ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining.
SIGKDD is announcing a funding opportunity through its newly established KDD Impact Program. The SIGKDD community has expanded its reach dramatically over the past few years and the KDD conference has grown into a major event. SIGKDD would like to direct its success towards a broader positive
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This Call for Proposals invites industrial or academic institutions to submit their proposals for organizing the 2018 KDD Cup competition. Since 1997, KDD Cup has been the premier annual Data Mining competition held in conjunction with the ACM SIGKDD conference on Knowledge Discovery and Data
The 2017 Test of Time award recognizes the following influential contributions to SIGKDD that have withstood the test of time.
Dr. Qiang Yang has an outstanding history of serving and promoting the fields of data mining and the artificial intelligence. He has served as the PC Co-chair for ACM KDD 2010, General Chair for ACM KDD 2012 in Beijing and PC Chair for IJCAI 2015. He was the General Co-Chair for conferences such as ACM IUI 2009, ACM RecSys 2013, and IEEE Big Data 2013. He has chaired many committees in data mining and AI, including the 2017 ACM SIGKDD Test-of-Time Paper Award Committee, 2017 IJCAI Award Committee, and 2017 IEEE AI Ten-to-Watch Committee. He is the founding editor in chief of ACM Transactions on Intelligent Systems and Technology (ACM TIST), which has become one of the most cited journals under ACM in recent history. He has also founded the journal IEEE Transactions on Big Data, for which he is the Editor in Chief. He serves on the AAAI Executive Council and is a member of the Board of Trustees for IJCAI.
ACM SIGKDD is pleased to announce that Dr. Jian Pei is the winner of its 2017 Innovation Award. He is recognized for his seminal contributions to the foundation of data mining and applications, particularly in pattern mining and spatial data mining. He is a major inventor of several pattern-growth methods, including FP-growth and PrefixSpan, which have been extensively used by industry and adopted by data mining textbooks and open source software toolkits. As one of the most cited authors in data mining, his prolific publications have been cited tens of thousands of times.
The ACM SIGKDD Innovation Award is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD). It is conferred on one individual or one group of collaborators whose outstanding technical innovations in the KDD field have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems.
The ACM SIGKDD elections were recently concluded. The new SIGKDD leadership team took office on July 1, 2017.
The newly elected chair of ACM SIGKDD is Prof. Jian Pei, Canada Research Chair at Simon Fraser University and a Technical VP of Huawei Technologies, Co., Ltd. Prof. Jian Pei is an ACM and IEEE fellow, and his contributions to Data Science are well recognized with over 200 publications and 70K+ citations. Numerous industries have been transformed by these publications and results; and he continues to lead the movement towards creating an innovation driven field that is diverse, inclusive, and transformational. The SIGKDD community is honored to have him serve as chair leading the community on its next chapter.
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Nominations due Friday May 12, 2017
ACM SIGKDD invites your nominations for its 2017 Innovation and Service Awards.
ACM SIGKDD, ACMÕs Special Interest Group on Knowledge Discovery and Data Mining (KDD), is the premier global professional organization for researchers and professionals dedicated to
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2017 SIGKDD Dissertation Award nominations are open.
ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining.
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2017 SIGKDD Doctoral Dissertation Award
CALL FOR
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ACM SIGKDD Executive Committee hereby invites proposals to host the annual KDD Conference in 2019. The conference should take place in August 2019.
KDD is the flagship conference of ACM SIGKDD and the premier research conference on data science and data mining. Proposals for hosting KDD-2019
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The Association of Computing Machinery's Special Interest Group for Knowledge Discovery and Data Mining (ACM SIGKDD), the world’s oldest and largest community for data mining, data science and analytics, today announced the results of their prestigious awards granted in advance of the 22nd annual KDD-2016 conference in San Francisco, CA, August 13-17, 2016.
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ACM SIGKDD dissertation awards recognize outstanding work done by graduate students in the areas of data science, machine learning and data mining.
The 2016 Test of Time award recognizes the following influential contributions to SIGKDD that have withstood the test of time.
ACM SIGKDD is pleased to announce that Wei Wang is the winner of its 2016 Service Award for her exceptional technical contributions to the foundation and practice of data mining and for her excellent services to the data mining community.
ACM SIGKDD Service Award is the highest service award in the field of knowledge discovery and data mining (KDD). It is conferred on one individual or one group for their outstanding professional services and contributions to the field of knowledge discovery and data mining
ACM SIGKDD is pleased to announce that Philip S. Yu is the winner of its 2016 Innovation Award. He is recognized for his influential research and scientific contributions on mining, fusion and anonymization of big data.
The ACM SIGKDD Innovation Award is the highest award for technical excellence in the field of Knowledge Discovery and Data Mining (KDD). It is conferred on one individual or one group of collaborators whose outstanding technical innovations in the KDD field have had a lasting impact in advancing the theory and practice of the field. The contributions must have significantly influenced the direction of research and development of the field or transferred to practice in significant and innovative ways and/or enabled the development of commercial systems.
By Evangelos Simoudis, Founder and Managing Director at Synapse Partners, on behalf of the KDD-2016 Conference
Big data’s day has come: it dominates headlines and business conversations alike. As industries coalesce around it, the conversations surrounding big data (benefits, issues, challenges)
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NEW YORK, NY— 5/23/2016- The Association of Computing Machinery’s Special Interest Group for Knowledge Discovery and Data Mining (ACM SIGKDD), the world’s oldest and largest
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The KDD Cup 2016 challenge is underway, and the results from Phase 1 are in! This year’s task is to evaluate the most influential organizations in a given domain, such as machine learning, information retrieval, or computer vision. Team submissions are being evaluated on their predictive ability to
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