{"title":"使用图形处理器计算热门场所","authors":"Marta Fort, J. A. Sellarès, Nacho Valladares","doi":"10.1109/ICDMW.2010.45","DOIUrl":null,"url":null,"abstract":"Mobile devices provide the availability of tracking and collecting trajectories of moving objects such as vehicles, people or animals. There exists a well-known collection of patterns which can occur for a subset of trajectories. Specifically we study the so-called Popular Places, that is regions that are visited by many distinct moving objects.We propose algorithms to efficiently compute different forms of reporting Popular Places, that take benefit of the Graphics Processing Unit parallelism capabilities. We also describe how to visualize the reported solutions. Finally we present and discuss experimentalresults obtained with the implementation of our algorithms.","PeriodicalId":170201,"journal":{"name":"2010 IEEE International Conference on Data Mining Workshops","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Computing Popular Places Using Graphics Processors\",\"authors\":\"Marta Fort, J. A. Sellarès, Nacho Valladares\",\"doi\":\"10.1109/ICDMW.2010.45\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mobile devices provide the availability of tracking and collecting trajectories of moving objects such as vehicles, people or animals. There exists a well-known collection of patterns which can occur for a subset of trajectories. Specifically we study the so-called Popular Places, that is regions that are visited by many distinct moving objects.We propose algorithms to efficiently compute different forms of reporting Popular Places, that take benefit of the Graphics Processing Unit parallelism capabilities. We also describe how to visualize the reported solutions. Finally we present and discuss experimentalresults obtained with the implementation of our algorithms.\",\"PeriodicalId\":170201,\"journal\":{\"name\":\"2010 IEEE International Conference on Data Mining Workshops\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Data Mining Workshops\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDMW.2010.45\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Data Mining Workshops","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDMW.2010.45","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computing Popular Places Using Graphics Processors
Mobile devices provide the availability of tracking and collecting trajectories of moving objects such as vehicles, people or animals. There exists a well-known collection of patterns which can occur for a subset of trajectories. Specifically we study the so-called Popular Places, that is regions that are visited by many distinct moving objects.We propose algorithms to efficiently compute different forms of reporting Popular Places, that take benefit of the Graphics Processing Unit parallelism capabilities. We also describe how to visualize the reported solutions. Finally we present and discuss experimentalresults obtained with the implementation of our algorithms.