The 4th International Workshop on Talent and Management Computing (TMC'2023)
Authors: 
Hengshu Zhu, Hui Xiong, Yong Ge, 
Ee-Peng LimAuthors Info & Claims
Hengshu Zhu, Hui Xiong, Yong Ge, Ee-Peng LimAuthors Info & ClaimsPages 5909 - 5910
Abstract
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.
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Information & Contributors
Information
Published In
August 2023
5996 pages
ISBN:9798400701030
DOI:10.1145/3580305
- General Chairs:
- Ambuj Singh,
- Yizhou Sun,
- Program Chairs:
- Leman Akoglu,
- Dimitrios Gunopulos,
- Xifeng Yan,
- Ravi Kumar,
- Fatma Ozcan,
- Jieping Ye
Copyright � 2023 Owner/Author.
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 04 August 2023
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Conference
KDD '23: The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
August 6 - 10, 2023
CA, Long Beach, USA
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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%
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