[Infovis] CFP: KDD 2014 Workshop on Large-Scale Sports Analytics

John Stasko john.stasko at cc.gatech.edu
Thu May 22 17:47:03 CEST 2014

=== Call for Submissions ===

When: August 24th

Where: New York City, NY

Website: http://large-scale-sports-analytics.org/


Virtually every aspect of sports analytics is now entering the “Big 
Data” phase, and the interest in effectively mining, modeling, and 
learning from such data has also been correspondingly growing. Relevant 
data sources include detailed play-by-play game logs, tracking data, 
physiological sensor data to monitor the health of players, social media 
and text-based content, and video recordings of games.

The objective of this workshop is to bring together researchers and 
analysts from academia and industry who work in sports analytics, data 
mining and machine learning. We hope to enable meaningful discussions 
about state-of-the-art in sports analytics research, and how it might be 
improved upon.

We seek poster submissions (which can be both preliminary research as 
well as recently published work) on topics including but not limited to:

* Spatiotemporal modeling
* Video, text and social media analysis
* Feature selection and dimensionality reduction
* Feature learning and latent factor models
* Computational rationality
* Real-time predictive modeling
* Interactive analysis & visualization tools
* Sensor technology and reliability
* Labeling and annotation of events/activities/tactics
* Real-time/deployed analytical systems
* Knowledge discovery of player/team/league behaviors
* Game theory

Submission Details:

Poster submissions should be extended abstracts no more than 4 pages in 
length (in KDD format, do not need to be anonymous).  Extended abstracts 
should be submitted by June 17th 11:59 PM PDT, and can be submitted 
electronically via: https://cmt.research.microsoft.com/LSSA2014

Important Dates:
Submission - 17th June 2014 11:59 PM PDT
Notification - 8th July 2014
Workshop - 24th August 2014

Yisong Yue (Disney Research) <yisong.yue at disneyresearch.com>
Patrick Lucey (Disney Research) <patrick.lucey at disneyresearch.com>
Peter Carr (Disney Research) <peter.carr at disneyresearch.com>
Jenna Wiens (MIT) <jwiens at mit.edu>

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