机器学习模型的系统映射研究
Systematic Mapping Study on the Machine Learning Lifecycle
摘要：
人工智能（AI）的发展让各个行业都渴望探索AI的好处。围绕AI的研究越来越多，其中大部分集中在新AI算法和技术的开发上。然而，人工智能的出现带来了越来越多的与人工智能模型生命周期管理相关的实际问题，需要进行研究。我们通过对AI模型的生命周期进行系统的映射研究来解决这一差距。通过定量研究，我们提供了该领域的概述，确定研究机会，并为未来的研究提供建议。我们的研究产生了2005年至2020年发表的405篇出版物，映射在5个不同的主要研究主题和31个子主题。我们观察到，只有少数出版物关注数据管理和模型生产问题，更多的研究应该从整体的角度来解决人工智能的生命周期。
英文摘要：
The development of artificial intelligence (AI) has made various industries eager to explore the benefits of AI. There is an increasing amount of research surrounding AI, most of which is centred on the development of new AI algorithms and techniques. However, the advent of AI is bringing an increasing set of practical problems related to AI model lifecycle management that need to be investigated. We address this gap by conducting a systematic mapping study on the lifecycle of AI model. Through quantitative research, we provide an overview of the field, identify research opportunities, and provide suggestions for future research. Our study yields 405 publications published from 2005 to 2020, mapped in 5 different main research topics, and 31 sub-topics. We observe that only a minority of publications focus on data management and model production problems, and that more studies should address the AI lifecycle from a holistic perspective.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
