[leetcode-599-Minimum Index Sum of Two Lists]

本文介绍了一个帮助两个人基于各自的餐厅喜好列表找到共同喜欢的餐厅的算法。该算法通过使用映射记录每个餐厅出现的次数及其在列表中的位置来实现,最终找出双方共同喜爱且列表索引总和最小的餐厅。

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Suppose Andy and Doris want to choose a restaurant for dinner, and they both have a list of favorite restaurants
represented by strings.
You need to help them find out their common interest with the least list index sum.
If there is a choice tie between answers, output all of them with no order requirement.
You could assume there always exists an answer.
Example 1:
Input:
["Shogun", "Tapioca Express", "Burger King", "KFC"]
["Piatti", "The Grill at Torrey Pines", "Hungry Hunter Steakhouse", "Shogun"]
Output: ["Shogun"]
Explanation: The only restaurant they both like is "Shogun".
Example 2:
Input:
["Shogun", "Tapioca Express", "Burger King", "KFC"]
["KFC", "Shogun", "Burger King"]
Output: ["Shogun"]
Explanation: The restaurant they both like and have the least index sum is "Shogun" with index sum 1 (0+1).
Note:
The length of both lists will be in the range of [1, 1000].
The length of strings in both lists will be in the range of [1, 30].
The index is starting from 0 to the list length minus 1.
No duplicates in both lists.

思路:

主要是用map记录字符串出现次数,以及记录字符串对应的下标。

感觉写的太啰嗦,待优化。

vector<string> findRestaurant(vector<string>& list1, vector<string>& list2)
{
  vector<string>res;
  map<string,int>restaurant;//记录是否 饭店出现次数。如果>1 
  map<string,int>index1;//记录饭店1索引
  map<string,int>index2;//记录饭店2索引
  map<string,int>::iterator it;
  for(int i=0;i<list1.size();i++)
  {
    index1[list1[i]] = i;
    restaurant[list1[i]]++;
  }
  for(int i=0;i<list2.size();i++)
  {
    index2[list2[i]] = i;
    restaurant[list2[i]]++;
  }
  int indexsum = 2000;  
  for(it =restaurant.begin();it!=restaurant.end();it++)
  {     
     if(it->second ==2) 
     {          
       if(index1[it->first] + index2[it->first] <indexsum)
       {
     indexsum =index1 [it->first] + index2[it->first];
     res.clear();
     res.push_back(it->first);
      }
      else if(index1[it->first] + index2[it->first] == indexsum)
      {
     indexsum =index1 [it->first] + index2[it->first];     
     res.push_back(it->first);
      }       
    }     
  }    
  return res;
}

 

转载于:https://www.cnblogs.com/hellowooorld/p/6915305.html

Leetcode 高频考题整理确实是很有帮助的,以下是一些常见的 Leetcode 高频考题整理: 1. 数组和字符串问题: - 两数之和 (Two Sum) - 三数之和 (Three Sum) - 最长回文子串 (Longest Palindromic Substring) - 盛最多水的容器 (Container With Most Water) - 下一个排列 (Next Permutation) 2. 链表问题: - 反转链表 (Reverse Linked List) - 删除链表中的倒数第N个节点 (Remove Nth Node From End of List) - 合并两个有序链表 (Merge Two Sorted Lists) - 链表中环的检测 (Linked List Cycle) - 环形链表的起始点 (Linked List Cycle II) 3. 树和图问题: - 二叉树的遍历 (Binary Tree Traversal) - 二叉树的最大深度 (Maximum Depth of Binary Tree) - 二叉树的最小深度 (Minimum Depth of Binary Tree) - 图的深度优先搜索 (Depth First Search) - 图的广度优先搜索 (Breadth First Search) 4. 动态规划问题: - 爬楼梯 (Climbing Stairs) - 最大子序和 (Maximum Subarray) - 打家劫舍 (House Robber) - 不同路径 (Unique Paths) - 最长递增子序列 (Longest Increasing Subsequence) 5. 排序和搜索问题: - 快速排序 (Quick Sort) - 归并排序 (Merge Sort) - 二分查找 (Binary Search) - 搜索旋转排序数组 (Search in Rotated Sorted Array) - 寻找峰值 (Find Peak Element) 这只是一些常见的 Leetcode 高频考题整理,还有很多其他题目也值得关注。通过刷题和整理高频题目,可以提高对算法和数据结构的理解和应用能力。希望对你有所帮助!
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