During these years, IT has tremendously improved, and has dived deeply into knowledge. Many companies have started to focus on how to extract knowledge and use it into their business in order to improve their return of investment.
We invite submission of papers/extended abstracts/presentations 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 in IT.
- Prospective authors are invited to submit no more than 300 word abstract through the below form.
- Technical Paper abstracts should include Introduction, Methods, Results, and Discussion sections.
- All abstracts will be reviewed by the symposium committee. Submitted work 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.
- Authors will be notified about the status of their abstract submission (accepted, rejected, or if revisions are required for acceptance) by 16 March 2017.
- Authors of accepted abstracts will be asked to submit their work in the form of a paper or a presentation by 30 March 2017.
- 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.
