TL;DR
This paper demonstrates how balanced wavelet trees can efficiently support range quantile queries, enabling applications like space-efficient coloured range reporting and document listing.
Contribution
It introduces a novel use of wavelet trees for range quantile queries and their application to related problems, enhancing efficiency and space usage.
Findings
Supports efficient range quantile queries
Enables space-efficient coloured range reporting
Facilitates document listing applications
Abstract
We show how to use a balanced wavelet tree as a data structure that stores a list of numbers and supports efficient {\em range quantile queries}. A range quantile query takes a rank and the endpoints of a sublist and returns the number with that rank in that sublist. For example, if the rank is half the sublist's length, then the query returns the sublist's median. We also show how these queries can be used to support space-efficient {\em coloured range reporting} and {\em document listing}.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
