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Predicting player disengagement and first purchase with event-frequency based data representation

机译:通过基于事件频率的数据表示来预测玩家的脱离和首次购买

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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.
机译:在游戏产业中,尤其是对于免费游戏而言,玩家保留和购买是重要的问题。已经研究了几种方法来根据游戏过程中玩家的行为来预测它们。但是,大多数当前方法仅适用于特定游戏,因为所使用的数据表示通常是特定于游戏的。这项工作旨在利用游戏事件的发生频率作为数据表示,以预测玩家与游戏的脱离以及他们的首次购买决定。该方法能够提供更好的通用性,因为每个游戏中都存在事件,并且不需要任何事件的知识,但是需要它们的频率。此外,还将基于事件频率的方法与Runge等人的最新工作进行比较。 [1]在脱离预测方面。

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