Yizhi Liu1,3, Rutian Qing1,3, Yijiang Zhao1,3,*, Xuesong Wang1,3, Zhuhua Liao1,3, Qinghua Li1,2, Buqing Cao1,3
Computer Systems Science and Engineering, Vol.45, No.3, pp. 2505-2519, 2023, DOI:10.32604/csse.2023.021615
- 21 December 2022
Abstract Short-term GPS data based taxi pick-up area recommendation can improve the efficiency and reduce the overheads. But how to alleviate sparsity and further enhance accuracy is still challenging. Addressing at these issues, we propose to fuse spatio-temporal contexts into deep factorization machine (STC_DeepFM) offline for pick-up area recommendation, and within the area to recommend pick-up points online using factorization machine (FM). Firstly, we divide the urban area into several grids with equal size. Spatio-temporal contexts are destilled from pick-up points or points-of-interest (POIs) belonged to the preceding grids. Secondly, the contexts are integrated into deep factorization More >
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