PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Grossi R., Ottaviano G. Fast compressed tries through path decompositions. In: Journal of Experimental Algorithmics (JEA), vol. 19 article n. 1.8. ACM, 2014.
 
 
Abstract
(English)
Tries are popular data structures for storing a set of strings, where common prefixes are represented by common root-to-node paths. More than 50 years of usage have produced many variants and implementations to overcome some of their limitations. We explore new succinct representations of path-decomposed tries and experimentally evaluate the corresponding reduction in space usage and memory latency, comparing with the state of the art. We study the following applications: compressed string dictionary and monotone minimal perfect hash for strings. In compressed string dictionary, we obtain data structures that outperform other state-of-the-art compressed dictionaries in space efficiency while obtaining predictable query times that are competitive with data structures preferred by the practitioners. On real-world datasets, our compressed tries obtain the smallest space (except for one case) and have the fastest lookup times, whereas access times are within 20% slower than the best-known solutions. In monotone minimal perfect hash for strings, our compressed tries perform several times faster than other trie-based monotone perfect hash functions while occupying nearly the same space. On real-world datasets, our tries are approximately 2 to 5 times faster than previous solutions, with a space occupancy less than 10% larger.
URL: http://dl.acm.org/citation.cfm?doid=2627368.2656332
DOI: 10.1145/2656332
Subject Algorithms
Experimentation
Performance
Succinct data structures
String dictionaries
Monotone perfect hash functions
Tries
E.1 DATA STRUCTURES
H.3.3 Information Search and Retrieval


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