Given a list of items and their values. The task is to find top k items with the highest value. It is possible that two items have the same value, in that case item whose name comes first (lexicographically) will be given higher priority.

**Examples:**

Input:items[] = {Bat, Gloves, Wickets, Ball}, values[] = {100, 50, 200, 100}

k = 2

Output:Wickets Ball

Wickets has the highest value.

Bat, Ball has the same value but Ball comes first lexicographically.

**Approach:** This question can be solved by picking the items greedily according to the values. We will sort use the items list in the decreasing order of the values and in case of the same values items will be sorted lexicographical order increasing order.

We will store the data in the form of pairs in a vector and will use an inbuilt sort function with boolean comparator function which will be used to compare two items.

Below is the implementation of the above approach:

`// C++ implementation of above approach ` `#include <bits/stdc++.h> ` `using` `namespace` `std; ` ` ` `// Boolean Comparator Function ` `// to compare two pairs of item-value ` `bool` `comp(pair<string, ` `int` `> A, pair<string, ` `int` `> B) ` `{ ` ` ` `// Compare the name if the values are equal ` ` ` `if` `(A.second == B.second) ` ` ` `return` `A.first < B.first; ` ` ` ` ` `// Else compare values ` ` ` `return` `A.second > B.second; ` `} ` ` ` `// Driver code ` `int` `main() ` `{ ` ` ` `int` `k = 2; ` ` ` `int` `n = 3; ` ` ` ` ` `// Store data in a vector of Item-Value Pair ` ` ` `vector<pair<string, ` `int` `> > items; ` ` ` ` ` `// inserting items-value pairs in the vector ` ` ` `items.push_back(make_pair(` `"Bat"` `, 100)); ` ` ` `items.push_back(make_pair(` `"Gloves"` `, 50)); ` ` ` `items.push_back(make_pair(` `"Wickets"` `, 200)); ` ` ` `items.push_back(make_pair(` `"Ball"` `, 100)); ` ` ` ` ` `// Sort items using Inbuilt function ` ` ` `sort(items.begin(), items.end(), comp); ` ` ` ` ` `// Print top k values ` ` ` `// or if n is less than k ` ` ` `// Print all n items ` ` ` `for` `(` `int` `i = 0; i < min(n, k); ++i) { ` ` ` `cout << items[i].first << ` `'\n'` `; ` ` ` `} ` ` ` ` ` `return` `0; ` `} ` |

**Output:**

Wickets Ball

**Time Complexity:** O(NlogN)

Further Optimization : We can further optimize above solutions using Heap Data Structure. Please see k largest elements in an array.