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Title:Obdelava in gručenje naravnih besedil v programskem okolju python : diplomsko delo
Authors:ID Štingl, Eva (Author)
ID Podgorelec, Vili (Mentor) More about this mentor... New window
Files:.pdf UN_Stingl_Eva_2022.pdf (3,98 MB)
MD5: 4D3B152009994BABF1E19CC204379EC3
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Strojno učenje, ki se ukvarja z obravnavo naravnega jezika, je vseprisotno v našem vsakdanjiku. V tem diplomskem delu smo si podrobno pogledali kaj je naravni jezik in kaj zajema njegova obravnava. Opisali smo knjižnice za delo z njim in jih primerjali. Prav tako pa smo opredelili tip nenadzorovanega učenja – gručenja, ki se pogosto uporablja nad naravnimi besedili. V okviru dela smo opisali postopek gručenja in nekaj algoritmov. Nad scenarijem celotne serije Igra prestolov smo izvedli sentimentalno analizo stavkov in opravili gručenje nad podatki. Narisani grafi, so nam pokazali zanimiv rezultate gručenja po sentimentih. Gruče smo kontekstualizirali s pomočjo poznavanja vsebine serije in dogajanja v njej.
Keywords:gručenje, obdelava naravnega jezika, predprocesiranje besedila, knjižnice za obdelavo naravnega jezika, metoda voditeljev
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[E. Štingl]
Year of publishing:2022
Number of pages:1 spletni vir (1 datoteka PDF ([VIII], 28 f.))
PID:20.500.12556/DKUM-82743 New window
UDC:004.85:004.93'14(043.2)
COBISS.SI-ID:137176579 New window
Publication date in DKUM:24.10.2022
Views:890
Downloads:79
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:31.08.2022

Secondary language

Language:English
Title:Natural Language Processing and Clustering in Python
Abstract:Machine learning that processes natural language is a part of our everyday lives. In this thesis, we researched what natural language is and what its processing covers. We described the libraries for working with it and compared them. We also defined a type of unsupervised learning - clustering, which is often used when dealing with natural language. As part of the work, we described the clustering process and some algorithms. We performed a sentimental sentence analysis on the script of the entire series Game of Thrones and performed clustering on the data. The drawn graphs showed us interesting results of clustering by sentiments. We contextualized the clusters with the help of knowing the content of the series and the events that take place in it.
Keywords:clustering, natural language processing, text preprocessing, natural language processing libraries, Kmeans algorithm


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