{"title":"Application of graph theory in bigdata environment","authors":"Supratim Bhattacharya, Jayanta Poray","doi":"10.1109/ICCECE.2016.8009585","DOIUrl":null,"url":null,"abstract":"In data driven age, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only in high volume, but also high in variety, velocity & veracity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. Furthermore, decision makers need to be able to gain valuable insights from such varied and rapidly changing data, ranging from daily transactions to customer interactions and social network data. Graph theory is another flexible domain where we can able to analyze & predict and take decisions effortlessly, comparatively quicker & atmost accurately. In this paper we have reviewed and proposed certain graphical algorithms based on bigdata and analyse their effort towards decision making.","PeriodicalId":414303,"journal":{"name":"2016 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computer, Electrical & Communication Engineering (ICCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCECE.2016.8009585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In data driven age, enormous amounts of data have become available on hand to decision makers. Big data refers to datasets that are not only in high volume, but also high in variety, velocity & veracity, which makes them difficult to handle using traditional tools and techniques. Due to the rapid growth of such data, solutions need to be studied and provided in order to handle and extract value and knowledge from these datasets. Furthermore, decision makers need to be able to gain valuable insights from such varied and rapidly changing data, ranging from daily transactions to customer interactions and social network data. Graph theory is another flexible domain where we can able to analyze & predict and take decisions effortlessly, comparatively quicker & atmost accurately. In this paper we have reviewed and proposed certain graphical algorithms based on bigdata and analyse their effort towards decision making.