Dean Eckles, Hossein Esfandiari, Elchanan Mossel, M. Amin Rahimian
{"title":"用昂贵的网络信息播种","authors":"Dean Eckles, Hossein Esfandiari, Elchanan Mossel, M. Amin Rahimian","doi":"10.2139/ssrn.3386417","DOIUrl":null,"url":null,"abstract":"Seeding the most influential individuals based on the contact structure can substantially enhance the extent of a spread over the social network. Most of the influence maximization literature assumes the knowledge of the entire network graph. However, in practice, obtaining full knowledge of the network structure is very costly. We propose polynomial-time algorithms that provide almost tight approximation guarantees using a bounded number of queries to the graph structure. We also provide impossibility results to lower bound the query complexity and show tightness of our guarantees.","PeriodicalId":416173,"journal":{"name":"Proceedings of the 2019 ACM Conference on Economics and Computation","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Seeding with Costly Network Information\",\"authors\":\"Dean Eckles, Hossein Esfandiari, Elchanan Mossel, M. Amin Rahimian\",\"doi\":\"10.2139/ssrn.3386417\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Seeding the most influential individuals based on the contact structure can substantially enhance the extent of a spread over the social network. Most of the influence maximization literature assumes the knowledge of the entire network graph. However, in practice, obtaining full knowledge of the network structure is very costly. We propose polynomial-time algorithms that provide almost tight approximation guarantees using a bounded number of queries to the graph structure. We also provide impossibility results to lower bound the query complexity and show tightness of our guarantees.\",\"PeriodicalId\":416173,\"journal\":{\"name\":\"Proceedings of the 2019 ACM Conference on Economics and Computation\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2019 ACM Conference on Economics and Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3386417\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2019 ACM Conference on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3386417","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Seeding the most influential individuals based on the contact structure can substantially enhance the extent of a spread over the social network. Most of the influence maximization literature assumes the knowledge of the entire network graph. However, in practice, obtaining full knowledge of the network structure is very costly. We propose polynomial-time algorithms that provide almost tight approximation guarantees using a bounded number of queries to the graph structure. We also provide impossibility results to lower bound the query complexity and show tightness of our guarantees.