C#에서 추천 시스템 알고리즘을 구현하는 방법

// 数据加载
List<Rating> ratings = LoadRatingsFromCSV("ratings.csv");
// 构建用户-物品评分矩阵
Dictionary<int, Dictionary<int, double>> userItemRatings = new Dictionary<int, Dictionary<int, double>>();
foreach (Rating rating in ratings)
{
    int userId = rating.UserId;
    int itemId = rating.ItemId;
    double score = rating.Score;
    if (!userItemRatings.ContainsKey(userId))
    {
        userItemRatings[userId] = new Dictionary<int, double>();
    }
    userItemRatings[userId][itemId] = score;
}

// 计算用户之间的相似度
Dictionary<int, Dictionary<int, double>> userSimilarities = new Dictionary<int, Dictionary<int, double>>();
foreach (int userId in userItemRatings.Keys)
{
    userSimilarities[userId] = new Dictionary<int, double>();
    foreach (int otherUserId in userItemRatings.Keys)
    {
        if (userId == otherUserId) continue;
        double similarity = CalculateSimilarity(userItemRatings[userId], userItemRatings[otherUserId]);
        userSimilarities[userId][otherUserId] = similarity;
    }
}

// 为目标用户生成推荐物品
int targetUserId = 1;
List<int> recommendedItems = new List<int>();
foreach (int itemId in userItemRatings[targetUserId].Keys)
{
    double totalSimilarity = 0.0;
    double totalScore = 0.0;
    foreach (int otherUserId in userSimilarities[targetUserId].Keys)
    {
        double similarity = userSimilarities[targetUserId][otherUserId];
        double score = userItemRatings[otherUserId][itemId];
        totalSimilarity += similarity;
        totalScore += similarity * score;
    }
    double predictedRating = totalScore / totalSimilarity;
    if (predictedRating > threshold) // 设置一个阈值，只推荐评分高的物品
    {
        recommendedItems.Add(itemId);
    }
}