%0 Journal Article
%T 社交网络中求最小正影响支配集的改进算法<br>An Improved Algorithm for Finding Minimum Positive Influence Dominating Sets in Social Networks
%A 麦飞
%A 陈卫东   &lt
%A br&gt
%A MAI Fei
%A CHEN Weidong
%J 华南师范大学学报（自然科学版）
%D 2016
%R 10.6054/j.jscnun.2016.05.004
%X 网络中求解最小正影响支配集的问题已经被证明是NP难问题，且已有性能较好的贪心求解算法．通过分析现有的贪心近似算法（Wang-Greedy）和贪心启发式算法(Raei-Greedy)，融合其贪心策略，提出了1个改进的贪心近似算法(Hybrid-Greedy)．理论分析表明，Hybrid-Greedy仍保持Wang-Greedy的近似比性能和时间复杂度．在一些较大规模的真实社交网络实例中的实验研究表明，Hybrid-Greedy在这些社交网络中所得解的质量较Wang-Greedy和Raei-Greedy有明显提高．<br>： The problem of finding the minimum positive influence dominating set in a given network has been proved to be NP-hard, and there are greedy algorithms with good performance to solve it. An existing greedy approximation algorithm (Wang-Greedy) and a heuristic algorithm (Raei-Greedy) are analyzed. Accordingly, an improved greedy approximation algorithm (Hybrid-Greedy) to find the minimum positive influence dominating sets in social networks is proposed. It is shown theoretically that hybrid-Greedy remains the same approximation ratio and time complexity as Wang-Greedy. Experimental results on some large real-world social network instances show that Hybrid-Greedy yields better solutions than Wang-Greedy and Raei-Greedy for these social network instances
%K 正影响支配集
%K NP难度
%K 近似算法
%K 贪心算法
%K 社交网络
%K &lt
%K br&gt
%K positive influence dominating set
%K NP-hard
%K approximation algorithm
%K greedy algorithm
%K social network
%U http://journal.scnu.edu.cn:8080/jwk_xbzrb/CN/abstract/abstract3892.shtml