Find the k th largest element with the partition algorithm, then all the elements after it will be larger than it, and those are your top k .
Feb 10, 2011
In this paper we investigate the top-k-selection problem, i.e. to determine and sort the top k elements, in the dynamic data model.
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How to solve top k problems?
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Which data structure will be best to easily get the k greatest elements of an array where k is less than n and n is the length of the array?
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In this paper we investigate the top-k-selection problem, i.e. to determine and sort the top k elements, in the dynamic data model.
Sep 15, 2012 · Your job is to maintain a current list of maximum top k records as elements are read off the stream, processed, and discarded. How can you do this in O(n) time?
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Once the heap size is k + 1, we use the min heap to identify the element with the least frequency and remove that element (this element is necessarily not a ...
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Use a HashMap to track frequency of every element, let's call it mp · Use a set to track the top-most k elements, let's call it pq.
Sep 30, 2024 · Use a heap (min-heap) to keep track of the top K elements by frequency. Extract the elements from the heap to get the top K frequent elements.
Missing: Select Evolving
Jul 2, 2012 · Another approach is using binary search trees. If you use a self-balancing variant, that makes updates possible in O(logn) time. The queries you ...
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1 day ago · Find k largest elements in an array · Using Sorting – O(n Log n) · Using Quick Select algorithm – O(n^2) in Worst · [Approach – 3] Using Priority ...
Oct 19, 2016 · One efficient approach is to use QuickSelect to find the value of the k-th largest element, then follow with a linear scan that outputs all elements that are ...
Missing: Select Evolving