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https://doi.org/10.1109/dcc.20...
Article . 2017 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.48550/ar...
Article . 2017
License: arXiv Non-Exclusive Distribution
Data sources: Datacite
DBLP
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Data sources: DBLP
DBLP
Article . 2017
Data sources: DBLP
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Making Compression Algorithms for Unicode Text

Authors: Adam Gleave; Christian Steinruecken;

Making Compression Algorithms for Unicode Text

Abstract

The majority of online content is written in languages other than English, and is most commonly encoded in UTF-8, the world's dominant Unicode character encoding. Traditional compression algorithms typically operate on individual bytes. While this approach works well for the single-byte ASCII encoding, it works poorly for UTF-8, where characters often span multiple bytes. Previous research has focused on developing Unicode compressors from scratch, which often failed to outperform established algorithms such as bzip2. We develop a technique to modify byte-based compressors to operate directly on Unicode characters, and implement variants of LZW and PPM that apply this technique. We find that our method substantially improves compression effectiveness on a UTF-8 corpus, with our PPM variant outperforming the state-of-the-art PPMII compressor. On ASCII and binary files, our variants perform similarly to the original unmodified compressors.

10 pages

Keywords

FOS: Computer and information sciences, Computer Science - Information Theory, Information Theory (cs.IT)

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    popularity
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    Average
    influence
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Top 10%
Green