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KDD 2018 Call for Research Papers
- Submission: February 11, 2018
- Notification: May 06, 2018
- Camera-ready: May 25, 2018
- (All deadlines are at 11:59PM Alofi Time) Note: There will be absolutely no exception to these deadlines.
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.
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. Submissions are limited to a total of 9 (nine) 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. Submitted papers will be assessed based on their novelty, technical quality, potential impact, insightfulness, depth, clarity, and reproducibility.
Website Submissions for KDD 2018 are being accepted at: https://easychair.org/conferences/?conf=kdd18.
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.
Every listed author must take responsibility for the entire content of a paper. Note that changes to the author list after the submission deadline is not 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.
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, e.g., advisor, student, colleague, or coauthor in the last five years.
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).
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 2018 is on or after Jul 11, 2018. The official publication date affects the deadline for any patent filings related to published work.
Chih-Jen Lin and Hui Xiong
Research Track PC Chairs of KDD-2018
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KDD 2018 - London, United Kingdom. 19 - 23 August 2018
The annual KDD conference is the premier interdisciplinary conference bringing together researchers and practitioners from data science, data mining, knowledge discovery, large-scale data analytics, and big data.