锦中融合门户系统

import pandas as pd

from sklearn.neighbors import NearestNeighbors

# 模拟用户-物品评分数据

data = {'user': [1, 1, 2, 2, 3], 'item': [101, 102, 101, 103, 102], 'rating': [5, 3, 4, 2, 4]}

df = pd.DataFrame(data)

# 构建用户-物品矩阵

pivot_table = df.pivot(index='user', columns='item', values='rating').fillna(0)

# 使用KNN算法进行协同过滤

model = NearestNeighbors(n_neighbors=2, metric='cosine')

model.fit(pivot_table)

distances, indices = model.kneighbors(pivot_table.values)

# 输出最近邻用户

print(indices)