Collaborative-Enhanced Prediction of Spending on Newly Downloaded Mobile Games under Consumption Uncertainty

arXiv:2404.08301v1 Announce Type: cross
Abstract: With the surge in mobile gaming, accurately predicting user spending on newly downloaded games has become paramount for maximizing revenue. However, the inherently unpredictable nature of user behavior poses significant challenges in this endeavor. To address this, we propose a robust model training and evaluation framework aimed at standardizing spending data to mitigate label variance and extremes, ensuring stability in the modeling process. Within this framework, we introduce a collaborative-enhanced model designed to predict user …

abstract arxiv become behavior challenges collaborative consumption cs.ir cs.lg endeavor games gaming however mobile mobile games mobile gaming nature prediction revenue robust spending training type uncertainty