东南大学学报（自然科学版）2016，Vol.46Issue(5)：950-956,7.DOI:10.3969/j.issn.1001-0505.2016.05.009
基于启发式和贪心策略的社交网络影响最大化算法
Mixed heuristic and greedy strategies based algorithm for influence maximization in social networks
摘要
Abstract
To solve the imbalance problem between the influence scope and the running time of the classic influence maximization algorithms,a mixed heuristic and greedy strategies based algorithm (MHG algorithm)for influence maximization in social networks is proposed.The algorithm consid-ers the advantages on the greedy and heuristic strategies,and the selection of seed nodes is divided into two steps.First,the candidate node set is selected by the heuristic algorithm,and then the final seed node set is deduced from this set by the greedy algorithm.The results show that the MHG algo-rithm is superior in influence scope compared with current heuristic algorithms.It exhibits the ap-proximate effect of the greedy algorithm,but the running time is obviously lower.Therefore,the MHG algorithm achieves a good balance between the influence scope and the running time.Moreo-ver,the MHG algorithm presents a stable influence scope when running on real data sets and differ-ent dissemination models,showing its scalability in large scale social networks.关键词
社交网络/影响最大化/贪心算法/启发式算法/传播模型Key words
social networks/influence maximization/greedy algorithm/heuristic algorithm/dis-semination model分类
信息技术与安全科学引用本文复制引用
曹玖新,闵绘宇,徐顺,刘波..基于启发式和贪心策略的社交网络影响最大化算法[J].东南大学学报（自然科学版）,2016,46(5):950-956,7.基金项目
国家自然科学基金资助项目（61272531，61472081）、江苏省科技厅产学研前瞻性联合研究资助项目（SBY2014020139）． （）
