<｜begin▁of▁sentence｜>### Instruction:
As a process engineer, you have been tasked with optimizing the manufacturing process of a new line of political books related to US politics. The network of books is represented by the 'polbooks.gml' file, and your goal is to apply the Markov Clustering algorithm to identify clusters within this network. The parameters specified include an expansion factor of 2, an inflation factor of 2, an initialization value for self-loops set to 0.1, a maximum of 100 iterations, and using a pruning threshold of 0.001, pruning every 2 iterations, and checking for convergence every 10 iterations. Once the clustering is completed, you are then required to generate the JSON representation of the resulting Node Clustering.
### Response:
import networkx as nx
from cdlib import algorithms

# Read the graph from the GML file
G = nx.read_gml('polbooks.gml')

# Apply the Markov Clustering algorithm
coms = algorithms.markov_clustering(G, expansion=2, inflation=2, loop_value=0.1, iterations=100, pruning_threshold=0.001, pruning_frequency=2, convergence_check_frequency=10)

# Generate JSON object from NodeClustering
coms_json = coms.to_json()
print(coms_json)
<|EOT|>
