<｜begin▁of▁sentence｜>### Instruction:
As a real estate developer, you may want to analyze the cohesiveness of your project team to ensure efficient collaboration and communication. Using the "similarity_inverse_log_weighted" function in the igraph API, you can calculate the inverse log-weighted similarity coefficient of team members based on their interactions and contributions to the project. This analysis can help you identify potential bottlenecks or areas where collaboration can be improved, ultimately enhancing the overall efficiency of the development process.
### Response:
from igraph import Graph

# Assuming 'graph_data.gml' is a file containing graph data
# Read the graph from a .gml file
graph = Graph.Read_GML('graph_data.gml')

# Compute the inverse log-weighted similarity coefficient of vertices
similarity_coefficients = graph.similarity_inverse_log_weighted()

# Print the similarity coefficients
print(similarity_coefficients)
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