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A contextual collaborative approach for app usage forecasting
2016
Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '16
Fine-grained long-term forecasting enables many emerging recommendation applications such as forecasting the usage amounts of various apps to guide future investments, and forecasting users' seasonal demands for a certain commodity to find potential repeat buyers. For these applications, there often exists certain homogeneity in terms of similar users and items (e.g., apps), which also correlates with various contexts like users' spatial movements and physical environments. Most existing works
doi:10.1145/2971648.2971729
dblp:conf/huc/WangYSZXLC16
fatcat:2v46rcz2sne5jd6p5jezn7agz4