知识图谱双十一促销活动

import networkx as nx

# 创建一个知识图谱
G = nx.Graph()

# 添加实体和关系
G.add_node('user1', type='user')
G.add_node('product1', type='product', price=100, category='electronics')
G.add_node('product2', type='product', price=200, category='electronics')

G.add_edge('user1', 'product1', action='bought')
G.add_edge('user1', 'product2', action='viewed')

# 推荐逻辑
def recommend_products(user_id):
    user_products = G[user_id]
    recommended_products = []
    
    for product_id, edge_data in user_products.items():
        if edge_data['action'] == 'viewed':
            similar_products = [n for n, d in G[product_id].items() if d['type'] == 'product' and n != product_id]
            recommended_products.extend(similar_products)
    
    return recommended_products

# 获取推荐商品
recommended_products = recommend_products('user1')
print("Recommended Products:", recommended_products)