Knowledge Discovery and Data Mining is an interdisciplinary area focusing upon methodologies and applications for extracting useful knowledge from data1. Different from machine learning, Knowledge Discovery and Data Mining (KDD) is considered to be more practical and more related with real-world applications. Some good examples include recommender systems, clustering, graph mining, anomaly detection, and ensemble learning.
To facilitate KDD related research, we create this repository with:
- Upcoming data mining (DM) conference submission date, notification date, and etc.
- Historical conference acceptance rate
- Conference ranking by CORE (2018), Qualis (2016), CCF (2015), and ERA (2012)
- Publication tips from field experts
Table of Contents:
- 1. 2019-2020 Data Mining Conferences
- 2. Data Mining Conference Acceptance Rate
- 3. Conference Ranking
- 4. Tips for Doing Good DM Research & Get it Published!
| Conference | Submission Deadline | Notification | Conference Date | Location | Acceptance Rate (2018) | Website |
|---|---|---|---|---|---|---|
| ACM SIGKDD International Conference on Knowledge discovery and data mining (KDD) | Feb 13, 2020 | May 15, 2020 | Aug 22-27, 2020 | San Diego, California | 17.8% | Link |
| European Conference on Machine learning and knowledge discovery in databases (ECML PKDD) | Mar 19 (26), 2020 | Jun 04, 2020 | Sep 14-18, 2020 | Ghent, Belgium | 25% | Link |
| ACM International Conference on Information and Knowledge Management (CIKM) | May 2020 | July 2020 | Oct 19-23, 2020 | Galway, Ireland | 17% | Link |
| IEEE International Conference on Data Mining (ICDM) | Jun 2020 | Aug 2020 | Nov 17-20, 2020 | Sorrento, Italy | 19.8% | Link |
| IEEE International Conference on Data Engineering (ICDE) [First Round] | Jun 08, 2019 | Aug 10, 2019 | Apr 20-24, 2020 | Dallas, Texas, USA | 18% | Link |
| ACM SIGMOD/PODS Conference (SIGMOD) | Jul 09, 2019 | Oct 03, 2019 | Jun 14-19, 2020 | Portland, Oregon, USA | 18% | Link |
| ACM International Conference on Web Search and Data Mining (WSDM) | Aug 12, 2019 | Oct 12, 2019 | Feb 05-09, 2020 | Houston, Texas, USA | 16.3% | Link |
| IEEE International Conference on Big Data (BigData) | Aug 19, 2019 | Oct 16, 2019 | Dec 09-12, 2019 | Log Angels, CA, USA | 19.7% | Link |
| SIAM International Conference on Data Mining (SDM) | Oct 04 (11), 2019 | Dec, 2019 (TBA) | May 05-07, 2020 | Cincinnati, Ohio, USA | 22.9% | Link |
| The Web Conference (WWW) | Oct 07 (14), 2019 | Jan 10, 2020 | Apr 20-24, 2020 | Taipei, Taiwan | 15% | Link |
| IEEE International Conference on Data Engineering (ICDE) | Oct 08 (15), 2019 | Dec 14, 2019 | Apr 20-24, 2020 | Dallas, Texas, USA | 18% | Link |
| Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) | Nov 18 (25), 2019 | Jan 28, 2020 | May 11-14, 2020 | Singapore | 24.1% | Link |
| Conference | Acceptance Rate | Oral Presentation (otherwise poster) |
|---|---|---|
| KDD '19 | 17.8% (321/1808) | N/A |
| KDD '18 | 18.4% (181/983, research track), 22.5% (112/497, applied data science track) | 59.1% (107/181, research track), 35.7% (40/112, applied data science track) |
| KDD '17 | 17.4% (130/748, research track), 22.0% (86/390, applied data science track) | 49.2% (64/130, research track), 41.9% (36/86, applied data science track) |
| KDD '16 | 18.1% (142/784, research track), 19.9% (66/331, applied data science track) | 49.3% (70/142, research track), 60.1% (40/66, applied data science track) |
| SDM '19 | 22.7% (90/397) | N/A |
| SDM '18 | 23.0% (86/374) | N/A |
| SDM '17 | 26.0% (93/358) | N/A |
| SDM '16 | 26.0% (96/370) | N/A |
| ICDM '18* | 19.8% (188/948, overall), 8.9% (84/?, regular paper), ?% (104/?, short paper) | N/A |
