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InfluenceMaximization: algorithms in C# (.NET or Mono is required for compiling the project)
ConfigFilesExamples: configuration examples
data_utils: data preprocessing files in Python
Data transformation
data_stat.py: transform the original data from SNAP and get graph statistics information.
data_stat.py
def graph_reform(infile, outfile, head_skip)
Seed probability functions assignment
func_rand_assign.py: assign discounts to users with configurable probability.
func_rand_assign.py
def func_rand_assign(outfile, numnodes)
The assignments of seed probability functions used in our experiments can be found HERE.
Use the examples in ConfigFilesExamples to write a config file.
The config files we used in our paper can be download HERE.
Execute the compiled executable file (e.g., .exe) to read the config file (examples) to run the experiment.