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User Role Discovery and Optimization Method based on K-means + Reinforcement learning in Mobile Applications
[article]
2021
arXiv
pre-print
With the widespread use of mobile phones, users can share their location and activity anytime, anywhere, as a form of check in data. These data reflect user features. Long term stable, and a set of user shared features can be abstracted as user roles. The role is closely related to the user's social background, occupation, and living habits. This study provides four main contributions. Firstly, user feature models from different views for each user are constructed from the analysis of check in
arXiv:2107.00862v1
fatcat:jxrorr67o5a3xp63ebceumns7q