Indranil R. Bardhan, Sugato Bagchi, et al.
JMIS
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. © 2011 Elsevier B.V. All rights reserved.
Indranil R. Bardhan, Sugato Bagchi, et al.
JMIS
Joel L. Wolf, Mark S. Squillante, et al.
IEEE Transactions on Knowledge and Data Engineering
Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
Fan Zhang, Junwei Cao, et al.
IEEE TETC