DeepApp: characterizing dynamic user interests for mobile application recommendation-Reference-Cited by-同舟云学术

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DeepApp: characterizing dynamic user interests for mobile application recommendation

Published:2023-05-02 Issue:5 Volume:26 Page:2623-2645
ISSN:1386-145X
Container-title:World Wide Web
language:en
Short-container-title:World Wide Web

Author:

Liang Yunji,Liu Lei,Huangfu Luwen,Wang Zhu,Guo Bin

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Link

https://link.springer.com/content/pdf/10.1007/s11280-023-01161-3.pdf

Reference44 articles.

1. Tu, Z., Li, Y., Hui, P., Su, L., Jin, D.: Personalized mobile app recommendation by learning user’s interest from social media. IEEE Trans. Mob. Comput. 19(11), 2670–2683 (2020)

2. Wang, X., Wang, C., Chen, X., Fu, X., Han, J., Wang, X.: Measurement and analysis on large-scale offline mobile app dissemination over device-to-device sharing in mobile social networks. World Wide Web. 23(4), 2363–2389 (2020)

3. Xu, Y., Zhu, Y., Shen, Y., Yu, J.: Leveraging app usage contexts for app recommendation: a neural approach. World Wide Web. 22(6), 2721–2745 (2019)

4. Peng, M., Zeng, G., Sun, Z., Huang, J., Wang, H., Tian, G.: Personalized app recommendation based on app permissions. World Wide Web. 21(1), 89–104 (2018)

5. Zhao, S., Li, S., Ramos, J., Luo, Z., Jiang, Z., Dey, A.K., Pan, G.: User profiling from their use of smartphone applications: A survey. Pervasive Mob. Comput. 59, 101052 (2019)

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1. App Recommendation Model Based on Heterogeneous Graph Collaborative Filtering;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

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