SIGKDD, representing the
Association for Computing Machinery
The Association for Computing Machinery (ACM) is a US-based international learned society for computing. It was founded in 1947 and is the world's largest scientific and educational computing society. The ACM is a non-profit professional member ...
's (ACM)
Special Interest Group (SIG) on Knowledge Discovery and
Data Mining, hosts an influential annual conference.
Conference history
The KDD Conference grew from KDD (Knowledge Discovery and Data Mining) workshops at
AAAI
The Association for the Advancement of Artificial Intelligence (AAAI) is an international scientific society devoted to promote research in, and responsible use of, artificial intelligence. AAAI also aims to increase public understanding of artif ...
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.
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:
* 4489 papers were published at ACM SIGKDD conference over 22 years between 1994-2015.
* These 4489 papers had received 112570 citations in total across 3033 venues.
* 56% of these 3033 venues are recognized as top 25 venues in the field.
The annual conference of ACM SIGKDD has received the highest rating A* from independent organization Computing Research and Education (a.k.a. CORE).
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, th
WSDM conferencehas a lower acceptance rate than the higher-ranked
SIGIR.
Awards
The group recognizes members of the KDD community with its annua
Innovation Awardand 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 (Best Research Track Paper) 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 (Best Research Track Paper).
The candidates for Best Paper Award (Best Research Track Paper) 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 (Best Research Track Paper) 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.
Best Student Paper Award
This only difference between "Best Student Paper Award" and "Best Paper Award (Best Research Track Paper)" is the limitation in competition.
All authors participating the conference are considered equally for "Best Paper Award (Best Research Track Paper)", 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
An academy (Attic Greek: Ἀκαδήμεια; Koine Greek Ἀκαδημία) is an institution of secondary education, secondary or tertiary education, tertiary higher education, higher learning (and generally also research or honorary membershi ...
, particularly students, interested in
KDD.
SIGKDD Explorations
SIGKDD has also published a biannual
academic journal
An academic journal or scholarly journal is a periodical publication in which scholarship relating to a particular academic discipline is published. Academic journals serve as permanent and transparent forums for the presentation, scrutiny, and d ...
titled ''SIGKDD Explorations'' since June 1999 when
Usama Fayyad took on role of Founding Editor-inChief as ACM SIGKDD was formed. Editors in Chief:
* Charu Aggarwal (since 2014)
*
Bart Goethals
Bart is a masculine given name, usually a diminutive of Bartholomew, sometimes of Barton, Bartolomeo, etc.
Bart is a Dutch and Ashkenazi Jewish surname, and derives from the name ''Bartholomäus'', a German form of the biblical name ''Barth ...
(2010-2013)
*
Osmar R. Zaiane (2008-2010)
* Ramakrishnan Srikant (2006-2007)
*
Sunita Sarawagi[http://www.it.iitb.ac.in/~sunita/] (2003-2006)
*
Usama Fayyad (Founding Editor-in-Chief) (1999-2002)
People
The original founding Board of Directors of SIGKDD in 1998 consist of:
* Won Kim, President, Cyber Database Solutions, ''SIGKDD Chair''
* Rakesh Agrawal, IBM Almaden, ''SIGKDD Secretary/Treasurer''
*
Usama Fayyad,
Microsoft Research
Microsoft Research (MSR) is the research subsidiary of Microsoft. It was created in 1991 by Richard Rashid, Bill Gates and Nathan Myhrvold with the intent to advance state-of-the-art computing and solve difficult world problems through technologi ...
, ''SIGKDD Director and Editor-in-Chief of SIGKDD Explorations Newsletter''
*
Gregory Piatetsky-Shapiro, Knowledge Stream Partners, ''SIGKDD Director''
* Daryl Pregibon, AT&T Labs, ''SIGKDD Director''
* Padhraic Smyth, U. of California Irvine, ''SIGKDD Director''
Current Chair:
*
Bing Liu (2013- )
Former Chairpersons:
*
Usama Fayyad (2009-2013)
*
Gregory Piatetsky-Shapiro (2005-2009)
* Won Kim (1998-2005)
Former Executive Committee (2009-2013)
*
Johannes Gehrke
Johannes Gehrke is a German computer scientist and the director of Microsoft Research in Redmond and CTO and Head of Machine Learning for the Microsoft Teams Backend. He is an ACM Fellow, an IEEE Fellow, and the recipient of the 2011 IEEE Comput ...
* Robert Grossman
* David D. Jensen
*
Raghu Ramakrishnan
Raghu Ramakrishnan is a researcher in the areas of database and information management. He is a Technical Fellow at Microsoft. He has been a Vice President and Research Fellow for Yahoo! Inc.
Ramakrishnan spent 22 years as a professor at the Un ...
*
Sunita Sarawagi
*
Ramakrishnan Srikant
Ramakrishnan Srikant is a Google Fellow at Google
Google LLC () is an American multinational technology company focusing on search engine technology, online advertising, cloud computing, computer software, quantum computing, e-commerc ...
Information Directors:
* Ankur Teredesai (2011-)
* Gabor Melli (2004-2011)
* Ramakrishnan Srikant (1998-2003)
See also
*
ACM SIGAI
*
ACM SIGMOD
*
ICML
The International Conference on Machine Learning (ICML) is the leading international academic conference in machine learning. Along with NeurIPS and ICLR, it is one of the three primary conferences of high impact in machine learning and artifici ...
*
NIPS
*
IEEE
The Institute of Electrical and Electronics Engineers (IEEE) is a 501(c)(3) professional association for electronic engineering and electrical engineering (and associated disciplines) with its corporate office in New York City and its operation ...
ICDM
*
WWW
The World Wide Web (WWW), commonly known as the Web, is an information system enabling documents and other web resources to be accessed over the Internet.
Documents and downloadable media are made available to the network through web se ...
References
External links
*
ACM SIGKDD Explorations
{{Authority control
Association for Computing Machinery Special Interest Groups
Data mining