Efficient and Compact Representations of Some Non-canonical Prefix-Free Codes

Fariña, Antonio; Gagie, Travis; Manzini, Giovanni; Navarro, Gonzalo; Ordóñez, Alberto

doi:10.1007/978-3-319-46049-9_5

Cited by 5 publications

(3 citation statements)

References 14 publications

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“…In theory terms, important results were given by Gagie et al [13] and Fariña et al [10] (see also an extended version [11]). The former is heavily cited in this work, and is discussed in detail in Section 2.2.…”

Section: Introductionmentioning

confidence: 93%

Space-Efficient Huffman Codes Revisited

Grabowski¹,

Köppl²

2021

Preprint

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Canonical Huffman code is an optimal prefix-free compression code whose codewords enumerated in the lexicographical order form a list of binary words in non-decreasing lengths. Gagie et al. ( 2015) gave a representation of this coding capable to encode or decode a symbol in constant worst case time. It uses σ lg ℓmax + o(σ) + O(ℓ 2 max ) bits of space, where σ and ℓmax are the alphabet size and maximum codeword length, respectively. We refine their representation to reduce the space complexity to σ lg ℓmax(1 + o(1)) bits while preserving the constant encode and decode times. Our algorithmic idea can be applied to any canonical code.

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Section: Introductionmentioning

confidence: 93%

Space-Efficient Huffman Codes Revisited

Grabowski¹,

Köppl²

2021

Preprint

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“…Yet, compressing the WM by giving either a Huffman or Hu-Tucker shape is not possible as the reordering of the WM could lead to the existence of holes in the structure that would ruin the process of tracking symbols during traversals. To overcome this issue an optimal Huffman-based coding was specifically developed for wavelet matrices [38,59]. This allows to obtain space similar to that of a pointerless Huffman-shaped WT but faster rank, select, and access operations.…”

Section: The Wavelet Tree (Wt)mentioning

confidence: 99%

A compact representation for trips over networks built on self-indexes

Brisaboa

Fariña

Galaktionov

et al. 2018

Information Systems

Self Cite

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Representing the movements of objects (trips) over a network in a compact way while retaining the capability of exploiting such data effectively is an important challenge of real applications. We present a new Compact Trip Representation (CTR) that handles the spatio-temporal data associated with users' trips over transportation networks. Depending on the network and types of queries, nodes in the network can represent intersections, stops, or even street segments.CTR represents separately sequences of nodes and the time instants when users traverse these nodes. The spatial component is handled with a data structure based on the well-known Compressed Suffix Array (CSA), which provides both a compact representation and interesting indexing capabilities. The temporal component is self-indexed with either a Hu-Tucker-shaped Wavelet-tree or a Wavelet Matrix that solve range-interval queries efficiently. We show how CTR can solve relevant counting-based spatial, temporal, and spatio-temporal queries over large sets of trips. Experimental results show the space requirements (around 50-70% of the space needed by a compact non-indexed baseline) and query efficiency (most queries are solved in the range of 1-1000 microseconds) of CTR.

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“…• New universal indexes for highly repetitive document collections [9] • Efficient and compact representations of some non-canonical prefix-free codes [11] • New compressed representations of sequences with rank/select support [16,18] • Efficient representation of trajectories [6,7] and event sequences [4].…”

Section: Compression and Indexing Techniques For Repetitive Datamentioning

confidence: 99%

About BIRDS project (Bioinformatics and Information Retrieval Data Structures Analysis and Design)

Bernardo

Ladra

2018

Proceedings of the 5th Spanish Conference on Information Retrieval

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BIRDS stands for "Bioinformatics and Information Retrieval Data Structures analysis and design" and is a 4-year project (2016-2019) that has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 690941.The overall goal of BIRDS is to establish a long term international network involving leading researchers in the development of efficient data structures in the fields of Bioinformatics and Information Retrieval, to strengthen the partnership through the exchange of knowledge and expertise, and to develop integrated approaches to improve current approaches in both fields. The research will address challenges in storing, processing, indexing, searching and navigating genome-scale data by designing new algorithms and data structures for sequence analysis, networks representation or compressing and indexing repetitive data.BIRDS project is carried out by 7 research institutions from Australia (

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Efficient and Compact Representations of Some Non-canonical Prefix-Free Codes

Cited by 5 publications

References 14 publications

Space-Efficient Huffman Codes Revisited

Space-Efficient Huffman Codes Revisited

A compact representation for trips over networks built on self-indexes

About BIRDS project (Bioinformatics and Information Retrieval Data Structures Analysis and Design)

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