The 4th International Workshop on Talent and Management Computing (TMC'2023): Editorial

• Main Authors: ZHU, Hengshu, XIONG, Hui, GE, Yong, LIM, Ee-peng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/8328; https://ink.library.smu.edu.sg/context/sis_research/article/9331/viewcontent/3580305.3599200_pvoa.pdf
• Institution: Singapore Management University

In today's competitive and fast-evolving business environment, it is a critical time for organizations to rethink how to deal with the talent and management related tasks in a quantitative manner. Indeed, thanks to the era of big data, the availability of large-scale talent data provides unparalleled opportunities for business leaders to understand the rules of talent and management, which in turn deliver intelligence for effective decision making and management for their organizations. In the past few years, talent and management computing have increasingly attracted attentions from KDD communities, and a number of research/applied data science efforts have been devoted. To this end, the purpose of this workshop, i.e., the 4th International Workshop on Talent and Management Computing (TMC'2023), is to bring together researchers and practitioners to discuss both the critical problems faced by talent and management related domains, and potential data-driven solutions by leveraging state-of-the-art data mining technologies.