Silesia corpus

The Silesia corpus is a collection of files intended for use as a benchmark for testing lossless data compression algorithms. It was created in 2003 as an alternative for the Canterbury corpus and Calgary corpus, based on concerns about how well these represented modern files. It contains various data types, including large text documents, executable files, and databases. [1]

Contents

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The corpus consists of 12 files, totaling 211MB. The files were chosen to represent what the author considered to be data types likely to grow rapidly in size over time, such as computer programs and databases, along with more traditional compression benchmarks, such as large text files. [1]

Overview of files, their sizes, descriptions, and data types
File Size (B) Description Type of data
dickens 10192446 The works of Charles Dickens English text
mozilla 51220480 Executable files for Mozilla 1.0 Executable
mr 9970564 MRI Images 3D image
nci 33553445 A database of chemical structures Database
office 6152192 A shared library from OpenOffice Executable
osdb 10085684 A Sample MySQL database from the Open Source Database Benchmark Database
reymont 6625583 The text of the book Chłopi by Władysław Reymont PDF in Polish
samba 21606400 The source code of Samba 2‑2.3 Executable
sao 7251944 The SAO star catalogue Binary database
webster 41458703 The 1913 Webster Unabridged Dictionary HTML
xml 5345280 Collected XML files XML
x-ray 8474240 A medical X-Ray Image
Total 211938580

Because it has a broader and more modern selection of datatypes, it is considered a better source of test data for compression algorithms when compared to the Calgary corpus.[2]

See also

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References

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  1. ^ a b Deorowicz, Sebastian. Universal Lossless Data Compression Algorithms (PDF) (Thesis). Silesian University of Technology. pp. 93–95. Archived from the original (PDF) on 2024-08-28.
  2. ^ Gupta, Apoorv; Bansal, Aman; Khanduja, Vidhi (2017-02-22). "Modern lossless compression techniques: Review, comparison and analysis". Second International Conference on Electrical, Computer and Communication Technologies (ICECCT). IEEE: 1–8. doi:10.1109/ICECCT.2017.8117850. ISBN 978-1-5090-3239-6.
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