approximate optimal solutions for certain real life social networks. | URI: | https://hdl.handle.net/20.500.11779/1148 https://doi.org/10.1016/j.ins.2019.07.043 |
ISSN: | 0020-0255 |
Appears in Collections: | Endüstri Mühendisliği Bölümü koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
evrenguney_1.pdf Until 2040-11-07 | Yazar Sürümü - Makale | 2.07 MB | Adobe PDF | View/Open Request a copy |
CORE Recommender
SCOPUSTM
Citations
23
checked on Aug 1, 2024
WEB OF SCIENCETM
Citations
23
checked on Jun 23, 2024
Page view(s)
6
checked on Jun 26, 2024
Google ScholarTM
Check
Altmetric
Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.