Download datasets from [Crime Data] (https://catalog.data.gov/dataset/crime-data-from-2020-to-present). And put the files in ./crime_detection/data.
And run data_pre_process.py and behavioral_space_generation.py to generate the crime behavioral structure graph.
Download datasets from [ZhihuRec Data] (https://github.com/THUIR/ZhihuRec-Dataset). And put the files in ./behavior_prediction/data/zhihurec/ori.
Following the article "A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-Sharing (https://arxiv.org/pdf/2106.06467.pdf),"
data from files info_user.csv, info_answer.csv, and inter_impression.csv were extracted, specifically the first 7,963, 81,214, and 1,000,026 records, respectively.
These extracted records were then generated into files info_user_small.csv, info_answer_small.csv, inter_impression_small.csv, which were placed in the directory path ./behavior_prediction/data/zhihurec/ori.
And run preprocess.py and bsg.py to generate the zhihu behavioral structure graph, run rgcn.py, fc.py and fcori.py to generate zhihu_vec and zhihu_ori datasets for RecBole.
Download datasets from [Fraudulent Transaction Data] (https://www.kaggle.com/datasets/chitwanmanchanda/fraudulent-transactions-data). And put the files in ./graph_Gen.