Computer Science ›› 2020, Vol. 47 ›› Issue (5): 7-13.doi: 10.11896/jsjkx.200200071
Special Issue: Theoretical Computer Scinece
• Theoretical Computer Science • Previous Articles Next Articles
KONG Fang1, LI Qi-zhi2, LI Shuai3
CLC Number:
[1]KEMPE D,KLEINBERG J M,TARDOS É.Maximizing thespread of influence through a social network[J].Theory of Computing,2015,11(4):105-147. [2]CENTOLA D,MACY M.Complex contagion and the weakness of long ties[J].American Journal of Sociology,2007,113(3):702-734. [3]WANG C,CHEN W,WANG Y.Scalable influence maximization for independent cascade model in large-scale social networks[J].Data Mining and Knowledge Discovery,2012,25(3):545-576. [4]CHEN W,YUAN Y,ZHANG L.Scalable influence maximization in social networks under the linear threshold Model[C]//Proceedings of the 10th IEEE International Conference on Data Mining (ICDM).2010:88-97. [5]CHEN W,LAKSHMANAN L V S,CASTILLO C.Information and Influence Propagation in Social Networks[M].Morgan & Claypool Publishers,2013. [6]LESKOVEC J,KRAUSE A,GUESTIN C,et al.Cost-effective outbreakdetection in networks[C]//Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining (KDD).2007:420-429. [7]GOYAL A,LU W,LAKSHMANAN L V S.CELF++: Optimizing the greedy algorithm for influence maximization in social networks (poster entry)[C]//Proceedings of the 20th International World Wide Web Conference (WWW).2011:47-48. [8]KIMURA M,SAITO K,NAKANO R.Extracting influentialnodes for information diffusion on a social network[C]//Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI).2007:1371-1376. [9]CHEN W,WANG Y, YANG S.Efficient influence maximization in social networks[C]//Proceedings of the 15thACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).2009:199-208. [10]GOYAL A,LU W,LAKSHMANAN L V S.SIMPATH: An efficient algorithm for influence maximization under the linear threshold model[C]// Proceedings of the 11th IEEE International Conference on Data Mining (ICDM).2011:211-220. [11]JUNG K,HEO W,CHEN W.IRIE: Scalable and robust influence maximization in social networks[C]//Proceedings of the 12th IEEE International Conference on Data Mining (ICDM).2012:918-923. [12]KIM J,KIM S K,YU H.Scalable and parallelizable processing of influence maximization for large-scalesocial networks[C]//Proceedings of the 29th IEEE International Conference on Data Engineering (ICDE).2013:266-277. [13]WANG Y,CONG G,SONG G,et al.Community-based greedyalgorithm for mining top-K influential nodes in mobile social networks[C]//Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).2010:1039-1048. [14]JIANG Q,SONG G,CONG G,et al.Simulated annealing based influence maximization in social networks[C]//Proceedings of the 25th AAAI Conference on Artificial Intelligence (AAAI).2011:127-132. [15]BORGS C,BRAUTBAR M,CHAYES J,et al.Maximizing social influence in nearly optimal time[C]//Proceedings of the 25th ACM-SIAM Symposium on Discrete Algorithms (SODA).2014:946-957. [16]TANG Y,XIAO X,SHI Y.Influence maximization: near-optimal time complexity meets practical efficiency[C]//Proceedings of ACM SIGMOD Conference (SIGMOD).2014:75-86. [17]TANG Y,SHI Y,XIAO X.Influence maximization in near-li-near time: A martingale approach[C]//Proceedings of ACM SIGMOD Conference (SIGMOD).2015:1539-1554. [18]CHEN W.An issue in the martingale analysis of the influence maximization algorithm IMM[J].arXiv:1808.09363,2018. [19]NGUYEN H T,THAI M T,DINH T N.Stop-and-Stare: Optimal sampling algorithms for viral marketing in billion- scale networks[C]// Proceedings of the 2016 International Conference on Management of Data (SIGMOD).2016:695-710. [20]NGUYEN H T,NGUYEN T P,PHAN N H,et al.Importance sketching of influence dynamics in billion-scale networks[C]//Proceedings of the 2017 IEEE International Conference on Data Mining (ICDM).2017. [21]AUDIBERT J-Y,BUBECK S,LUGOSI G.Minimax policies for combinatorial prediction games[C]//Proceedings of the 24th Annual Conference on Learning Theory (COLT).2011. [22]LEI S,MANIU S,MO L,et al.Online influence maximization[C]//Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).2015:645-654. [23]CHEN W,WANG Y,YUAN Y,et al.Combinatorial multi-armed bandit and its extension toprobabilistically triggered arms[J].Journal of Machine Learning Research,2016,17(50):1-33. [24]AUER P,CESA-BIANCHI N,FISCHER P.Finite-time analysis of the multiarmed bandit problem[J].Machine Learning Journal,2002,47(2/3):235-256. [25]WANG Q,CHEN W.Improving regret bounds for combinatorial