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Title:Analiza algoritmov stiskanja na primeru tekstovnih datotek v različnih jezikih
Authors:ID Arzenšek, Klemen (Author)
ID Sepesy Maučec, Mirjam (Mentor) More about this mentor... New window
ID Donaj, Gregor (Comentor)
Files:.pdf MAG_Arzensek_Klemen_2024.pdf (2,04 MB)
MD5: FE5375CA7EE7473F68313AEFB8F390D4
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Magistrsko delo obravnava različne algoritme stiskanja tekstovnih datotek in analizira, ali jezik, v katerem je zapisana vhodna datoteka, vpliva na uspešnost stiskanja z izbranimi algoritmi. Preučeni in predstavljeni bodo izbrani algoritmi stiskanja, ugotovljene prednosti uporabe izbranih algoritmov stiskanja tekstovnih datotek, določene entropije analiziranih jezikov na ravni znakov, izvedeni praktični testi izbranih algoritmov stiskanja tekstovnih datotek s testnimi vzorci različnih jezikov, analizirano in ugotovljeno, ali jezik v izbranih testnih vzorcih vpliva na uspešnost posameznih algoritmov stiskanja tekstovnih datotek. Delo bo iskalo povezave med entropijo jezika in uspešnostjo stiskanja. Na koncu bo na primeru Huffmanovega algoritma, ki kodira posamezne znake, preverjeno, ali kodiranje daljših nizov izboljša učinkovitost kodiranja.
Keywords:naravni jezik, entropija jezika, algoritmi stiskanja, algoritem LZW, tekstovne datoteke
Place of publishing:Maribor
Publisher:[K. Arzenšek]
Year of publishing:2024
PID:20.500.12556/DKUM-90482 New window
UDC:004.627.021:81'32(043.2)
COBISS.SI-ID:222701827 New window
Publication date in DKUM:23.12.2024
Views:114
Downloads:48
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:05.09.2024

Secondary language

Language:English
Title:Analysis of text compression algorithms in different languages
Abstract:In this master's thesis, we discuss different algorithms for compressing text files and analyse whether the language of the input text file affects the compression rate of selected algorithms. We study and present the selected compression algorithms, determine the advantages of using these algorithms, determine the entropies of analysed languages at the character level, perform practical tests of selected text file compression algorithms with test samples of different languages, analyse and determine whether the language of the selected test samples affects the performance of individual text file compression algorithms, and we look for relations between language entropy and compression rate. Finally, we compare the efficiency of the Huffman algorithm when encoding individual characters versus longer sequences of characters.
Keywords:natural language, language entropy, compression algorithms, LZW algorithm, text files


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