KDD 2016 Call for Research Track Papers
Paper submission and deadlines
Submission date: February 12, 2016
Notification date: May 12, 2016
Camera Ready: June 12, 2016
Short Promotional Video (Required): June 17, 2016
Source Code and Presentation (Optional): June 17, 2016
Note: This year, (aside from the usual ACM/Sheridan-centric camera ready procedures) we will ask authors to make electronic versions of their manuscripts available at a publicly hosted Website immediately after acceptance, and give them the option of updating it at the camera ready deadline when they submit official versions to ACM/Sheridan printing.
KDD accepts only electronic submissions in PDF format at https://cmt.research.microsoft.com/KDD2016/ (Active for submissions only in January, 2016)
The deadline for submission is February 12, 2016, at 11:59PM Pacific Standard Time.
Description of the Research track
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 significant advances over existing approaches.
Papers submitted to the Research Track are solicited in all areas of data mining, knowledge discovery, and large-scale data analytics, including, but not limited to:
- Big Data: Distributed data mining and machine learning platforms and algorithms, systems for large-scale data analytics of textual and graph data, large-scale machine learning systems, distributed computing (cloud, map-reduce, MPI), large-scale optimization, and novel statistical techniques for big data.
- Data Science: Methods for analyzing scientific data, business data, social network analysis, recommender systems, mining sequences, time series analysis, online advertising, bioinformatics, systems biology, text/web analysis, mining temporal and spatial data, and multimedia processing.
- Foundations of Data Mining: Data mining methodology, data mining model selection, visualization, asymptotic analysis, information theory, security and privacy, graph and link mining, rule and pattern mining, web mining, dimensionality reduction and manifold learning, combinatorial optimization, relational and structured learning, matrix and tensor methods, classification and regression methods, deep learning, semi-supervised learning, and unsupervised learning and clustering.
Evaluation and decision criteria
As per KDD tradition, reviews are not double-blind, and author names and affiliations should be listed.
Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Authors are strongly encouraged to make data and code publicly available whenever possible.
Papers will be reviewed by members of the KDD program committee and decisions will be emailed to all authors by May 12, 2016.
Papers are limited to 10 pages, including references, diagrams, and appendices, if any. The format is 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.
Note: Papers that do not meet the formatting requirements will be rejected without review.
Dual submission policy
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 to journals. Such submissions violate our dual submission policy.
Conflicts of interest
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.
- You have extensively collaborated with this institution within the past three years.
- Furthermore, all authors are required to identify all members of the program committee with which they have a conflict of interest. Select all PC and SPC members who have been your PhD advisor; for whom you have been a PhD advisor; with whom you have co-authored a paper published in or since 2010;
- If there are any other PC or SPC members who you believe have, or may be perceived to have, a conflict of interest not covered above, please notify the PC Chairs by email to the id research-chairs2016 and the domain name kdd.org (put an @ in the middle).
Accepted papers will be published in the conference proceedings by ACM and also appear in the ACM Digital Library.