A review of systematic evaluation and improvement in the big data environment

• 作 者: Feng YANG Manman WANG
• 机 构: School of Management, University of Science and Technology of China,Hefei 230026, China
• 出 处: 工程管理前沿（英文版）
• 发表日期: 2020年1期
• 关键词: big data evaluation methods systematic improvement big data analytic techniques

The era of big data brings unprecedented opportunities and challenges to management research.As one of the important functions of management decisionmaking,evaluation has been given more functions and application space.Exploring the applicable evaluation methods in the big data environment has become an important subject of research.The purpose of this paper is to provide an overview and discussion of systematic evaluation and improvement in the big data environment.We first review the evaluation methods based on the main analytic techniques of big data such as data mining,statistical methods,optimization and simulation,and deep leing.Focused on the characteristics of big data (association feature,data loss,data noise,and visualization),the relevant evaluation methods are given.Furthermore,we explore the systematic improvement studies and application fields.Finally,we analyze the new application areas of evaluation methods and give the future directions of evaluation method research in a big data environment from six aspects.We hope our research could provide meaningful insights for subsequent research.