Continuing the tradition of bridging the gap between research and application, we are excited to call for participation in two flavors of tutorials at KDD 2017:
- Traditional Tutorials
- Hands-on Tutorials.
A Traditional Tutorial will cover the state-of-the-art research, development and applications in a specific data mining related area, and stimulate and facilitate future work. Tutorials on interdisciplinary directions, novel and fast growing directions, and significant applications are highly encouraged. We also encourage tutorials in areas that are somewhat different from the usual KDD mainstream, but still very much related to KDD mission and objectives of gaining insight from data.
A Hands-on Tutorial will feature in-depth hands-on training on cutting edge systems and tools of relevance to data mining and machine learning community. These sessions are targeted at novice as well as moderately skilled users. The focus should be on providing hands-on experience to the attendees. The pace of the tutorial should be set such that beginners can follow along comfortably. The tools & systems themselves must be available under open-source licenses (e.g. Apache 2.0, MIT, BSD etc.) and have proven track record of success in the community. Tutorials should introduce the motivation behind the tool, associated fundamental concepts, and work through examples and demonstrate its application to relatable real-life use cases.Read More