On demand string sorting over unbounded alphabets

Carmel Kent, Moshe Lewenstein, Dafna Sheinwald

Research output: Contribution to journalArticlepeer-review

Abstract

On-demand string sorting is the problem of preprocessing a set of strings to allow subsequent queries for finding the k lexicographically smallest strings (and afterward the next k etc.) This on-demand variant strongly resembles the search engine queries which give you the best k-ranked pages recurringly. We present a data structure that supports this in O(n) preprocessing time, where n is the number of strings, and answer queries in O(logn) time. There is also a cost of O(N) time amortized over all operations, where N is the total length of the strings. Our data structure is a heap of strings, which supports heapify and delete-mins. As it turns out, implementing a full heap with all operations is not that simple. For the sake of completeness, we propose a heap with full operations based on balanced indexing trees that supports the heap operations in optimal times.

Original languageAmerican English
Pages (from-to)66-74
Number of pages9
JournalTheoretical Computer Science
Volume426-427
DOIs
StatePublished - 6 Apr 2012

Keywords

  • Data structures
  • String matching

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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