Special Interest Group on Knowledge Discovery and Data Mining


SIGKDD, representing the Association for Computing Machinery's Special Interest Group on Knowledge Discovery and Data Mining, hosts an influential annual conference.

Conference history

The KDD Conference grew from KDD workshops at AAAI conferences, which were started by Gregory I. Piatetsky-Shapiro in 1989, 1991, and 1993, and Usama Fayyad in 1994. Conference papers of each Proceedings of the SIGKDD International Conference on Knowledge Discovery and Data Mining are published through ACM. KDD is widely considered the most influential forum for knowledge discovery and data mining research.
YearConference location
2012Beijing, China
2013Chicago, IL, United States
2014New York City, NY, United States
2015Sydney, Australia
2016San Francisco, CA, United States
2017Halifax, Canada
2018London, England
2019Anchorage, AK, United States
2020San Diego, CA, United States

The KDD conference has been held each year since 1995, and SIGKDD became an official ACM Special Interest Group in 1998. Past conference locations are listed on the KDD conference web site.
The annual ACM SIGKDD conference is recognized as a flagship venue in the field. Based on statistics provided by independent researcher Lexing Xie in her analysis “Visualizing Citation Patterns of Computer Science Conferences“ as part of the research in Computation Media Lab at Australian National University:
The annual conference of ACM SIGKDD has received the highest rating A* from independent organization Computing Research and Education.

Selection Criteria

Like all flagship conferences, SIGKDD imposes a high requirement to present and publish submitted papers. The focus is on innovative research in data mining, knowledge discovery, and large-scale data analytics. Papers emphasizing theoretical foundations are particularly encouraged, as are novel modeling and algorithmic approaches to specific data mining problems in scientific, business, medical, and engineering applications. Visionary papers on new and emerging topics are particularly welcomed. Authors are explicitly discouraged from submitting papers that contain only incremental results or that do not provide significant advances over existing approaches.
In 2014, over 2,600 authors from at least fourteen countries submitted over a thousand papers to the conference. A final 151 papers were accepted for presentation and publication, representing an acceptance rate of 14.6%. This acceptance rate is slightly lower than those of other top computer science conferences, which typically have a rate of 15-25%. The acceptance rate of a conference is only a proxy measure of its quality. For example, in the field of information retrieval, the has a lower acceptance rate than the higher-ranked SIGIR.

Awards

The group recognizes members of the KDD community with its annual and Service Award.
Each year KDD presents a Best Paper Award to recognizes papers presented at the annual SIGKDD conference that advance the fundamental understanding of the field of knowledge discovery in data and data mining. Two research paper awards are granted: Best Research Paper Award Recipients and Best Student Paper Award Recipients.

Best Paper Award (Best Research Track Paper)

Winning the ACM SIGKDD Best Paper Award is widely considered an internationally recognized significant achievement in a researcher's career. Authors compete with established professionals in the field, such as tenured professors, executives, and eminent industry experts from top institutions. It is common to find press articles and news announcements from the awardees’ institutions and professional media to celebrate this achievement.
This award recognizes innovative scholarly articles that advance the fundamental understanding of the field of knowledge discovery in data and data mining.
Each year, the award is given to authors of the strongest paper by this criterion, selected by a rigorous process.

Selection Process

The selection process follows multiple rounds of peer reviews under stringent criteria. The selection committee consists of leading experts who provide insightful and independent analysis on the merits and degree of innovation of the scholarly articles submitted by each author. The reviewers are required to be recognized subject experts who had extensive contributions to the specific subject area addressed by the paper. Reviewers are also required to be completely unaffiliated with the authors.
First, all papers submitted to the ACM SIGKDD conference are reviewed by research track program committee members. Each submitted paper is extensively reviewed by multiple committee members and detailed feedback is given to each author. After review, decisions are made by the committee members to accept or reject the paper based on the paper’s novelty, technical quality, potential impact, clarity, and whether the experimental methods and results are clear, well executed, and repeatable. During the process, committee members also evaluate the merits of each paper based on above factors, and make decision on recommending candidates for Best Paper Award.
The candidates for Best Paper Award are extensively reviewed by conference chairs and the best paper award committee. The final determination of the award is based on the level of advancement made by authors through the paper to the understanding of the field of knowledge discovery and data mining. Authors of a single paper who are judged to have contributed the highest level of advancement to the field are selected as recipients of this award. Anyone who submits a scholarly article to SIGKDD is considered for this award.

