| |||||||||||||||
GDS 2016 : Game Data Science - Special Session, DSAA | |||||||||||||||
Link: https://www.ualberta.ca/~dsaa16 | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
============================================================
IEEE DSAA'2016 Special Session Game Data Science - GDS 2016 Montreal, Canada October 17-19, 2016 https://www.ualberta.ca/~dsaa16/ http://gamedatascience.org/ ============================================================ ---- AIMS AND SCOPE In the past years, both traditional video game platforms and emerging mobile games have tended to become always connected to the Internet. This allows game developers to collect a huge amount of data in real time while maintaining an active relationship with the players. This recent revolution of the video-game industry creates a broad range of new challenges for both research and business applications. The current trend to include social features and in-app purchases to games, combined with the exceptional level of granularity of the data collected makes game datasets a unique source of information to observe and analyze human behavior, including social and consumer dynamics. It is paramount that research efforts focus on the development of adequate statistical and learning methods able to model and predict player behavior, that scale to big datasets and allow an intuitive visualization of the results. In this special session on Game Data Science we aim to bring together experts from research and industry, providing a stimulating atmosphere to promote collaborations and mutual exchange. The goal of the GDS session is to gather outstanding contributions, pursuing the development and application of new technologies towards a new paradigm in video-games. This special session calls for work on data science that help to understand and predict player behavior, addressing this challenge from three points of view: the statistical/machine learning methodology, visualization analysis and data science product deployment. ---- TOPICS OF INTEREST Machine learning applied to game data: - Advanced methods - Dimensionality reduction and feature extraction - Modeling of the player behavior and social interactions - Churn prediction - Forecast of time series of player activity - Forecast of the impact of game and marketing events on player behavior - Clustering of player profiles and activity - Virality models Deployment of game data science in products: - Big data architecture challenges - Novel algorithms that scale with big datasets - A/B testing of game data science features - Visualizations and visual analytics - Novel visualization techniques for time-series analysis - Game data science product management - Game data science applied to game development ---- SPECIAL SESSION WEBSITE http://gamedatascience.org/ ---- SUBMISSION WEBSITE https://easychair.org/conferences/?conf=dsaa2016 When you submit a paper, select the track "Special session". ---- IMPORTANT DATES Paper Submission deadline: 12 June, 2016 (updated) Notification of acceptance: 15 July, 2016 Final Camera-ready papers due: 19 August, 2016 ---- PUBLICATIONS Accepted special session submissions will be published by IEEE and included into the IEEE Xplore Digital Library. --- CHAIRS Alain Saas, Silicon Studio (Japan) Africa Perianez, Silicon Studio (Japan) --- Program Committee Alessandro Canossa, Northeastern University (USA) Thomas Debeauvais, University of California Irvine (USA) Benjamin Devienne, Gameloft (Canada) Anders Drachen, Aalborg University (Denmark) Austin Frank, Riot Games (USA) Kirsti Laurila, Rovio Entertainment Ltd. (Finland) Julian Runge, Wooga (Germany), Humboldt University of Berlin (Germany) Rafet Sifa, Fraunhofer IAIS (Germany) Ben Weber, Electronic Arts (USA) |
|