用于作业自动化的人工智能和机器学习

IF 1.3 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Gang Peng, R. Bhaskar
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引用次数: 0

摘要

工作自动化是一个重要的决定,它给工作场所带来了深刻的变化。然而,是什么推动了工作自动化的问题仍然不清楚。本研究对工作自动化的五个理论框架进行了跨学科的回顾,特别关注人工智能和机器学习所起的作用。它强调了每个框架的概念和机制,比较和对比了它们的异同,并强调了工作自动化的挑战和机遇。它还通过解决现有框架中的研究空白,提出了一个关于工作自动化的综合框架,从而有助于这一重要主题的研究和实践。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence and Machine Learning for Job Automation
Job automation is a critical decision that has brought about profound changes in the workplace. However, the question of what drives job automation remains unclear. This study conducts an interdisciplinary review of five theoretical frameworks on job automation, paying particular attention to the role played by artificial intelligence and machine learning. It highlights the concepts and mechanisms underlying each of the frameworks, compares and contrasts their similarities and differences, and highlights challenges and suggests opportunities of job automation. It also proposes an integrated framework on job automation by addressing the research gaps in extant frameworks and thereby contributes to the research and practice on this important topic.
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来源期刊
Journal of Database Management
Journal of Database Management 工程技术-计算机:软件工程
CiteScore
4.20
自引率
23.10%
发文量
24
期刊介绍: The Journal of Database Management (JDM) publishes original research on all aspects of database management, design science, systems analysis and design, and software engineering. The primary mission of JDM is to be instrumental in the improvement and development of theory and practice related to information technology, information systems, and management of knowledge resources. The journal is targeted at both academic researchers and practicing IT professionals.
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