{"title":"大图表分析:技术现状和未来研究议程","authors":"A. Cuzzocrea, I. Song","doi":"10.1145/2666158.2668454","DOIUrl":null,"url":null,"abstract":"Analytics over big graphs is becoming a first-class challenge in database research, with fast-growing interest from both the academia and the industrial community. This problem arises in several application scenarios, ranging from social networks to large-scale network systems, from knowledge discovery to cybersecurity, and so forth. Following this major trend, this paper explores actual state-of-the-art results in the area of analytics over big graphs and discusses open research issues and actual trends in such area.","PeriodicalId":335396,"journal":{"name":"International Workshop on Data Warehousing and OLAP","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"52","resultStr":"{\"title\":\"Big Graph Analytics: The State of the Art and Future Research Agenda\",\"authors\":\"A. Cuzzocrea, I. Song\",\"doi\":\"10.1145/2666158.2668454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analytics over big graphs is becoming a first-class challenge in database research, with fast-growing interest from both the academia and the industrial community. This problem arises in several application scenarios, ranging from social networks to large-scale network systems, from knowledge discovery to cybersecurity, and so forth. Following this major trend, this paper explores actual state-of-the-art results in the area of analytics over big graphs and discusses open research issues and actual trends in such area.\",\"PeriodicalId\":335396,\"journal\":{\"name\":\"International Workshop on Data Warehousing and OLAP\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"52\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Workshop on Data Warehousing and OLAP\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2666158.2668454\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Workshop on Data Warehousing and OLAP","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2666158.2668454","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Big Graph Analytics: The State of the Art and Future Research Agenda
Analytics over big graphs is becoming a first-class challenge in database research, with fast-growing interest from both the academia and the industrial community. This problem arises in several application scenarios, ranging from social networks to large-scale network systems, from knowledge discovery to cybersecurity, and so forth. Following this major trend, this paper explores actual state-of-the-art results in the area of analytics over big graphs and discusses open research issues and actual trends in such area.