prikaz prve stranice dokumenta Classification and Information Extraction from Documents in the Domain of Culture
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master's thesis
Classification and Information Extraction from Documents in the Domain of Culture
2021. urn:nbn:hr:195:679471
Bogović, Petar Kristijan
University of Rijeka
Faculty of Informatics and Digital Technologies

Cite this document

Bogović, P. K. (2021). Classification and Information Extraction from Documents in the Domain of Culture (Master's thesis). Rijeka: University of Rijeka. Retrieved from https://urn.nsk.hr/urn:nbn:hr:195:679471

Bogović, Petar Kristijan. "Classification and Information Extraction from Documents in the Domain of Culture." Master's thesis, University of Rijeka, 2021. https://urn.nsk.hr/urn:nbn:hr:195:679471

Bogović, Petar Kristijan. "Classification and Information Extraction from Documents in the Domain of Culture." Master's thesis, University of Rijeka, 2021. https://urn.nsk.hr/urn:nbn:hr:195:679471

Bogović, P. K. (2021). 'Classification and Information Extraction from Documents in the Domain of Culture', Master's thesis, University of Rijeka, accessed 27 April 2024, https://urn.nsk.hr/urn:nbn:hr:195:679471

Bogović PK. Classification and Information Extraction from Documents in the Domain of Culture [Master's thesis]. Rijeka: University of Rijeka; 2021 [cited 2024 April 27] Available at: https://urn.nsk.hr/urn:nbn:hr:195:679471

P. K. Bogović, "Classification and Information Extraction from Documents in the Domain of Culture", Master's thesis, University of Rijeka, Rijeka, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:195:679471

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Metadata
TitleClassification and Information Extraction from Documents in the Domain of Culture
Title (croatian)Klasifikacija i ekstrakcija informacija iz tekstova u domeni kulture
AuthorPetar Kristijan Bogović
MentorSanda Martinčić-Ipšić (mentor)
Committee memberAna Meštrović (predsjednik povjerenstva)
Committee memberSanda Martinčić-Ipšić (član povjerenstva)
Committee memberBožidar Kovačić (član povjerenstva)
GranterUniversity of Rijeka
(Faculty of Informatics and Digital Technologies)
Rijeka
Defense date and country2021-03-30, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract
The main goal of this thesis is to develop procedures for computer analysis of documents in the field of culture, cultural policies and activities. The collected documents need to be preprocessed and prepared for further computer processing, e.g. to perform lemmatization, stemming, and other NLP procedures. In this thesis, various NLP procedures will be implemented: classification, automatic extraction of keywords and locations, and the topic modeling procedure. Automatic text classification will be implemented to classify documents into already defined categories of cultural policy impacts on broader social aspects, using a standard word bag model for document representation and machine learning algorithms such as Naive Bayes, Support Vector Machine and Random Tree Forests for the classification of documents. Automatic keyword and location extraction procedures will be implemented using the MAUI keyword extraction method and the Named Entity Recognition algorithm with available tools. The topic modeling process will be performed using the Latent Dirichlet Allocation (LDA) and evaluated using the coherence of the obtained topics.
Abstract (croatian)
Glavni cilj ovog diplomskog rada jest izradit postupke za računalnu analizu dokumenta iz domene kulture, kulturnih politika i aktivnosti. Prikupljene dokumente potrebno je pročistiti i pripremiti za daljnju računalnu obradu npr. provesti lematizaciju, korijenovanje, i ostale NLP postupke. U ovom diplomskom radu implementirati će se različiti NLP postupci: klasifikacija, automatsko izlučivanje ključnih riječi i lokacija te postupak modeliranja tema(topic modelling). Automatska klasifikacija teksta implementirati će se kako bi se dokumenti klasificrali u već definirane kategorije utjecaja kulturnih politika na šire socijalne aspekte primjene, uz pomoć standardnog modela „vreće riječi“ za reprezentaciju dokumenata te algoritmi strojnog učenja poput Naivnog Bayes, Support Vector Machine te Šume slučajnih stabala za samu klasifikaciju dokumenata. Postupci automatskog izlučivanja ključnih riječi i lokacija implementirati će se pomoću MAUI metode za ključne riječi te Named Entity Recognition algoritma sa dostupnim alatima. Postupak modeliranja tema izvršiti će se pomoću Latentne Dirichletove Alokacije(LDA) te evaluirati pomoću koherentnosti dobivenih tema.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:195:679471
Study programmeTitle: Informatics
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra informatike (magistar/magistra informatike)
Type of resourceText
File originReformatted digital
Access conditionsAccess restricted to students and staff of home institution
Terms of useLicence In copyright icon
Created on2021-03-29 08:39:41