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SIGKDD 2017 : SIGKDD Call for Research Papers and Applied Data Science Papers

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Link: http://www.kdd.org/kdd2017/calls/view/kdd-2017-call-for-research-papers
 
When Aug 13, 2017 - Aug 17, 2017
Where Halifax, Nova Scotia, Canada
Submission Deadline Feb 17, 2017
Notification Due May 19, 2017
Final Version Due Jun 16, 2017
 

Call For Papers


KDD 2017 Call for Research Papers

Key dates

Submission: February 17, 2017

Notification: May 19, 2017

Camera-ready: June 16, 2017

Short Promotional Video (Required); June 16, 2017

Source Code and Presentation (Optional): June 16, 2017

(All deadlines are at 11:59PM Alofi Time)
Description

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.

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.
Submission directions

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.

Following KDD conference tradition, reviews are not double-blind, and author names and affiliations should be listed. There will be an author response phase between submission and final decision.

Submissions are limited to 8 (eight) pages of content and 1 (one) page for references and must be in PDF format and formatted according to the standard double column ACM Proceedings Template, Tighter Alternate style. Additional information about formatting and style files are available online at: http://www.acm.org/sigs/publications/proceedings-templates. Papers that do not meet the formatting requirements will be rejected without review. Submitted papers will be assessed based on their novelty, technical quality, potential impact, clarity, and reproducibility.
Submission site

Submissions site will open in Jan 2017. Please check back for further information.
Important policies
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. 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 reproducibility factor will play an important role in the assessment of each submission.
Authorship

Every listed author must take responsibility for the entire content of a paper. Changes to the author list after the submission deadline is not allowed.
Dual submissions

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. However, there are some exceptions to this rule.

Submission to KDD is permitted of a shorter version of a paper that has been submitted to a journal, but has not yet been published in that journal. Authors must declare such dual-submissions on the submission form. Authors must make sure that the journal in question allows dual concurrent submissions to conferences.
Submission is permitted for papers presented or to be presented at conferences or workshops without proceedings, or with only abstracts published.
Submission is permitted for papers that have previously been made available as a technical report or similar, in particular in arXiv.

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, eg, advisor, student, colleague, or coauthor in the last five years.
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. For accepted papers, the authors also agree that the papers will also be made available to general public on the KDD website.

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