| ICDM '17* | 19.9% (155/778, overall), 9.3% (72/?, regular paper), ?% (83/?, short paper) | N/A |
| ICDM '16* | 19.6% (178/904, overall), 8.6% (78/?, regular paper), ?% (100/?, short paper) | N/A |
| CIKM '19 | 19.6% (202/1031, long paper), 22.7% (107/471, short paper), 21.8% (38/174m applied research) | N/A |
| CIKM '18 | 17% (147/826, long paper), 23% (96/413, short paper), 25% (demo), 34% (industry paper) | Short papers are presented at poster sessions |
| CIKM '17 | 20% (171/855, long paper), 28% (119/419, short paper), 38% (30/80, demo paper) | Short papers are presented at poster sessions |
| CIKM '16 | 23% (160/701, long paper), 24% (55/234, short paper), 54 extended short papers (6 pages) | Short papers are presented at poster sessions |
| ECML PKDD '18 | 26% (94/354, research track), 26% (37/143, applied ds track), 15% (23/151, journal track) | N/A |
| ECML PKDD '17 | 28% (104/364) | N/A |
| ECML PKDD '16 | 28% (100/353) | N/A |
| PAKDD '19 | 24.1% (137/567, overall) | N/A |
| PAKDD '18 | 27.8% (164/592, overall), 9.8% (58/592, long presentation), 18.1% (107/592, regular) | N/A |
| PAKDD '17 | 28.2% (129/458, overall), 9.8% (45/458, long presentation), 18.3% (84/458, regular) | N/A |
| PAKDD '16 | 29.6% (91/307, overall), 12.7% (39/307, long presentation), 16.9% (52/307, regular) | N/A |
| WSDM '19 | 16.4% (84/511, overall) | 40.4% (34/84, long presentation), 59.5% (50/84, short presentation)^ |
| WSDM '18 | 16.3% (84/514 in which 3 papers are withdrawn/rejected after the acceptance) | 28.4% (23/81, long presentation), 71.6% (58/81, short presentation)^ |
| WSDM '17 | 15.8% (80/505) | 30% (24/80, long presentation), 70% (56/80, short presentation)^ |
| WSDM '16 | 18.2% (67/368) | 29.8% (20/67, long presentation), 70.2% (47/67, short presentation)^ |
| WSDM '15 | 16.4% (39/238) | 53.8% (21/39, long presentation), 46.2% (18/39, short presentation)^ |
*ICDM has two tracks (regular paper track and short paper track), but the exact statistic is not released, e.g., the split between these two tracks. See ICDM Acceptance Rates for more information.
^All accepted WSDM papers are associated with an interactive poster presentation in addition to oral presentations.
Conference stats are visualized below for a straightforward comparison.
| Conference | CORE (2018) | Qualis (2016) | CCF (2015) | ERA (2010) |
|---|---|---|---|---|
| ACM SIGKDD International Conference on Knowledge discovery and data mining (KDD) | A* | A1 | A | A |
| European Conference on Machine learning and knowledge discovery in databases (ECML PKDD) | A | A1 | B | A |
| IEEE International Conference on Data Mining (ICDM) | A* | A1 | B | A |
| SIAM International Conference on Data Mining (SDM) | A | A1 | B | A |
| ACM International Conference on Information and Knowledge Management (CIKM) | A | A1 | B | A |
| ACM International Conference on Web Search and Data Mining (WSDM) | A* | A1 | B | B |
| Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) | A | A2 | C | A |
| The Web Conference (WWW) | A* | A1 | A | A |
| IEEE International Conference on Data Engineering (ICDE) | A* | A1 | A | A |
Source and ranking explanation:
How to do good research, Get it published in SIGKDD and get it cited!: a fantastic tutorial on SIGKDD'09 by Prof. Eamonn Keogh (UC Riverside).
Checklist for Revising a SIGKDD Data Mining Paper: a concise checklist by Prof. Eamonn Keogh (UC Riverside).
How to Write and Publish Research Papers for the Premier Forums in Knowledge & Data Engineering: a tutorial on how to structure data mining papers by Prof. Xindong Wu (University of Louisiana at Lafayette).
Last updated @ May 12th, 2019
IBM Research, 2018. Knowledge Discovery and Data Mining. https://researcher.watson.ibm.com/researcher/view_group.php?id=144↩