After much consideration, the General Chairs, Executive Committee and Organizing Committee for KDD 2020 have decided to take the conference fully virtual. The events of the past few months and the continued safety concerns have led us to make this difficult decision. Our focus now is on creating a virtual conference with the vibrancy, excellence and sense of community that KDD has become known for.
In the coming weeks, the agenda and more programmatic details will be announced, watch the website and our social media posts. Our plans include all the tracks and content you’ve come to count on at KDD, and five exciting keynote speakers! Registration is now open, clear your calendar for August 23-27, 2020, and enjoy access to all the virtual content live and on demand the week of the event.
We’ll look forward to seeing you next year, when we will hope to be together in a safe manner. We are also pursuing a KDD 2023 Conference in San Diego, so that we can realize the hard work this committee has put in and showing the KDD community this beautiful location!
Until then, please spread the word, and feel free to drop us a note with any questions or virtual best practices that you’d like to share.
All the Best,
Rajesh Gupta and Yan Liu
KDD 2020 General Chairs
KDD 2020 Call for Research Papers
- Submission: February 13, 2020
- Notification: May 15, 2020
- Camera-ready: June 17, 2020
- Short Promotional Video (Required): July 1, 2020
- Conference (San Diego, California): August 22-27, 2020
We invite submission of papers describing innovative research on all aspects of knowledge discovery and data mining, ranging from theoretical foundations to novel models and algorithms for data mining problems in science, business, medicine, and engineering. Visionary papers on new and emerging topics are also welcome, as are application-oriented papers that make innovative technical contributions to research. Authors are explicitly discouraged from submitting incremental results that do not provide major advances over existing approaches.
All deadlines are at 11:59PM Alofi Time. There will be absolutely no exception to these deadlines.
Topics of interest include, but are not limited to:
- Data Science: Methods for analyzing scientific and business data, social networks, time series; mining sequences, streams, text, web, graphs, rules, patterns, logs data, IoT data, spatio-temporal data, biological data; recommender systems, computational advertising, multimedia, finance, bioinformatics.
- Big Data: Large-scale systems for text and graph analysis, machine learning, optimization, sampling, parallel and distributed data mining (cloud, map-reduce, federated learning), novel algorithmic and statistical techniques for big data.
- Foundations: Models and algorithms, asymptotic analysis; model selection, dimensionality reduction, relational/structured learning, matrix and tensor methods, probabilistic and statistical methods; deep learning, meta learning, AutoML, reinforcement learning; classification, clustering, regression, semi-supervised and unsupervised learning; personalization, security and privacy, visualization; fairness, interpretability and robustness.
KDD is a dual track conference hosting both a Research track and an Applied Data Science track. Due to the large number of submissions, papers submitted to the Research track will not be considered for publication in the Applied Data Science track and vice versa. Authors are encouraged to read the track descriptions carefully and to choose an appropriate track for their submissions. Submissions are limited to a total of nine (9) pages, including all content andreferences, and must be in PDF format and formatted according to the new Standard ACM Conference Proceedings Template. For LaTeX users: unzip acmart.zip, make, and use sample-sigconf.tex as a template.
Additional information about formatting and style files is available online at: https://www.acm.org/publications/proceedings-template.
Papers that do not meet the formatting requirements will be rejected without review. In addition, authors can provide an optional two (2) page supplement at the end of their submitted paper (it needs to be in the same PDF file and start at page 10) focusedon reproducibility. This supplement can only be used to include (i) information necessary for reproducing the experimental results, insights, or conclusions reported in the paper (e.g., various algorithmic and model parameters and configurations, hyper-parameter search spaces, details related to dataset filtering and train/test splits, software versions, detailed hardware configuration, etc.), and (ii) any pseudo-code, or proofs that due to space limitations, could not be included in the main nine-page manuscript, but that help in reproducibility (see reproducibility policy below for more details).
The Research track follows a double-blind review process. Submitted papers must not include author names and affiliations and they must be written in a way so that they do not break the double-blind reviewing process. If the preliminary version of a paper was posted in arXiv, the authors should NOT mention as their own paper in the submission. Papers that violate the double-blind review requirements will be desk rejected.
Website for submissions: https://easychair.org/conferences/?conf=kdd20
SIGKDD Policy on Double Submission, Plagiarism, and Misrepresentation
Papers submitted to SIGKDD cannot be simultaneously under review or consideration in any other venue (or in different tracks of KDD) during the entire SIGKDD review period (i.e., from paper submission to notification dates). This includes conferences, workshops, journals, and any other venues that have published proceedings. The only exception is for papers submitted to ArXiv before the SIGKDD submission deadline.
Papers submitted to SIGKDD must have substantial novelty compared to any previous work, including other works by the same authors. Any overlap (in content, methods, writing, etc.) with prior work must be properly cited or attributed. SIGKDD also takes cases of plagiarism very seriously (including self-plagiarism), as well as author misrepresentation and inclusion of false content.
Details of the full policy and handling of potential violations can be found at: https://www.kdd.org/kdd2020/calls/view/sigkdd-policy-on-double-submission-plagiarism-and-misrepresentation
Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility. Authors are strongly encouraged to make their code and data publicly available whenever possible. In addition, authors are strongly encouraged to also report, whenever possible, results for their methods on publicly available datasets. Algorithms and resources used in a paper should be described as completely as possible to allow reproducibility. This includes experimental methodology, empirical evaluations, and results. The authors are encouraged to take advantage of the optional two-page supplement to provide the appropriate information. The reproducibility factor will play an important role in the assessment of each submission.
Every person named as the author of a paper must have contributed substantially both to the work described in the paper and to the writing of the paper. Every listed author must take responsibility for the entire content of a paper. Persons who do not meet these requirements may be acknowledged, but should not be listed as authors. Post-submission changes to the author list are not allowed.
No dual submissions are allowed. Submitted papers must describe work that is substantively different from work that has already been published, or accepted for publication, or submitted in parallel to other conferences or journals.
Violations on the dual submission policy may lead to immediate desk rejection and further penalties including prohibition of submitting to conferences and journals sponsored by SIGKDD or/and ACM for a certain period. The employers of the violating authors may be notified. Details of the full policy and handling of potential violations can be found at: https://www.kdd.org/kdd2020/calls/view/sigkdd-policy-on-double-submission-plagiarism-and-misrepresentation
Conflicts of Interest
During the submission process, enter the email domains of all institutions with which you have an institutional conflict of interest. You have an institutional conflict of interest if you are currently employed or have been employed at this institution in the past three years, or you have extensively collaborated with this institution within the past three years. Authors are also required to identify all PC/SPC members with whom they have a conflict of interest, e.g., advisor, student, colleague, or coauthor in the last five years.
Additional information about ACM’s Conflict of Interest policy, which KDD follows, can be found at https://www.acm.org/publications/policies/conflict-of-interest.
KDD follows ACM’s policies, which are described at https://www.acm.org/publications/policies/retraction-policy.
AttendanceFor each accepted paper, at least one author must attend the conference and present the paper. Authors of all accepted papers must prepare a final version for publication, a poster, and a three-minute short video presentation (details will be in the acceptance notification).
Accepted papers will be published in the conference proceedings by ACM and also appear in the ACM Digital Library. The rights retained by authors who transfer copyright to ACM can be found here.
AUTHORS TAKE NOTE: The official publication date is the date the proceedings are made available in the ACM Digital Library. This date for KDD 2020 is on or after July 15, 2020. The official publication date affects the deadline for any patent filings related to published work.
Wei Wang and Heng Huang
Research Track PC co-Chairs of KDD-2020
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