I\'m trying to come up with something to solve the following:
Given a max-heap represented as an array, return the kth largest element without modifyi
The max-heap can have many ways, a better case is a complete sorted array, and in other extremely case, the heap can have a total asymmetric structure.
Here can see this:
In the first case, the kth lagest element is in the kth position, you can compute in O(1) with a array representation of heap. But, in generally, you'll need to check between (k, 2k) elements, and sort them (or partial sort with another heap). As far as I know, it's O(K·log(k))
And the algorithm:
Input:
Integer kth <- 8
Heap heap <- {19,18,10,17,14,9,4,16,15,13,12}
BEGIN
Heap positionHeap <- Heap with comparation: ((n0,n1)->compare(heap[n1], heap[n0]))
Integer childPosition
Integer candidatePosition <- 0
Integer count <- 0
positionHeap.push(candidate)
WHILE (count < kth) DO
candidatePosition <- positionHeap.pop();
childPosition <- candidatePosition * 2 + 1
IF (childPosition < size(heap)) THEN
positionHeap.push(childPosition)
childPosition <- childPosition + 1
IF (childPosition < size(heap)) THEN
positionHeap.push(childPosition)
END-IF
END-IF
count <- count + 1
END-WHILE
print heap[candidate]
END-BEGIN
EDITED
I found "Optimal Algorithm of Selection in a min-heap" by Frederickson here: ftp://paranoidbits.com/ebooks/An%20Optimal%20Algorithm%20for%20Selection%20in%20a%20Min-Heap.pdf