Compression of Small Text Files using Syllables

Lánský, Jan; Žemlička, Michal

doi:10.1109/dcc.2006.16

Cited by 16 publications

(17 citation statements)

References 2 publications

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“…This leads to reduction of used space. In [21, 22], Lansky and his colleagues were the first to propose a method for syllable-based text compression techniques. In their papers, they focused on specification of syllables, methods for decomposition of words into syllables, and using syllable-based compression in combination of the principles of LZW and Huffman coding.…”

Section: Related Workmentioning

confidence: 99%

n-Gram-Based Text Compression

Nguyen

Duong

et al. 2016

Computational Intelligence and Neuroscience

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We propose an efficient method for compressing Vietnamese text using n-gram dictionaries. It has a significant compression ratio in comparison with those of state-of-the-art methods on the same dataset. Given a text, first, the proposed method splits it into n-grams and then encodes them based on n-gram dictionaries. In the encoding phase, we use a sliding window with a size that ranges from bigram to five grams to obtain the best encoding stream. Each n-gram is encoded by two to four bytes accordingly based on its corresponding n-gram dictionary. We collected 2.5 GB text corpus from some Vietnamese news agencies to build n-gram dictionaries from unigram to five grams and achieve dictionaries with a size of 12 GB in total. In order to evaluate our method, we collected a testing set of 10 different text files with different sizes. The experimental results indicate that our method achieves compression ratio around 90% and outperforms state-of-the-art methods.

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Section: Related Workmentioning

confidence: 99%

n-Gram-Based Text Compression

Nguyen

Duong

et al. 2016

Computational Intelligence and Neuroscience

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“…The closest one to the topic of this work is the one on the level of words [4], symbols or sentential units. Another interesting method is the compression based on syllables [6,7].…”

Section: Previous Workmentioning

confidence: 99%

Techniques of Czech Language Lossless Text Compression

Ševčı́k

Dvorský

2016

Computer Information Systems and Industrial Management

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Part 4: Optimization, TuningInternational audienceFor lossless data compression of the texts of natural language and for achieving better compression ratio we can use linguistic and grammatical properties extracted from the text analysis. This work deals with usage of word order, word categories and grammatical rules in sentences and sentence units in Czech language. Special grammatical properties of this language which are different from for example English language are used here. Further, there is an algorithm designed for searching similarities in analyzed sentence structures and its next processing to final compressed file. For analysis of the sentence units a special tool is used which allows parsing on more levels

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“…The recent paper in [11] uses syllables for compression of short text files larger than 3 kBytes. A related work in the field of very short text files is the study in [12], where a tree machine is employed as a static context model.…”

Section: A Related Workmentioning

confidence: 99%

Compression of Short Text on Embedded Systems

Rein¹,

Gühmann²,

Fitzek³

2006

JCP

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Abstract-The paper details a scheme for lossless compression of short data series larger than 50 Bytes. The method uses arithmetic coding and context modeling with a low-complexity data model. A data model that takes 32 kBytes of RAM already cuts the data size in half. The compression scheme just takes a few pages of source code, is scalable in memory size, and may be useful in sensor or cellular networks to spare bandwidth. As we demonstrate the method allows for battery savings when applied to mobile phones.

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Compression of Small Text Files using Syllables

Cited by 16 publications

References 2 publications

n-Gram-Based Text Compression

n-Gram-Based Text Compression

Techniques of Czech Language Lossless Text Compression

Compression of Short Text on Embedded Systems

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