{"title":"大图中新的影响最大化算法研究","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":"{\"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}","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}
New Influence Maximization Algorithm Research in Big Graph
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.