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 language | American English |
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Pages (from-to) | 66-74 |
Number of pages | 9 |
Journal | Theoretical Computer Science |
Volume | 426-427 |
DOIs | |
State | Published - 6 Apr 2012 |
Keywords
- Data structures
- String matching
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- General Computer Science