├── Distance2Pre_ Personalized Spatial Preference for Next Point-of-Interest Prediction.pdf ├── README.md ├── code ├── Ubuntu, Theano, Python27.txt ├── programs │ ├── __init__.py │ ├── poidata │ │ ├── Foursquare.rar │ │ ├── Gowalla.rar │ │ └── 解压可得数据集.txt │ ├── prog_bpr_gru_spatial.py │ ├── prog_ca_rnn.py │ ├── prog_fpmc_lr.py │ ├── prog_poi2vec.py │ └── prog_prme.py └── public │ ├── BPR.py │ ├── CA_RNN.py │ ├── FPMC_LR.py │ ├── GRU.py │ ├── GRU_Spatial.py │ ├── Global_Best.py │ ├── Load_Data_Poi2vec.py │ ├── Load_Data_by_length.py │ ├── Load_Data_fpmc_lr.py │ ├── Load_Data_prme.py │ ├── POI2Vec.py │ ├── PRME.py │ ├── Valuate.py │ └── __init__.py ├── plot_matlab ├── check_which_line_is_significant_choose_3_4_9.m ├── data.m ├── data.mat ├── plot_histogram.m ├── plot_line_cluster_in_one_fig_and_three_usr_in_three_fig.m ├── plot_wd.m └── 维度图 │ ├── cluster_3_4_9_user_688_1537_1591.fig │ ├── cluster_3_4_9_user_688_1537_1591.pdf │ ├── figure_to_pdf.vsdx │ ├── legend.fig │ ├── legend1.pdf │ ├── legend2.pdf │ ├── matlab figure直接复制到visio里，再另存为最高质量的pdf，不失真.txt │ ├── split_cluster_3_4_9.pdf │ ├── split_user_688_1537_1591.pdf │ ├── user_1537_in_cluster_4.fig │ ├── user_1591_in_cluster_9.fig │ ├── user_688_in_cluster_3.fig │ ├── values_foursquare.fig │ ├── values_foursquare.pdf │ ├── values_gowalla.fig │ ├── values_gowalla.pdf │ ├── wds_four.fig │ ├── wds_four.pdf │ ├── wds_gowa.fig │ └── wds_gowa.pdf └── results ├── test ├── foursquare - all.txt └── gowalla - all.txt └── 距离间隔向量做聚类 ├── 738_758_1020.npy ├── 738_758_1020【重要，这三个用户的spatial preference，就是各距离区间的概率值】.txt ├── a_user_in_cluster3.pdf ├── a_user_in_cluster4.pdf ├── a_user_in_cluster9.pdf ├── users_map 三个用户放到图里.vsdx ├── users_map.pdf ├── 将用户轨迹绘制在地图上 user_trajectory.ipynb ├── 截取后 a_user_1537_in_cluster_4.pdf ├── 截取后 a_user_1591_in_cluster_9.pdf ├── 截取后 a_user_688_in_cluster_3.pdf ├── 淡化背景 user1020_cluster9.html ├── 淡化背景 user738_cluster4.html ├── 淡化背景 user758_cluster3.html ├── 淡化背景 带标点 user1020_cluster9.html ├── 淡化背景 带标点 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