Decision Support Framework for Big Data Analytics

被引：2
|
作者：
Agarwal, Sakshi [1 ]
Narayanan, Krishnaprasad [1 ]
Sinha, Manjira [2 ]
Gupta, Rohit [1 ]
Eswaran, Sharanya [3 ]
Mukherjee, Tridib [3 ]
机构：
[1] Conduent Labs India, Bengaluru, Karnataka, India
[2] Accenture, Bangalore, Karnataka, India
[3] Play Games24x7, Data Sci Team, Bangalore, Karnataka, India
来源：
2018 IEEE WORLD CONGRESS ON SERVICES (IEEE SERVICES 2018) | 2018年
关键词：
Decision Support Framework; Big Data; Urban Informatics; Analytic Hierarchy Process (AHP); Decision Tree Modeling; Multi-modal Data Analytics; Crime;
D O I：
10.1109/SERVICES.2018.00040
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Making design choices for big data systems is not trivial. If not planned out efficiently, keeping in mind the practical requirements, there's a possibility that the deployed system can lack important features to match up the application or it may contain over-sophisticated methods that incurs a large cost, but little increase in the efficiency, output. To equip the end user towards wise design choices, we have proposed a decision support framework for big data systems that can evaluate the suitability over numerous design combinations and outputs the one most efficient for the end-user requirement.
引用
收藏
页码：53 / 54
页数：2
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