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Title:
STATISTIČNI GENERATOR BESEDIL V SLOVENSKEM JEZIKU
Authors:
ID
Petrović, Goran
(Author)
ID
Sepesy Maučec, Mirjam
(Mentor)
More about this mentor...
ID
Žgank, Andrej
(Comentor)
Files:
UNI_Petrovic_Goran_2012.pdf
(2,06 MB)
MD5: E839869F2AE5040891D9C4BC392C09FE
PID:
20.500.12556/dkum/2411da69-3cb0-45e3-b963-2017d6140849
Language:
Slovenian
Work type:
Bachelor thesis/paper
Typology:
2.11 - Undergraduate Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V diplomskem delu smo se posvetili generatorjem besedil. Opravili smo analizo obstoječih generatorjev in izdelali preprost eksperimentalni generator besedil, ki tvori besedila v slovenskem jeziku. Temelji na statistiki n-gramov. Za izdelavo programa smo uporabili okolje Code::Blocks, na voljo smo imeli sezname frekvenc besednih unigramov, bigramov in trigramov ter n-gramov z MSD-oznakami. Analizirali smo tvorjena besedila iz dveh scenarijev in podali rezultate ter končni sklep uporabe n-gramov z MSD-oznakami in brez njih.
Keywords:
generator besedil v naravnem jeziku
,
Markove verige
,
n-gramski modeli
Place of publishing:
Maribor
Publisher:
[G. Petrović]
Year of publishing:
2012
PID:
20.500.12556/DKUM-38565
UDC:
004.93:621.39(043.2)
COBISS.SI-ID:
16424726
NUK URN:
URN:SI:UM:DK:KECC7ATD
Publication date in DKUM:
14.11.2012
Views:
2031
Downloads:
136
Metadata:
Categories:
KTFMB - FERI
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:
PETROVIĆ, Goran, 2012,
STATISTIČNI GENERATOR BESEDIL V SLOVENSKEM JEZIKU
[online]. Bachelor’s thesis. Maribor : G. Petrović. [Accessed 30 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=38565
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Secondary language
Language:
English
Title:
STATISTICAL GENERATOR OF TEXT IN SLOVENIAN LANGUAGE
Abstract:
The diploma work analyse text generators. We developed a simple experimental text generator, that generates text in Slovenian language based on n-gram statistics. During the process of development we used Code::Blocks environment and lists of unigrams, bigrams and trigrams of words and n-grams with MSD tags attached. Generated sentences in both scenarios were analyzed and results were presented. We also made a conclusion about using word n-grams and n-grams with MSD tags.
Keywords:
natural language generator
,
Markov chain
,
n-gram models
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