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The rapid growth of location acquisition technologies makes Point-of-Interest(POI) recommendation possible due to redundant user check-in records.
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R. Ding, Z. Chen, and X. Li, “Spatial-temporal distance metric embedding for time-specific poi recommendation,” IEEE Access , vol. 6, pp. 67 035–67 045, 2018
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C. Ma, Y. Zhang, Q. Wang, and X. Liu, “Point-of-interest recommendation: Exploiting self-attentive autoencoders with neighbor-aware influence,” in Proceedings of the 27th ACM International Conference on Information and Knowledge Management, CIKM 2018, Torino, Italy, October 22-26, 2018 , 2018, pp. 697–706. [Online]. Available: https://doi.org/10.1145/3269206.3271733
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T. Qian, B. Liu, Q. V. H. Nguyen, and H. Yin, “Spatiotemporal representation learning for translation-based poi recommendation,” ACM Trans. Inf. Syst. , vol. 37, no. 2, pp. 18:1–18:24, Jan. 2019. [Online]. Available: http://doi.acm.org/10.1145/3295499
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J. Yao, C. Li, Y. Sun, Keqiang andCai, H. Li, W. Ouyang, and H. Li, “Ndc-scene: Boost monocular 3d semantic scene completion in normalized devicecoordinates space,” in 2023 IEEE/CVF International Conference on Computer Vision (ICCV) . IEEE Computer Society, 2023, pp. 9421–9431
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Y. Zhang, M. Zhu, Y. Gong, and R. Ding, “Optimizing science question ranking through model and retrieval-augmented generation,” International Journal of Computer Science and Information Technology , vol. 1, no. 1, pp. 124–130, 2023
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2024
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2019
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2023
Cited alongside, same era.
L. Gao, G. Cordova, C. Danielson, and R. Fierro, “Autonomous multi-robot servicing for spacecraft operation extension,” in 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2023, pp. 10 729–10 735
2023
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2024
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2024
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