{"title":"reginf:在任意数量的任意形状查询区域内最大化影响的交互式系统","authors":"Hui Li, Q. Yang, Jiangtao Cui","doi":"10.1145/3488560.3502188","DOIUrl":null,"url":null,"abstract":"Recently, aside with the prevalent usage of location-based social network, location-aware influence maximization (laim) problem has received plenty of attention in viral marketing. It aims to find a set of seed users such that information propagated from them can reach the largest number of users within particular geographical regions. However, existing solutions to laim can only work on single simple query region, e.g., a rectangle, instead of complex ones. Besides, there is no ready-to-use system for users to address laim visually. In this work, we present a pair of solutions towards location-aware influence maximization problem. Both can work on queries with arbitrary number of regions and arbitrary shapes. More importantly, we implement a web-based system, namely a2RegInf, which enables viral marketers to address laim visually, with native GPU support. To the best of our knowledge, we are the first to provide a ready-to-use system for answering the problem over web-based interface that supports arbitrary number of arbitrary shaped query regions.","PeriodicalId":348686,"journal":{"name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","volume":"349 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"a2RegInf: An Interactive System for Maximizing Influence within Arbitrary Number of Arbitrary Shaped Query Regions\",\"authors\":\"Hui Li, Q. Yang, Jiangtao Cui\",\"doi\":\"10.1145/3488560.3502188\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently, aside with the prevalent usage of location-based social network, location-aware influence maximization (laim) problem has received plenty of attention in viral marketing. It aims to find a set of seed users such that information propagated from them can reach the largest number of users within particular geographical regions. However, existing solutions to laim can only work on single simple query region, e.g., a rectangle, instead of complex ones. Besides, there is no ready-to-use system for users to address laim visually. In this work, we present a pair of solutions towards location-aware influence maximization problem. Both can work on queries with arbitrary number of regions and arbitrary shapes. More importantly, we implement a web-based system, namely a2RegInf, which enables viral marketers to address laim visually, with native GPU support. To the best of our knowledge, we are the first to provide a ready-to-use system for answering the problem over web-based interface that supports arbitrary number of arbitrary shaped query regions.\",\"PeriodicalId\":348686,\"journal\":{\"name\":\"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining\",\"volume\":\"349 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3488560.3502188\",\"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 Fifteenth ACM International Conference on Web Search and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3488560.3502188","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
a2RegInf: An Interactive System for Maximizing Influence within Arbitrary Number of Arbitrary Shaped Query Regions
Recently, aside with the prevalent usage of location-based social network, location-aware influence maximization (laim) problem has received plenty of attention in viral marketing. It aims to find a set of seed users such that information propagated from them can reach the largest number of users within particular geographical regions. However, existing solutions to laim can only work on single simple query region, e.g., a rectangle, instead of complex ones. Besides, there is no ready-to-use system for users to address laim visually. In this work, we present a pair of solutions towards location-aware influence maximization problem. Both can work on queries with arbitrary number of regions and arbitrary shapes. More importantly, we implement a web-based system, namely a2RegInf, which enables viral marketers to address laim visually, with native GPU support. To the best of our knowledge, we are the first to provide a ready-to-use system for answering the problem over web-based interface that supports arbitrary number of arbitrary shaped query regions.