Semantičko pretraživanje tekstualnih baza znanja u poslovnoj domeni

master's thesis

• Title (english): Semantic Search of Text-based Knowledge Repositories in Business Domains
• Author: Borna Bejuk
• Mentor: Damir Pintar (mentor)
• Committee member: Damir Pintar (predsjednik povjerenstva)
• Committee member: Zoran Skočir (član povjerenstva)
• Committee member: Mihaela Vranić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2019-07-09, 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: odgovaranje na upit; obrada pitanja; dohvaćanje podataka; reprezentiranje rečenica; obrada prirodnog jezika; nlp
• Keywords (english): question answering; question processing; non-factoid question answering; information retrieval; sentence embedding; natural language processing; nlp
• Language: croatian
• URN:NBN: urn:nbn:hr:168:523573
• Study programme: Title: Computing; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2020-01-07 16:40:45