Poluautomatska izgradnja repozitorija povezanih podataka na temelju nestrukturiranog teksta s internetskih portala

master's thesis

• Title (english): Semi-Automated Construction of Linked Data Repository Using Unstructured Web Portals' Text
• Author: Goran Rumin
• Mentor: Igor Mekterović (mentor)
• Committee member: Igor Mekterović (predsjednik povjerenstva)
• Committee member: Gordan Gledec (član povjerenstva)
• Committee member: Mirta Baranović (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2017-07-14, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

U radu je najprije sagledano trenutačno stanje u semantičkom webu. Opisani su osnovni koncepti, tehnologije i poznatiji repozitoriji. Nastavlja se s pregledom koncepata strojnog učenja te načina na koji on može pomoći semantičkom webu. Pregledava se postojeće modele za prepoznavanje relacija te se izgrađuje i evaluira vlastiti. Zatim se opisuje servis koji koristi model za obradu tekstova s pet odabranih web portala s vijestima. Nabrajaju se komponente servisa te se pojedinačno opisuju. Nakon... More toga se opisuje izrađena ekstenzija za preglednik Chrome koja služi kao korisničko sučelje te stranica za vizualizaciju relacija. Na kraju se razmatra mogućnost kontinuiranog poboljšavanja modela. Less

Abstract (english)

The thesis first makes assessment of the current state in the field of semantic web. Basic concepts, technologies and repositories that are wider known are described. It is continued with overview of machine learning concepts and its potential benefits for the semantic web. Existing models for relation extraction are reviewed and own model is built and evaluated. Then the service which uses the model to process texts from five chosen news portals is described. Service components are listed... More and individually described. After that Chrome extension, which is used as a user interface, and page for relations visualization are described. At the end, possibility of continuous model improvement is considered. Less

• Keywords: semantički web; ekstrakcija relacija; strojno učenje; Linked Open Data; Chrome ekstenzija
• Keywords (english): semantic web; relation extraction; machine learning; Linked Open Data; Chrome extension
• Language: croatian
• URN:NBN: urn:nbn:hr:168:488677
• 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: 2019-03-14 00:32:37