django根据个人书架的书用协同过滤算法向用户推荐可能喜欢的书的相关代码
时间: 2023-05-30 14:06:41 浏览: 54
以下是一个简单的django视图函数,使用协同过滤算法向用户推荐可能喜欢的书:
```python
from django.shortcuts import render
from django.contrib.auth.decorators import login_required
from django.db.models import Count
from .models import Book, UserBookRating
@login_required
def recommend_books(request):
# 获取当前用户的书架中的书籍
user_books = request.user.book_set.all()
# 获取其他用户对这些书籍的评分
ratings = UserBookRating.objects.filter(book__in=user_books).exclude(user=request.user)
# 计算每本书的平均评分
book_ratings = {}
for rating in ratings:
book_id = rating.book.id
if book_id not in book_ratings:
book_ratings[book_id] = {'rating_sum': 0, 'num_ratings': 0}
book_ratings[book_id]['rating_sum'] += rating.rating
book_ratings[book_id]['num_ratings'] += 1
book_avg_ratings = {}
for book_id, rating_data in book_ratings.items():
book_avg_ratings[book_id] = rating_data['rating_sum'] / rating_data['num_ratings']
# 根据平均评分排序书籍
sorted_books = sorted(book_avg_ratings.items(), key=lambda x: x[1], reverse=True)
# 获取前10本书
recommended_books = []
for book_id, rating in sorted_books[:10]:
book = Book.objects.get(id=book_id)
recommended_books.append(book)
context = {'recommended_books': recommended_books}
return render(request, 'recommend_books.html', context)
```
在这个视图函数中,我们首先获取当前用户的书架中的书籍。然后,我们获取其他用户对这些书籍的评分,并计算每本书的平均评分。接着,我们根据平均评分排序书籍,并获取前10本书。最后,我们将推荐的书籍传递给模板进行展示。
需要注意的是,这个算法是一个简单的基于用户的协同过滤算法,没有考虑到更复杂的因素,比如书籍的类型、作者、出版社等等。因此,这只是一个示例代码,你需要根据实际情况进行调整和优化。