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LeetCode 1917: Leetcodify Friends Recommendations Solution

Master LeetCode problem 1917 (Leetcodify Friends Recommendations), a hard challenge, with our optimized solutions in Java, C++, and Python. Explore detailed explanations, test your code in our interactive editor, and prepare for coding interviews.

1917. Leetcodify Friends Recommendations

Hard
Database

Problem Explanation

Explanation:

To solve this problem, we can use a graph-based approach. We will start by constructing a graph where each user is represented by a node, and there is an edge between two users if they are friends. Then, we can iterate through each user and for each user, we can find the friends of their friends (excluding the direct friends) and recommend them as potential friends.

We will keep track of the count of mutual friends between the user and the potential friend. We can use a hashmap to store the count of mutual friends for each potential friend. Finally, we can recommend the top k potential friends based on the count of mutual friends.

Algorithm:

  1. Construct a graph where each user is a node and there is an edge between two users if they are friends.
  2. Iterate through each user:
    • For each friend of the user, find their friends (excluding the direct friends).
    • Increment the count of mutual friends between the user and potential friends.
  3. Store the count of mutual friends for each potential friend in a hashmap.
  4. Recommend the top k potential friends based on the count of mutual friends.

Time Complexity:

  • Building the graph: O(n * m) where n is the number of users and m is the average number of friends per user.
  • Finding potential friends and counting mutual friends: O(n * m^2) where n is the number of users and m is the average number of friends per user.
  • Recommending top k friends: O(n * log(n)) where n is the number of users.

Space Complexity:

  • Graph representation: O(n + e) where n is the number of users and e is the number of edges (friend connections).
  • Hashmap for storing mutual friends count: O(n)

: :

Solution Code

// Java solution
class Solution {
    public List<Integer> recommendFriends(int[][] friends, int user, int k) {
        // Implement the algorithm here
    }
}

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