Big data;
Object-oriented data;
Transport;
Networks;
D O I:
10.1016/j.spl.2018.02.013
中图分类号:
O21 [概率论与数理统计];
C8 [统计学];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
The realm of big data is a very wide and varied one. We discuss old, new, small and big data, with some of the important challenges including dealing with highly-structured and object-oriented data. In many applications the objective is to discern patterns and learn from large datasets of historical data. We shall discuss such issues in some transportation network applications in non-academic settings, which are naturally applicable to other situations. Vital aspects include dealing with logistics, coding and choosing appropriate statistical methodology, and we provide a summary and checklist for wider implementation. (C) 2018 Elsevier B.V. All rights reserved.
机构:
Univ Carlos III Madrid, Dept Estadist, Madrid 28903, Spain
Univ Carlos III Madrid, Inst Financial Big Data, Madrid 28903, SpainUniv Carlos III Madrid, Dept Estadist, Madrid 28903, Spain
Galeano, Pedro
Pena, Daniel
论文数: 0引用数: 0
h-index: 0
机构:
Univ Carlos III Madrid, Dept Estadist, Madrid 28903, Spain
Univ Carlos III Madrid, Inst Financial Big Data, Madrid 28903, SpainUniv Carlos III Madrid, Dept Estadist, Madrid 28903, Spain
机构:
Goethe Univ Frankfurt, D-60323 Frankfurt, Germany
Europa Kommiss, Stat Amt Europa Union Eurostat, Luxembourg, LuxembourgGoethe Univ Frankfurt, D-60323 Frankfurt, Germany
机构:
Univ A Coruna, Fac Informat, Dept Matemat, CITIC,ITMATI,Grp MODES, La Coruna 15071, SpainUniv A Coruna, Fac Informat, Dept Matemat, CITIC,ITMATI,Grp MODES, La Coruna 15071, Spain