node2vec python 实现和理解

最新推荐文章于 2025-03-06 23:45:07 发布

梦dancing

最新推荐文章于 2025-03-06 23:45:07 发布

阅读量1.5w

点赞数 16

分类专栏：自然语言处理--DL & NLP

本文链接：https://blog.youkuaiyun.com/qq_15192373/article/details/89845036

版权

1. 安装

pip install node2vec

2. 使用案例

import networkx as nx
from node2vec import Node2Vec

# Create a graph 这里可以给出自己的graph
graph = nx.fast_gnp_random_graph(n=100, p=0.5)

# Precompute probabilities and generate walks - **ON WINDOWS ONLY WORKS WITH workers=1**
node2vec = Node2Vec(graph, dimensions=64, walk_length=30, num_walks=200, workers=4)  # Use temp_folder for big graphs

# Embed nodes
model = node2vec.fit(window=10, min_count=1, batch_words=4)  # Any keywords acceptable by gensim.Word2Vec can be passed, `diemnsions` and `workers` are automatically passed (from the Node2Vec constructor)

# Look for most similar nodes
model.wv.most_similar('2')  # Output node names are always strings

# Save embeddings for later use
model.wv.save_word2vec_format(EMBEDDING_FILENAME)

# Save model for later use
model.save(EMBEDDING_MODEL_FILENAME)

#