semi-bandits with probabilistically triggered arms and its applications[C]//Proceedings of the 30 th Annual Conference on Neural Information Processing Systems (NeurIPS).2017. [26]WEN Z,KVETON B,VALKO M,et al.Online influence maximization under independent cascade modelwith semi-bandit feedback[C]//Proceedings of the 30th Annual Conference on Neural Information Processing Systems (NeurIPS).2017. [27]WU Q Y,LI Z G,WANG H Z,et al.Factorization Bandits for Online Influence Maximization[C]//Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Disco-very and Data Mining (KDD).2019: 636-646. [28]VASWANI S,LAKSHMANAN L V S,SCHMIDT M.Influence maximization with bandits[C]//NIPS Workshop on Networks in the Social and Information Sciences.2015. [29]BAO Y X,WANG X K,WANG Z,et al,Online influence maximization in non-stationary social networks[C]//IEEE/ACM 24th International Symposium on Quality of Service (IWQoS).2016. [30]VASWANI S,KVETON B,WEN Z,et al.Diffusion independent semi-bandit influence maximization[C]//Proceedings of the 34 th International Conference on Machine Learning (ICML).2017. [31]CARPENTIER A,VALKO M.Revealing graph bandits formaximizing local influence[C]//International Conference on Artificial Intelligence and Statistics.2016. [32]LUGOSI G,NEU G,OLKHOVSKAYA J.Online influencemaximization with local observations[C]// Proceedings of the 30th International Conference on Algorithmic Learning Theory.2019:557-580. [33]AUER P,CESA-BIANCHI N,FREUND Y,et al.The non-stochastic multi-armed bandit problem[J].SIAM Journal on Computing,2002,32(1):48-77. [34]LINT,LI J,CHEN W,Stochastic Online Greedy Learning with Semi-bandit Feedbacks[C]//Proceedings of the 28th Annual Conference on Neural Information Processing Systems (NeurIPS).2015:352-360. [35]LICHAO S,WEIRAN H,PHILIP S Y,et al.Multi-Round Influence Maximization[C]// Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD).2018: 2249-2258. |
[1] | WANG Jian, PENG Yu-qi, ZHAO Yu-fei, YANG Jian. Survey of Social Network Public Opinion Information Extraction Based on Deep Learning [J]. Computer Science, 2022, 49(8): 279-293. |
[2] | WEI Peng, MA Yu-liang, YUAN Ye, WU An-biao. Study on Temporal Influence Maximization Driven by User Behavior [J]. Computer Science, 2022, 49(6): 119-126. |
[3] | YU Ai-xin, FENG Xiu-fang, SUN Jing-yu. Social Trust Recommendation Algorithm Combining Item Similarity [J]. Computer Science, 2022, 49(5): 144-151. |
[4] | CHANG Ya-wen, YANG Bo, GAO Yue-lin, HUANG Jing-yun. Modeling and Analysis of WeChat Official Account Information Dissemination Based on SEIR [J]. Computer Science, 2022, 49(4): 56-66. |
[5] | ZUO Yuan-lin, GONG Yue-jiao, CHEN Wei-neng. Budget-aware Influence Maximization in Social Networks [J]. Computer Science, 2022, 49(4): 100-109. |
[6] | GUO Lei, MA Ting-huai. Friend Closeness Based User Matching [J]. Computer Science, 2022, 49(3): 113-120. |
[7] | SHAO Yu, CHEN Ling, LIU Wei. Maximum Likelihood-based Method for Locating Source of Negative Influence Spreading Under Independent Cascade Model [J]. Computer Science, 2022, 49(2): 204-215. |
[8] | WANG Jian, WANG Yu-cui, HUANG Meng-jie. False Information in Social Networks:Definition,Detection and Control [J]. Computer Science, 2021, 48(8): 263-277. |
[9] | TAN Qi, ZHANG Feng-li, WANG Ting, WANG Rui-jin, ZHOU Shi-jie. Social Network User Influence Evaluation Algorithm Integrating Structure Centrality [J]. Computer Science, 2021, 48(7): 124-129. |
[10] | ZHANG Ren-zhi, ZHU Yan. Malicious User Detection Method for Social Network Based on Active Learning [J]. Computer Science, 2021, 48(6): 332-337. |
[11] | BAO Zhi-qiang, CHEN Wei-dong. Rumor Source Detection in Social Networks via Maximum-a-Posteriori Estimation [J]. Computer Science, 2021, 48(4): 243-248. |
[12] | ZHANG Shao-jie, LU Xu-dong, GUO Wei, WANG Shi-peng, HE Wei. Prevention of Dishonest Behavior in Supply-Demand Matching [J]. Computer Science, 2021, 48(4): 303-308. |
[13] | ZHANG Hao-chen, CAI Ying, XIA Hong-ke. Delivery Probability Based Routing Algorithm for Vehicular Social Network [J]. Computer Science, 2021, 48(3): 289-294. |
[14] | YUAN De-yu, CHEN Shi-cong, GAO Jian, WANG Xiao-juan. Intervention Algorithm for Distorted Information in Online Social Networks Based on Stackelberg Game [J]. Computer Science, 2021, 48(3): 313-319. |
[15] | TAN Qi, ZHANG Feng-li, ZHANG Zhi-yang, CHEN Xue-qin. Modeling Methods of Social Network User Influence [J]. Computer Science, 2021, 48(2): 76-86. |
|