{"title":"New Influence Maximization Algorithm Research in Big Graph","authors":"Guigang Zhang, Sujie Li, Jian Wang, Ping Liu, Yibing Chen, Yunchuan Luo","doi":"10.1109/WISA.2017.50","DOIUrl":null,"url":null,"abstract":"Influence maximization is a very hot research in social network. However, it is difficult to find a good algorithm to keep balance between the time complexity and computing result' accuracy. In order to solve this problem, in this paper, we propose two new algorithms. Firstly, we present a heuristic algorithm based on the greedy algorithm, which can reduce the time complexity a lot and it will have a good result, too. Then, we present another new algorithm. We use the k-means idea to solve the IM problem. We use the k-means idea to find s seed nodes. At the same time, we prove these two new algorithms.","PeriodicalId":204706,"journal":{"name":"2017 14th Web Information Systems and Applications Conference (WISA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 14th Web Information Systems and Applications Conference (WISA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WISA.2017.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Influence maximization is a very hot research in social network. However, it is difficult to find a good algorithm to keep balance between the time complexity and computing result' accuracy. In order to solve this problem, in this paper, we propose two new algorithms. Firstly, we present a heuristic algorithm based on the greedy algorithm, which can reduce the time complexity a lot and it will have a good result, too. Then, we present another new algorithm. We use the k-means idea to solve the IM problem. We use the k-means idea to find s seed nodes. At the same time, we prove these two new algorithms.