Code for greedy and LP rounding based seed set selection in a mult-advertiser scenario. Author - Kartik Lakhotia
Directory structure
- greedy - greedy algorithm
- lpSol - LP rounding based algorithm
Uses CPLEX as an LP solver and python PULP interface for creating the LP
To run a particular algorithm, go to the corresponding directory and use following commands.
make
./imm_greedy -dataset *** -epsilon *** -k *** -h ***"
k is the total seed set size for all advertisers
h is the max number of advertisements per user
Directory containing the following files:
attribute.txt - specify problem parameters
n - number of vertices
m - number of edges
a - number of advertisers
g - number of influence networks (either 1 or a)
budgets.txt - max budget for each advertiser
graph_ic.inf - edge list
prob<i> - edge probabilities for each influence network
For reference, checkout the ./testGraph/ directory
This code was built on top of the single greedy influence maximization code available at\
https://sourceforge.net/projects/im-imm/