NSF Student Support for the 2018 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
NSF Student Support for the 2018 ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018)
批准号:
1832544
负责人:
Wei Wang
金额:
$2.5万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-05-01 至 2020-04-30
中文摘要
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英文摘要
This grant provides support for 25 U.S.-based graduate students to participate in the 24th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2018), to be held in London, United Kingdom August 19-23, 2018. KDD is the world's premier conference in data science. It is a prestigious interdisciplinary conference that brings together researchers and practitioners every year, over 2,000 in recent years, from all aspects of data science, data mining, and knowledge discovery. A strong representation of U.S. students and researchers is essential in maintaining U.S. competitiveness in this important area today and into the future. Since 2013, the KDD conference includes a Broadening Participation in Data Mining workshop. As in various STEM fields, increasing the diversity of participants in KDD research areas is a primary goal. The grant will provide travel support for 25 students. The selection committee will select recipients of the support based on merit and need and place particular emphasis on diversity in the selection process. The KDD technical program includes oral and poster presentations of refereed papers, panel discussions, and invited talks by the world's leading experts. It provides an international forum for presentation of original research results as well as exchange and dissemination of innovative and practical development experiences, which are particularly valuable for student participants. Besides the technical program, the conference features workshops, tutorials, panels, posters, project showcases, a data mining contest (KDD Cup), social networks and job matching sessions, and a PhD forum. These will provide a comprehensive multi-facet learning experience to students at all levels. Information on KDD 2018 can be accessed at http://www.kdd.org/kdd2018/. Proceedings will be made available through the ACM Digital Library.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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