<｜begin▁of▁sentence｜>### Instruction:
Given the Internet Graph which can be loaded from a GML file named 'as-22july06.gml', can you compare communities detected by the Louvain and Walktrap algorithms and visualize their similarity using a cluster map? Use adjusted mutual information as the scoring function to evaluate the similarity.
### Response:
import networkx as nx
from cdlib import algorithms, viz, evaluation

# Load the graph
G = nx.read_gml('as-22july06.gml')

# Perform community detection using different algorithms
communities_louvain = algorithms.louvain(G)
communities_walktrap = algorithms.walktrap(G)

# Plot the similarity matrix
clustermap = viz.plot_sim_matrix([communities_louvain, communities_walktrap], evaluation.adjusted_mutual_information)

# Display the cluster map (if using an environment that supports GUI, like Jupyter)
clustermap.plot()
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