Practical Evaluation of Lempel-Ziv-78 and Lempel-Ziv-Welch Tries

Fischer, Johannes; Köppl, Dominik

doi:10.1007/978-3-319-67428-5_16

Cited by 8 publications

(7 citation statements)

References 34 publications

(29 reference statements)

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“…They concluded that HAT is a good data structure taking aspects like working space and time performance into account. 21 However, as demonstrated in our experiments, our DynPDT dictionaries can maintain the URI datasets in space up to 74% smaller than HAT, while keeping competitive insertion times.…”

Section: Comparison With Existing Data Structuresmentioning

confidence: 71%

“…It takes O(t log σ) bits of space, while supporting update and some traversal operations in O(1) expected time. Fischer and Köppl [21] presented and evaluated a number of dynamic tries for LZ78 [62] and LZW [57] factorization. They also proposed an efficient hash-based trie representation in a similar way to m-Bonsai, which is referred to as FK-hash.…”

Section: Theoretical Discussionmentioning

confidence: 99%

“…Node-Label-Map NLM dynamically manages node labels depending on the node ids assigned. As explained in Section 1, we use the m-Bonsai [47] and FK-hash [21] representations for T D . Moreover, we design the NLM data structures for m-Bonsai and FK-hash individually, which we respectively present in Sections 4 and 5.…”

Section: Representation Schemementioning

confidence: 99%

“…This section presents our DynPDT representation approaches based on FK-hash [21]. The basic idea of FK-hash is the same as that of m-Bonsai.…”

Section: Representation Based On Fk-hashmentioning

confidence: 99%

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Dynamic Path-Decomposed Tries

Kanda

Köppl

Tabei

et al. 2019

Preprint

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A keyword dictionary is an associative array whose keys are strings. Recent applications handling massive keyword dictionaries in main memory have a need for a space-efficient implementation. When limited to static applications, there are a number of highly-compressed keyword dictionaries based on the advancements of practical succinct data structures. However, as most succinct data structures are only efficient in the static case, it is still difficult to implement a keyword dictionary that is space efficient and dynamic. In this article, we propose such a keyword dictionary. Our main idea is to embrace the path decomposition technique, which was proposed for constructing cache-friendly tries. To store the path-decomposed trie in small memory, we design data structures based on recent compact hash trie representations. Exhaustive experiments on real-world datasets reveal that our dynamic keyword dictionary needs up to 68% less space than the existing smallest ones.

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Section: Comparison With Existing Data Structuresmentioning

confidence: 71%

Section: Theoretical Discussionmentioning

confidence: 99%

Section: Representation Schemementioning

confidence: 99%

“…This section presents our DynPDT representation approaches based on FK-hash [21]. The basic idea of FK-hash is the same as that of m-Bonsai.…”

Section: Representation Based On Fk-hashmentioning

confidence: 99%

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Dynamic Path-Decomposed Tries

Kanda

Köppl

Tabei

et al. 2019

Preprint

Self Cite

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“…The source code of our implementations is freely available at https://github.com/tudocomp 18. Unfortunately, the cedar trie[71] evaluated by Fischer and Köppl[29] fails to handle our datasets, which are many times larger than the 200 MiB datasets studied there. ACM Journal of Experimental Algorithmics, Vol.…”

mentioning

confidence: 99%

Engineering Practical Lempel-Ziv Tries

Arroyuelo

Cánovas

Fischer

et al. 2021

ACM J. Exp. Algorithmics

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The Lempel-Ziv 78 ( LZ78 ) and Lempel-Ziv-Welch ( LZW ) text factorizations are popular, not only for bare compression but also for building compressed data structures on top of them. Their regular factor structure makes them computable within space bounded by the compressed output size. In this article, we carry out the first thorough study of low-memory LZ78 and LZW text factorization algorithms, introducing more efficient alternatives to the classical methods, as well as new techniques that can run within less memory space than the necessary to hold the compressed file. Our results build on hash-based representations of tries that may have independent interest.

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