SDM17: Call for Tutorials
Accepted Tutorials
An Introduction to Redescription Mining
Presenters: Pauli Miettinen, MPI-INF, Germany; Esther Galbrun, INRIA, France
IoT Big Data Stream Mining
Presenters: Gianmarco De Francisci Morales, QCRI, Qatar; Albert Bifet, Telecom-ParisTech, France; Latifur Khan, University of Texas at Dallas, USA; Joao Gama, University of Porto, Portugal; Wei Fan, Baidu Research, California, USA
Leveraging Propagations for Data Mining
Presenters: B. Aditya Prakash, Virginia Tech, USA; Naren Ramakrishnan, Virginia Tech, USA
Opportunities, Challenges and Methods for Higher Education Data Mining
Presenters: Huzefa Rangwala, George Mason University, USA; Aditya Johri, George Mason University, USA; Asmaa El Badrawy, University of Minnesota, USA; George Karypis, University of Minnesota, USA
Summarizing Large-Scale Graph Data
Presenter: Danai Koutra, University of Michigan, USA
The SIAM Data Mining (SDM17) Organizing Committee invites proposals for tutorials to be held in conjunction with the conference. Tutorials are an effective way to educate and/or provide the necessary background to the intended audience enabling them to understand technical advances.
For SDM17, we are seeking proposals for tutorials on all topics related to data mining. A tutorial may be a theme-oriented comprehensive survey, discuss novel data mining techniques or may center around successful and timely application of data mining in important application areas (e.g., medicine, national security, scientific data analysis). Tutorials on interdisciplinary research topics, novel and fast growing directions, and innovative applications are highly encouraged. For examples of typical SIAM tutorials, see the set of accepted tutorials at previous SIAM conferences SDM13, SDM14, SDM15, and SDM16.
Tutorials are open to all conference attendees without any extra fees. The typical tutorial will be 2 hours long (longer tutorials will be considered). Previous SDM conferences attracted up to 100 attendees in a tutorial.
Proposals should be submitted electronically with subject heading: “SDM 2017 Tutorial Proposal Submission” by October 8, 2016, 11:59 PM (US Pacific Time) to:
Prof. Jilles Vreeken
Saarland University and Max Planck Institute for Informatics
[email protected]
Proposals should be submitted in PDF format (for other formats please contact the tutorial chair first).
Proposals should include the following:
- Basic information: Title, brief description, name and contact information for each tutor, length of the proposed tutorial. If the intended tutorial is expected to take longer than 2 hours a rationale is expected. Also identify any other venues in which the tutorial has been or will be presented.
- Audience: Proposals must clearly identify the intended audience for the tutorial (e.g., novice, intermediate, expert).
- What background will be required of the audience?
- Why is this topic important/interesting to the SIAM data mining community?
- What is the benefit to participants?
- Provide some informal evidence that people would attend (e.g., related workshops).
- Coverage: Enough material should be included to provide a sense of both the scope of material to be covered and the depth to which it will be covered. The more details that can be provided, the better (up to and including links to the actual slides or viewgraphs). Note that the tutors should not focus mainly on their own research results. If, for certain parts of the tutorial, the material comes directly from the tutors' own research or product, please indicate this clearly in the proposal.
- Biographies: Provide brief biographical information on each tutor (including qualifications with respect to the tutorial's topic).
Timeline
- Submission: October 8, 2016, 11:59 PM (US Pacific Time)
- Decision Notification: November 8, 2016
- Complete Set of Tutorial Viewgraphs (Slides): February 15, 2017