1 Dataset raw data download: dataset C and dataset D https://www.dropbox.com/sh/ist4ojr03e2oeuw/AAD5NkpAFg1nOI2Ttug3h2qja?dl=0 initial events：raw data sets are transferred to initial events，dataset C --> data/events_initial_A、dataset D -->data/events_initial_B

2 Dataprocess

step1: cal_faults.py read raw data faults.csv from dataset C and dataset D, construct offline_data_set_info.json和online_data_set_info.json

step2: runtime evn configuration, log4j

step3: use the method proposed in this paper to preprocess event data for train & test

step4: DataSetGraphSimGenerator.py split train & test dataset

3 Method

#-----------fault KG constuction----------

KBConstruction.py

#---------------KGroot--------------------

graph_sim_dej_X.py #X represents the normalization of Dataset A/Dataset B.

#-------KGroot without GCN--------------

graph_sim_no_gcn_dej_X.py

#---------KGroot without KG--------------

graph_sim_no_kb_dej_X.py