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→Data structure-based solutions: Some rewording/grammar. |
→Data structure-based solutions: More grammar. |
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Another simple method is to add each element of the list into a [[priority queue]] data structure, such as a [[heap (data structure)|heap]] or [[self-balancing binary search tree]], with at most ''k'' elements. Whenever the data structure has more than ''k'' elements, we remove the largest element, which can be done in O(log ''k'') time. Each insertion operation also takes O(log ''k'') time, resulting in O(''n'' log ''k'') time overall.
It is possible to transform the list into a [[binary heap]] in Θ(''n'') time, and then traverse the heap using a modified [[breadth-first search]] algorithm that places the elements in a [[priority queue]]{{clarify|reason=a heap is a priority queue!|date=January 2014}} (instead of the ordinary queue that is normally used in a BFS), starting with the root node
== Specialised sorting algorithms ==
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