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master's thesis
Primjena metoda strojnog učenja u analizi korisničkih upita
2017. urn:nbn:hr:200:679105
Komljenović, Nikola
Josip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
Department of Computer Engineering and Automation
Chair of Automation and Robotics

Cite this document

Komljenović, N. (2017). Primjena metoda strojnog učenja u analizi korisničkih upita (Master's thesis). Retrieved from https://urn.nsk.hr/urn:nbn:hr:200:679105

Komljenović, Nikola. "Primjena metoda strojnog učenja u analizi korisničkih upita." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2017. https://urn.nsk.hr/urn:nbn:hr:200:679105

Komljenović, Nikola. "Primjena metoda strojnog učenja u analizi korisničkih upita." Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, 2017. https://urn.nsk.hr/urn:nbn:hr:200:679105

Komljenović, N. (2017). 'Primjena metoda strojnog učenja u analizi korisničkih upita', Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, accessed 24 May 2022, https://urn.nsk.hr/urn:nbn:hr:200:679105

Komljenović N. Primjena metoda strojnog učenja u analizi korisničkih upita [Master's thesis]. Osijek: Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek; 2017 [cited 2022 May 24] Available at: https://urn.nsk.hr/urn:nbn:hr:200:679105

N. Komljenović, "Primjena metoda strojnog učenja u analizi korisničkih upita", Master's thesis, Josip Juraj Strossmayer University of Osijek, Faculty of Electrical Engineering, Computer Science and Information Technology Osijek, Osijek, 2017. Available at: https://urn.nsk.hr/urn:nbn:hr:200:679105

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Metadata
TitlePrimjena metoda strojnog učenja u analizi korisničkih upita
Title (english)Machine learning in user inquiry analysis
AuthorNikola Komljenović
MentorRatko Grbić (mentor)
Committee memberRatko Grbić (predsjednik povjerenstva)
Committee memberEmmanuel Karlo Nyarko (član povjerenstva)
Committee memberJosip Job (član povjerenstva)
GranterJosip Juraj Strossmayer University of Osijek
Faculty of Electrical Engineering, Computer Science and Information Technology Osijek
(Department of Computer Engineering and Automation)
(Chair of Automation and Robotics)
Osijek
Defense date and country2017-09-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Information Systems
Abstract
U ovom radu dan je pregled metoda za klasifikaciju korisničkih upita i obradu prirodnog jezika korištenjem strojnog učenja. Dohvaćeni su podaci sa društvenih mreža koji su zatim ručno klasificirani, obrađeni te korišteni za izgradnju i evaluaciju klasifikatora. Korišteni algoritmi za klasifikaciju su Naivni Bayesov algoritam i strojevi sa potpornim vektorima. Rezultati evaluacije dobiveni su u obliku matrice zabune i općenitog postotka ispravnog klasificiranja upita u testnom skupu. Upiti se uspješno klasificiraju te sustav pokazuje dobre rezultate i na zahtjevnijim upitima korisnika. Model je implementiran unutar web aplikacije u koju korisnik unosi upit i osnovne podatke, aplikacija klasificira upit kroz implementirane modele te konačan rezultat zajedno sa upitom i podacima sprema u bazu podataka i ispisuje u web aplikaciji.
Abstract (english)
This paper reviews the methods for classifying user queries and natural language processing using machine learning. Data from social networks has been fetched, which are then manually classified, processed and used to construct and evaluate the classifier. Used classification algorithms are Naive Bayes algorithm and support vector machines. The test set of data was submitted to classifier, and an evaluation of the obtained classes was conducted for each query. Evaluation results were obtained in the form of confusion matrix and the overall percentage of correct classification of queries in the test set. Queries are successfully classified, and the system shows good results even on more demanding user queries. Model is implemented within a web application where user inputs the query and personal data, application classifies query through the implemented models, and final result along with query and data saves it in database and prints it in the web application.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:200:679105
Study programmeTitle: Graduate University Study Programme in Computer Engineering
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2017-10-27 15:14:30