Self-adjusting binary search trees
Journal of the ACM (JACM)
Applications of the theory of records in the study of random trees
Acta Informatica
Source models for natural language text
International Journal of Man-Machine Studies
An efficient implementation of trie structures
Software—Practice & Experience
Improved behaviour of tries by adaptive branching
Information Processing Letters
Self-adjusting k-ary search trees
Journal of Algorithms
Journal of Algorithms
SODA '93 Proceedings of the fourth annual ACM-SIAM Symposium on Discrete algorithms
Fast algorithms for sorting and searching strings
SODA '97 Proceedings of the eighth annual ACM-SIAM symposium on Discrete algorithms
The analysis of hybrid trie structures
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
PATRICIA—Practical Algorithm To Retrieve Information Coded in Alphanumeric
Journal of the ACM (JACM)
Self-Organizing Binary Search Trees
Journal of the ACM (JACM)
Communications of the ACM
Burst tries: a fast, efficient data structure for string keys
ACM Transactions on Information Systems (TOIS)
Average Case Analysis of Algorithms on Sequences
Average Case Analysis of Algorithms on Sequences
Adaptive Structuring of Binary Search Trees Using Conditional Rotations
IEEE Transactions on Knowledge and Data Engineering
Self-Organizing Data Structures
Developments from a June 1996 seminar on Online algorithms: the state of the art
Engineering scalable, cache and space efficient tries for strings
The VLDB Journal — The International Journal on Very Large Data Bases
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A Ternary Search Trie (TST) is a highly efficient dynamic dictionary structure applicable for strings and textual data. The strings are accessed based on a set of access probabilities and are to be arranged using a TST. We consider the scenario where the probabilities are not known a priori, and is time-invariant. Our aim is to adaptively restructure the TST so as to yield the best access or retrieval time. Unlike the case of lists and binary search trees, where numerous methods have been proposed, in the case of the TST, currently, the number of reported adaptive schemes are few. In this paper, we consider various self-organizing schemes that were applied to Binary Search Trees, and apply them to TSTs. Three new schemes, which are the splaying, the conditional rotation and the randomization heuristics, have been proposed, tested and comparatively presented. The results demonstrate that the conditional rotation heuristic is the best when compared to other heuristics that are considered in the paper. As far as we know, this paper reports the first search-based adaptive strategies for TSTs.