{"title":"面向大数据网络分析的图挖掘新设计与实现","authors":"D. Shravani","doi":"10.9790/9622-0707071625","DOIUrl":null,"url":null,"abstract":"The Research entitled Application of Graph Theory to Big Networks for Big Data” is an innovative idea having novel design and exemplar implementations on various case studies. Graph Mining strategies can be applied for Big Data Networks Analysis as specified by Literature survey. Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.","PeriodicalId":13972,"journal":{"name":"International Journal of Engineering Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Novel Design and Implementation of Graph Mining for Big Data Network Analysis\",\"authors\":\"D. Shravani\",\"doi\":\"10.9790/9622-0707071625\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Research entitled Application of Graph Theory to Big Networks for Big Data” is an innovative idea having novel design and exemplar implementations on various case studies. Graph Mining strategies can be applied for Big Data Networks Analysis as specified by Literature survey. Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.\",\"PeriodicalId\":13972,\"journal\":{\"name\":\"International Journal of Engineering Research and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Engineering Research and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.9790/9622-0707071625\",\"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 Journal of Engineering Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.9790/9622-0707071625","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Novel Design and Implementation of Graph Mining for Big Data Network Analysis
The Research entitled Application of Graph Theory to Big Networks for Big Data” is an innovative idea having novel design and exemplar implementations on various case studies. Graph Mining strategies can be applied for Big Data Networks Analysis as specified by Literature survey. Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.