Previous winners

The ACM SIGKDD Best Paper Award was given to 49 individuals between 1997 and 2014. Among these individuals, most are distinguished persons and established professionals with celebrated careers, who have made significant contributions to the field.
YearNamePositionAffiliation
1997Foster ProvostProfessorNew York University
1997Tom FawcettPrincipal Data ScientistSilicon Valley Data Science
1998, 1999Pedro DomingosProfessorUniversity of Washington
2000Associate ProfessorUniversity of Chicago
2000 Head of Statistical ResearchAT&T Labs and Bell Labs
2000Kathleen FisherChair & ProfessorTufts University
2000Corinna CortesHead of ResearchGoogle
2001ProfessorUniversity of British Columbia
2001ProfessorUniversity of British Columbia
2001Tenured Senior InstructorUniversity of British Columbia
2002Padhraic SmythProfessorUniversity of California, Irvine
2002Padhraic SmythAssociate DirectorCenter for Machine Learning and Intelligent Systems
2002VP of BioinformaticsGuardant Health
2003Éva TardosProfessor & DeanCornell University
2003, 2005Jon KleinbergProfessorCornell University
2003, 2005Jon KleinbergMemberNational Academy of Sciences
2003, 2005Jon KleinbergMemberNational Academy of Engineering
2003, 2005Jon KleinbergMemberAmerican Academy of Arts and Sciences
2003Associate ProfessorUniversity of Southern California
2004ProfessorThe University of Texas at Austin
2004Head of AI and ResearchYandex
2004Principal ScientistGoogle
2004, 2005Christos FaloutsosProfessorCarnegie Mellon University
2004, 2005Christos FaloutsosFellowACM
2005Jure LeskovecAssociate ProfessorStanford University
2005Jure LeskovecChief ScientistPinterest
2005Jure LeskovecMember, Board of DirectorsACM SIGKDD
2006Chair & ProfessorCornell University
2006FellowACM, AAAI, Humboldt
2007Principal Data ScientistFlipkart
2007VP of EngineeringLinkedIn
2007FellowAmerican Statistical Association
2007Member, Board of DirectorsACM SIGKDD
2008Chair & ProfessorUniversity of California, Los Angeles
2008DirectorScalable Analytics Institute
2008ProfessorUniversity of Florida
2008Associate ProfessorPennsylvania State University
2009Staff Research ScientistGoogle
2010Director of Machine LearningApple Inc
2010ProfessorUniversity of Washington
2010Co-founder, CEOTuri
2010Assistant ProfessorThe Hebrew University of Jerusalem
2010Assistant ProfessorUniversity of California, Los Angeles
2010Assistant ProfessorUniversity of California, Davis
2010Applied ScientistAmazon
2010Chih-Jen LinDistinguished ProfessorNational Taiwan University
2010Chih-Jen LinFellowACM, AAAI, IEEE
2011Chief ScientistDstillery
2011Adjunct ProfessorNew York University
2011Associate ProfessorTel Aviv University
2011Senior Data ScientistMetromile
2012Assistant ProfessorKasetsart University, Thailand
2012Staff Software EngineerGoogle
2012Assistant ProfessorUniversity of New Mexico
2012Associate ProfessorUniversidade de São Paulo
2012Director, Critical Care EEG Monitoring ServiceMassachusetts General Hospital
2012Data Science ManagerAirbnb
2012Software EngineerMicrosoft
2012ProfessorUniversity of California, Riverside
2013Principal ScientistAmazon
2013Group ManagerAmazon AI Algorithms
2014Director of Machine Learning and Deep LearningAmazon
2014ProfessorCarnegie Mellon University
2014Staff Research ScientistGoogle
2014Staff Research ScientistGoogle
2014Founder
2014 Lead Inference EngineerScaled Inference

Best Student Paper Award

This only difference between "Best Student Paper Award" and "Best Paper Award " is the limitation in competition.
All authors participating the conference are considered equally for "Best Paper Award ", and the award does not limit competition to any particular region, population, or age group.
However, "Best Student Paper Award" is limited to student authors only. "Best Student Paper Award" recognizes papers presented at the annual SIGKDD conference, with a student as a first author, that advance the fundamental understanding of the field of knowledge discovery in data and data mining.

KDD-Cup

SIGKDD sponsors the KDD Cup competition every year in conjunction with the annual conference. It is aimed at members of the industry and academia, particularly students, interested in KDD.

SIGKDD Explorations

SIGKDD has also published a biannual academic journal titled "SIGKDD Explorations" since June, 1999 when Usama Fayyad took on role of Founding Editor-inChief as ACM SIGKDD was formed. Editors in Chief:
The original founding Board of Directors of SIGKDD in 1998 consist of:
Current Chair:
Former Chairpersons:
Former Executive Committee
Information Directors: