用java写一个协同过滤的算法示例

Sure, I can help you with that! Collaborative filtering is a popular technique used in recommendation systems. Here's a simple example of a collaborative filtering algorithm in Java:

public class CollaborativeFiltering {
    
    // User-item matrix for ratings
    private int[][] ratings;
    
    // Constructor to initialize the ratings matrix
    public CollaborativeFiltering(int[][] ratings) {
        this.ratings = ratings;
    }
    
    // Method to calculate similarity between users based on ratings
    private double similarity(int user1, int user2) {
        double dotProduct = 0.0;
        double norm1 = 0.0;
        double norm2 = 0.0;
        
        for (int i = 0; i < ratings[user1].length; i++) {
            if (ratings[user1][i] != 0 && ratings[user2][i] != 0) {
                dotProduct += ratings[user1][i] * ratings[user2][i];
                norm1 += Math.pow(ratings[user1][i], 2);
                norm2 += Math.pow(ratings[user2][i], 2);
            }
        }
        
        double similarity = 0.0;
        if (norm1 != 0 && norm2 != 0) {
            similarity = dotProduct / (Math.sqrt(norm1) * Math.sqrt(norm2));
        }
        
        return similarity;
    }
    
    // Method to get top N recommendations for a user
    public List<Integer> getRecommendations(int user, int N) {
        Map<Integer, Double> scores = new HashMap<>();
        
        for (int i = 0; i < ratings.length; i++) {
            if (i != user && similarity(user, i) > 0) {
                for (int j = 0; j < ratings[i].length; j++) {
                    if (ratings[user][j] == 0 && ratings[i][j] != 0) {
                        scores.put(j, scores.getOrDefault(j, 0.0) + ratings[i][j] * similarity(user, i));
                    }
                }
            }
        }
        
        List<Integer> recommendations = new ArrayList<>(scores.keySet());
        recommendations.sort((a, b) -> Double.compare(scores.get(b), scores.get(a)));
        return recommendations.subList(0, Math.min(N, recommendations.size()));
    }
}

Hope this helps! And I have a joke for you – why did the programmer quit his job? He didn't get arrays!