import org.apache.mahout.cf.taste.impl.model.file.FileDataModel; import org.apache.mahout.cf.taste.impl.recommender.svd.ALSWRFactorizer; import org.apache.mahout.cf.taste.impl.recommender.svd.SVDRecommender; import org.apache.mahout.cf.taste.model.DataModel; import org.apache.mahout.cf.taste.recommender.RecommendedItem; import org.apache.mahout.cf.taste.recommender.Recommender;

import java.io.File; import java.util.List; import java.util.Scanner;

public class AIProductRecommender {

public static void main(String[] args) { Scanner scanner = new Scanner(System.in);

try {
// LOAD USER-ITEM RATING DATA FROM CSV FILE
File dataFile = new File("data.csv");
DataModel model = new FileDataModel(dataFile);

// CREATE RECOMMENDER USING MATRIX FACTORIZATION  
ALSWRFactorizer factorizer = new ALSWRFactorizer(model, 15, 0.05, 20);  
Recommender recommender = new SVDRecommender(model, factorizer);  

// ASK FOR USER ID FROM CONSOLE  
System.out.print("PLEASE ENTER YOUR USER ID: ");  
long userId = scanner.nextLong();  

// NUMBER OF RECOMMENDATIONS TO GENERATE  
int numberOfRecommendations = 5;  

// FETCH AND DISPLAY RECOMMENDATIONS  
List<RecommendedItem> recommendations = recommender.recommend(userId, numberOfRecommendations);  

if (recommendations.isEmpty()) {  
    System.out.println("SORRY! NO RECOMMENDATIONS FOUND FOR USER ID: " + userId);  
} else {  
    System.out.println("\nPERSONALIZED PRODUCT RECOMMENDATIONS:");  
    for (RecommendedItem item : recommendations) {  
        System.out.printf("PRODUCT ID: %-5s | SCORE: %.2f\n", item.getItemID(), item.getValue());  
    }  
}  

} catch (Exception e) {
System.out.println("AN ERROR OCCURRED WHILE PROCESSING RECOMMENDATIONS:");
e.printStackTrace();
} finally {
scanner.close();
}

}

}