下面是一个简单的Python实现DeepWalk算法的示例代码

from gensim.models import Word2Vec
import networkx as nx
# 加载网络数据
G = nx.read_adjlist('karate.adjlist')
# 定义随机游走策略
from deepwalk import DeepWalk
deepwalk = DeepWalk(G, num_walks=10, walk_length=80, window=5, workers=4)
# 训练模型
model = deepwalk.fit(window=5, min_count=1)
# 获取节点嵌入向量
embedding = model.wv.vectors
# 检索与相似度最高的节点对
similarity_matrix = np.dot(embedding, np.transpose(embedding))
non_edges = list(nx.non_edges(G))
scores = []
for (i, j) in non_edges:
    scores.append((i, j, similarity_matrix[i][j]))
# 按相似度分数从高到低排序