App usage on-the-move: Context- and commute-aware next app prediction

Author:

Kang YufanORCID,Rahaman Mohammad Saiedur,Ren Yongli,Sanderson Mark,White Ryen W.,Salim Flora D.

Publisher

Elsevier BV

Subject

Software,Computer Science Applications,Hardware and Architecture,Computer Networks and Communications,Information Systems

Reference47 articles.

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3. Z. Shen, K. Yang, W. Du, X. Zhao, J. Zou, DeepAPP: a deep reinforcement learning framework for mobile application usage prediction, in: Proceedings of the 17th Conference on Embedded Networked Sensor Systems, 2019, pp. 153–165.

4. Appusage2vec: Modeling smartphone app usage for prediction;Zhao,2019

5. A multilevel graph approach for predicting bicycle usage in London area;Colace,2020

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1. Understanding Mobile Information Needs and Behaviours;Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing;2023-10-08

2. Unsupervised video anomaly detection in UAVs: a new approach based on learning and inference;Frontiers in Sustainable Cities;2023-06-07

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