文章基本信息

标题：A Brief Survey of Data Pricing for Machine Learning
本地全文：下载
作者：Zuoqi Tang ; Zheqi Lv ; Chao Wu 等
期刊名称：Computer Science & Information Technology
电子版ISSN：2231-5403
出版年度：2020
卷号：10
期号：2
页码：99-110
DOI：10.5121/csit.2020.100209
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Big data and machine learning are poised to revolutionize the field of artificial intelligence and represent a step towards building an intelligent society. Big data is considered to be the key to unlocking the next great waves of growth in productivity, the value of data is realized through machine learning.In this survey, we begin with an introduction to the general field of data pricing and distributed machine learning then progress to the main streams of data pricing and mechanism design methods. Our survey will cover several current areas of research within the field of data pricing, including the incentive mechanism design for federated learning, reinforcement learning, auction, crowdsourcing, and blockchain, especially, focus on reward function for machine learning and payment scheme. In parallel, we highlight the pricing scheme in data transactions, focusing on data evaluation via distributed machine learning. To conclude, we discuss some research challenges and future directions of data pricing for machine learning.
关键词：Data pricing; Big data; Machine learning; Data transaction