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• W2000568570 abstract "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." @default.
• W2000568570 created "2016-06-24" @default.
• W2000568570 creator A5003288532 @default.
• W2000568570 creator A5006984021 @default.
• W2000568570 date "2015-01-07" @default.
• W2000568570 modified "2023-10-01" @default.
• W2000568570 title "Fast Compressed Tries through Path Decompositions" @default.
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• W2000568570 doi "https://doi.org/10.1145/2656332" @default.
• W2000568570 hasPublicationYear "2015" @default.
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