SAN DIEGO, Sept. 14, 2020 /PRNewswire/ -- KDD 2020, the premier interdisciplinary conference in data science, is pleased to announce the recipients of the SIGKDD Best Paper Awards, recognizing papers presented at the annual SIGKDD conference that advance the fundamental understanding of the field of knowledge discovery in data and data mining. Winners were selected from more than 2,000 papers initially submitted for consideration to be presented at the conference. Of the 338 papers chosen for the conference, three awards were granted: Best Paper in the Research Track, Best Paper in the Applied Data Science Track, and Best Student Paper.
"There was unprecedented interest in presenting advanced peer-reviewed papers in data science at KDD 2020 and the quality of submissions was outstanding," noted Dr. Michael Pazzani, Chair of the best research paper selection committee of KDD 2020 and distinguished scientist at UC San Diego. "The award committee deliberated long and hard to coalesce on the papers we felt surpassed all others in terms of potential impact on the industry and superior understanding of the field of knowledge discovery in data science." Anima Anandkumar, Bren professor at Caltech and a director of machine learning research at NVIDIA, joined Dr. Pazzani on the organization committee as chairperson for the Applied Data Science track.
The SIGKDD Best Papers of 2020 are as follows:
The technical program committees for the Research Track and the Applied Data Science Track identified and nominated a highly selective group of papers for the Best Paper Awards. The nominated papers were then independently reviewed by two separate committees led by Professor Michael Pazzani, UC San Diego (Research Track) and Professor Anima Anandkumar, California Institute of Technology (Applied Data Science Track).
For more information on this year's event, which took place virtually Aug. 23-27, 2020, please visit: www.kdd.org/kdd2020.
About ACM SIGKDD:
ACM is the premier global professional organization for researchers and professionals dedicated to the advancement of the science and practice of knowledge discovery and data mining. SIGKDD is ACM's Special Interest Group on Knowledge Discovery and Data Mining. The annual KDD International Conference on Knowledge Discovery and Data Mining is the premier interdisciplinary conference for data mining, data science and analytics.
For more information on KDD, please visit: https://www.kdd.org/.
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SOURCE ACM SIGKDD