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In the last few years, we have witnessed a true revolution in the video-game industry, as both emerging mobile games and traditional video-game platforms have become continuously connected to the Internet. This has contributed to widen the audience for video games (casual gamers) and to the appearance of a series of new economic models (free-to-play, in-app purchases) that are gradually gaining more importance in a sector that traditionally relied on expensive one-time purchases or subscriptions.

More importantly, this recent paradigm shift enables game developers both to collect a vast amount of data in real time and to maintain active relationships with their players. To fully take advantage of this new scenario, it is essential to develop appropriate statistical and learning methods to model and predict player behavior, which should scale to large datasets and allow intuitive visualization of the results, among other features.

Given the richness of the possibility for actions that modern game afford, players can actually express very nuanced motivation and personalities encoded in their in-game behaviors. The current trend to include in games in-app purchases and social features, together with the extraordinary level of granularity of the collected data, turns game datasets into a unique source of information to study human behavior, including social and consumer dynamics.

The objective of this special session on Game Data Science is to gather together experts from industry and academia, providing a stimulating atmosphere that fosters collaboration and mutual exchange. We call for top-notch and inspiring contributions that explore the development and application of new technologies toward this new paradigm in the realm of video games.

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Topics of interest for GDS 2017 include (but are not limited to):

Machine learning applied to game datasets

  • Advanced methods

  • Dimensionality reduction and feature extraction

  • Modeling of player behavior and social interactions

  • Churn prediction

  • Forecast of time series

  • 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

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重要日期
  • 会议日期

    10月19日

    2017

    10月21日

    2017

  • 10月21日 2017

    注册截止日期

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