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KDD 2019 : 25TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING

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Conference Series : Knowledge Discovery and Data Mining
 
Link: http://www.kdd.org/kdd2019/
 
When Aug 3, 2019 - Aug 7, 2019
Where Anchorage, Alaska - USA
Submission Deadline Feb 3, 2019
Notification Due Apr 28, 2019
Final Version Due May 17, 2019
 

Call For Papers


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KDD 2019 Call for Research Papers
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Details in https://www.kdd.org/kdd2019/calls/view/kdd-2019-call-for-research-papers
Website for submissions: https://easychair.org/conferences/?conf=kdd2019 .

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Key dates
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Submission: February 3, 2019
Notification: Apr 28, 2019
Camera-ready: May 17, 2019
Short Promotional Video (Required): June 2, 2019
Conference (Anchorage, Alaska): August 4 to August 8, 2019

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Description
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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:

Big Data: Large-scale systems for text and graph analysis, machine learning, optimization, parallel and distributed data mining (cloud, map-reduce), novel algorithmic and statistical techniques for big data.
Data Science: Methods for analyzing scientific and business data, social networks, time series; mining sequences, streams, text, web, graphs, rules, patterns, logs data, spatio-temporal data, biological data; recommender systems, computational advertising, multimedia, finance, bioinformatics.
Foundations: Models and algorithms, asymptotic analysis; model selection, dimensionality reduction, relational/structured learning, matrix and tensor methods, probabilistic and statistical methods; deep learning; manifold learning, classification, clustering, regression, semi-supervised and unsupervised learning; personalization, security and privacy, visualization.

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Submission Directions
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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 and references, 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) focused on 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. Papers that violate the double-blind review requirements will be desk rejected.

Because of the double-blind review process, non-anonymous papers that have been issued as technical reports or similar, in particular in arXiv, either prior to KDD submission or during the review process, cannot be submitted to the research track.

Website for submissions: https://easychair.org/conferences/?conf=kdd2019 .

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Important Policies
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Reproducibility
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.

Important Note: To encourage reproducibility of the results presented in KDD, only papers that include this two-page supplement with the necessary reproducibility-related information will be considered for the best paper awards.

Authorship
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.

Dual Submissions
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.

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.

Retraction Policy
KDD follows ACM’s policies, which are described at https://www.acm.org/publications/policies/retraction-policy .

Attendance
For 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).

Copyright
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 2019 is on or after July 11, 2019. The official publication date affects the deadline for any patent filings related to published work.

Contact Information
Email: research2019@kdd.org

George Karypis and Evimaria Terzi

Research Track PC co-Chairs of KDD-2019


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