The last decade has witnessed the rise of big data in game development as the increasing proliferation of internet-enabled gaming devices has made it easier than ever before to collect large amounts of player-related data. At the same time the emergence of new business models and the diversification of the player base have exposed a broader potential audience which attaches great importance to being able to tailor game experiences to a wide range of preferences and skill levels. This, in turn, has led to a growing interest in data mining techniques as they offer new opportunities for deriving actionable insights in order to inform game design, to ensure customer satisfaction, to maximize revenues, and to drive technical innovation.
This edited volume seeks to provide a comprehensive overview of data mining applications in gaming. Through research articles, case studies, and post-mortems written by subject experts it shows how data mining can be utilized in various aspects of game production, spanning areas such as game analytics, artificial intelligence, and procedural content generation.
Topics covered might include: techniques for player profiling and player experience modeling, approaches for analyzing player communities and social in-game structures, retention analysis and churn prediction, visual game analytics, innovative artificial intelligence solutions utilizing gameplay data, and data-driven approaches to procedural content generation. This book is intended as an ideal companion for practitioners, academic researchers, and students seeking knowledge on the latest practices in game data mining.
The book will be published by CRC Press, Taylor & Francis Group, as part of the Data Analytics Applications book series, edited by Jay Liebowitz.