I saw the implementation of the CF algorithm on the Internet, and knocked it myself, as follows: If you don’t understand, you can leave a message in the comment area
import java.util.*;
public class CFDemo {
private static String [] users = {
"Mike","Shrry","Lena","Jane"};
private static String [] movies = {
"Babi","The King","The Queen","The PikaQiu","Pokemon"};
private static int[][] allUserMovieScoreList = {
{
5,3,3,0,0},
{
1,4,4,2,0},
{
0,2,2,5,5},
{
4,0,0,3,4}};
private static List<List<Object>> similarUsers = null;
private static List<String> targetRecommendMovies = null;
private static Integer targetUserIndex =null;
private static List<String> commentedMovies = null;
public static void main(String[] args) {
System.out.println("请输入用户名：");
Scanner sc = new Scanner(System.in);
String user = sc.nextLine();
while(user!=null && !"exit".equals(user)){
targetUserIndex = getUserIndex(user);
if (targetUserIndex==null){
System.out.println("对不起，您输入的用户不存在！");
}else {
// 计算相似度得到最相近的两个用户
calcUserSimilarity();
// 推荐电影
calcRecommendMovie();
// 处理电影列表
handleRecommendMovies();
System.out.println("为其推荐的电影：");
for (String item : targetRecommendMovies) {
if (!commentedMovies.contains(item)) {
System.out.print("《" + item + "》" );
}
}
System.out.println();
}
user = sc.nextLine();
targetRecommendMovies = null;
}
}
public static Integer getUserIndex(String user){
if(user==null||" ".equals(user))
return null;
for (int i = 0; i < users.length; i++) {
if(user.equals(users[i])){
return i;
}
}
return null;
}
public static void calcUserSimilarity(){
similarUsers = new ArrayList<>();
List<List<Object>> userSimilarities = new ArrayList<>();
List<Object> userSimilarity =null;
for (int i = 0; i < users.length; i++) {
if(targetUserIndex == i){
continue;
}
userSimilarity = new ArrayList<>();
userSimilarity.add(i);
userSimilarity.add(caclTwoUserSimilarity(allUserMovieScoreList[i],
allUserMovieScoreList[targetUserIndex]));
userSimilarities.add(userSimilarity);
}
sortCollection(userSimilarities,1);
similarUsers.add(userSimilarities.get(0));
similarUsers.add(userSimilarities.get(1));
}
public static double caclTwoUserSimilarity(int[] user1score,int[] user2score){
float sum = 0;
for (int i = 0; i < movies.length; i++) {
sum += Math.pow(user1score[i]+user2score[i],2);
}
return Math.sqrt(sum);
}
public static void sortCollection(List<List<Object>> us,int order){
Collections.sort(us, new Comparator<List<Object>>() {
@Override
public int compare(List<Object> objects, List<Object> t1) {
double one = Double.parseDouble(objects.get(1).toString());
double two = Double.parseDouble(t1.get(1).toString());
if(one > two){
return order;
}else if(one < two){
return -order;
}else {
return 0;
}
}
});
}
public static void calcRecommendMovie(){
targetRecommendMovies = new ArrayList<>();
List<List<Object>> recommendedMovies = new ArrayList<>();
List<Object> recommendedMovie = null;
double recommendRate = 0,sumRate = 0;
for (int i = 0; i < movies.length; i++) {
recommendedMovie = new ArrayList<>();
recommendedMovie.add(i);
recommendRate = allUserMovieScoreList[Integer.parseInt(similarUsers.get(0).get(0).toString())][i]
* Double.parseDouble(similarUsers.get(0).get(1).toString())
+ allUserMovieScoreList[Integer.parseInt(similarUsers.get(1).get(0).toString())][i]
* Double.parseDouble(similarUsers.get(1).get(1).toString());
recommendedMovie.add(recommendRate);
recommendedMovies.add(recommendedMovie);
sumRate += recommendRate;
}
sortCollection(recommendedMovies,1);
for (List<Object> item : recommendedMovies) {
if (Double.parseDouble(item.get(1).toString()) > sumRate/movies.length){
targetRecommendMovies.add(movies[Integer.parseInt(item.get(0).toString())]);
}
}
}
public static void handleRecommendMovies(){
commentedMovies = new ArrayList<>();
for (int i = 0; i < allUserMovieScoreList[targetUserIndex].length; i++) {
if (allUserMovieScoreList[targetUserIndex][i] != 0){
commentedMovies.add(movies[i]);
}
}
}
}