Predicting player disengagement and first purchase with event-frequency based data representation
Predicting player disengagement and first purchase with event-frequency based data representation
复制标题
使用基于事件频率的数据表示来预测玩家脱离和首次购买
DOI：
10.1109/cig.2015.7317919
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
P. Cowling
中科院分区：
文献类型：
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作者：
Hanting Xie;Sam Devlin;D. Kudenko;P. Cowling
在游戏行业，尤其是对于免费玩游戏来说，玩家留存和购买都是重要的问题。已经有几种方法研究了通过玩家在游戏过程中的行为来预测它们。然而，大多数当前的方法仅适用于特定的游戏，因为所使用的数据表示通常是特定于游戏的。本研究以游戏事件的发生频率作为数据表征，预测玩家的游戏退出行为和首次购买行为。该方法具有较好的通用性，因为事件存在于每一场比赛中，不需要任何事件的知识，但需要它们的频率。此外，这种基于事件频率的方法也将与Runge等人[1]最近的工作进行比较。
In the game industry, especially for free to play games, player retention and purchases are important issues. There have been several approaches investigated towards predicting them by players' behaviours during game sessions. However, most current methods are only available for specific games because the data representations utilised are usually game specific. This work intends to use frequency of game events as data representations to predict both players' disengagement from game and the decisions of their first purchases. This method is able to provide better generality because events exist in every game and no knowledge of any event but their frequency is needed. In addition, this event frequency based method will also be compared with a recent work by Runge et al. [1] in terms of disengagement prediction.