mlsanityData to 14 Oct 2026

Development of an End-to-end Machine Learning System with Application to In-app Purchases

arXiv 2412.12390 ↗First posted 16 Dec 2024cs.LGcited by 0

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Abstract (arXiv)

Machine learning (ML) systems have become vital in the mobile gaming industry. Companies like King have been using them in production to optimize various parts of the gaming experience. One important area is in-app purchases: purchases made in the game by players in order to enhance and customize their gameplay experience. In this work we describe how we developed an ML system in order to predict when a player is expected to make their next in-app purchase. These predictions are used to present offers to players. We briefly describe the problem definition, modeling approach and results and then, in considerable detail, outline the end-to-end ML system. We conclude with a reflection on challenges encountered and plans for future work.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 16 Dec 2024.

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6 of 14 references.

References · 6

  1. 2017On Calibration of Modern Neural Networkscited by 4,960
  2. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
  3. 2019Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AIcited by 1,552
  4. 2019Continual Learning in Practicecited by 28
  5. 2021Looper: An end-to-end ML platform for product decisionscited by 9
  6. 2023Scalable End-to-End ML Platforms: from AutoML to Self-servecited by 2

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