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master's thesis
Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. urn:nbn:hr:168:523573
Bejuk, Borna
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Bejuk, B. (2019). Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:523573

Bejuk, Borna. "Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:523573

Bejuk, Borna. "Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2019. https://urn.nsk.hr/urn:nbn:hr:168:523573

Bejuk, B. (2019). 'Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:523573

Bejuk B. Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2019 [cited 2024 November 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:523573

B. Bejuk, "Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2019. Available at: https://urn.nsk.hr/urn:nbn:hr:168:523573

Metadata
TitleSemantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni
Title (english)Semantic Search of Text-based Knowledge Repositories in Business Domains
AuthorBorna Bejuk
MentorDamir Pintar (mentor)
Committee memberDamir Pintar (predsjednik povjerenstva)
Committee memberZoran Skočir (član povjerenstva)
Committee memberMihaela Vranić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2019-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Za izvlačenje korisnih informacija iz velike količine podataka potrebne su sofisticirane metode pretraživanja podataka. U slučaju sustava odgovaranja na upit potrebne su metode obrade upita, dohvaćanja podataka i odabira prikladnog odgovora. Ovaj rad bavi se izvlačenjem rečenice iz baze znanja koja predstavlja odgovor na pitanje upućeno sustavu. Većina rada posvećena je mjerenju semantičke sličnosti između pitanja i potencijalnog odgovora na hrvatskom jeziku. Implementirano je nekoliko tehnika reprezentiranja rečenica vektorom. Rad zaključuje da je običan TF-IDF vektor rečenice i kosinusna sličnost rečenica i dalje najbolja metoda usporedbe rečenica s obzirom na robusnost metode i lakoću korištenja.
Abstract (english)
For large amounts of textual information to be useful, appropriate search methods need to exist. In case of a question-answering system, methods of information retrieval, question processing and question answering are crucial. This thesis deals with non-factoid question answering where the answer is usually a sentence. Therefore, most of the work in the thesis is devoted to question-sentence semantic similarity task tested on Croatian language. Several sentence embedding techniques have been tested with various results. Thesis concludes that plain TF-IDF vectors of sentences combined with cosine similarity is still the preferable option for sentence comparison due to its robustness and ease of use.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:523573
Study programmeTitle: Computing
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
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Created on2020-01-07 16:40:45