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doctoral thesis
Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2010. urn:nbn:hr:168:192256
Prcela, Marin
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Prcela, M. (2010). Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:192256

Prcela, Marin. "Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2010. https://urn.nsk.hr/urn:nbn:hr:168:192256

Prcela, Marin. "Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2010. https://urn.nsk.hr/urn:nbn:hr:168:192256

Prcela, M. (2010). 'Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 17 May 2024, https://urn.nsk.hr/urn:nbn:hr:168:192256

Prcela M. Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2010 [cited 2024 May 17] Available at: https://urn.nsk.hr/urn:nbn:hr:168:192256

M. Prcela, "Predstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2010. Available at: https://urn.nsk.hr/urn:nbn:hr:168:192256

Metadata
TitlePredstavljanje znanja zasnovano na integraciji ontologija i Bayesovih mreža
Title (english)Knowledge representation based on the integration of ontologies and Bayesian networks
AuthorMarin Prcela
MentorNikola Bogunović (mentor)
Committee memberBojana Dalbelo Bašić (predsjednik povjerenstva)
Committee memberDragan Gamberger (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2010-01-28, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		004 - Computer science and technology. Computing. Data processing
Abstract
Ontologije temeljene na deskriptivnoj logici imaju semantiku koja je dovoljno izražajna za formalizaciju opisnog znanja (opis domene, terminologija), a u jednom dijelu i proceduralnog znanja (akcije koje se izvršavaju). Baza znanja formalizirana na taj naĊin osnova je modernih medicinskih sustava za potporu pri odlučivanju koji se u trenutku upotrebe oslanjaju na vanjske izvore podataka o pacijentima - najčešće iz nekih elektronskih registara pacijenata (medicinskih baza podataka). U slučajevima kada nedostaje dio informacije potreban za donošenje zaključaka, sustav nije u mogućnosti donositi konkretne odluke. U takvim slučajevima, uvođenjem Bayesovih mreža u sustav, mogu se donositi zaključci temeljeni na nepotpunoj informaciji - koji su najvjerojatniji zaključci i koje su najinformativnije akcije koje vode konkretnim zaključcima. U doktorskom se radu kroz primjer dijagnoze srčanog zatajenja predlaže metodologija integracije dvaju već provjerenih oblika predstavljanja znanja: ontologije i Bayesovih mreža. Pritom se analiziraju oblici upotrebe ovako integriranog sustava te se definiraju postupci rasuđivanja u integriranom sustavu. Nadalje, opisuje se formalizam koji omogućuje uključivanje realnih medicinskih podataka promatranog pacijenta u ovako oblikovanoj bazi znanja. Na kraju se daje uvid u korisničko sučelje sustava te se analiziraju neke funkcionalne značajke sustava kao što su vrijeme izvođenja i pogreška učinjena pri rasuđivanju.
Abstract (english)
Ontologies based on description logic have expressive enough semantics to cover the descriptive part of knowledge base (domain description, terminology), and also a large part of procedural knowledge in the knowledge base (actions to be taken). Such encoded knowledge is the basis of modern medical decision support systems, which at the time of use also have rely on external patient data – typically from some electronic health record. In cases when some amount of information is missing the system often has to refrain to draw any concrete conclusion. In such cases by introducing Bayesian networks into the system conclusions can be made based on uncertain knowledge: what are the most probable conclusions and what are the most informative actions that possibly lead to concrete conclusions. Through the example of diagnosis of heart failure disease this dissertation demonstrates methodology for integration of two well known forms of knowledge representation: ontologies and Bayesian networks. Features of such integrated system are analyzed and reasoning procedures are defined. Furthermore, a formalism that includes data of observed patients into reasoning process is described. Finally, user interface of the example decision support system is described and some functional properties of the system are analyzed such as duration of reasoning and error made in reasoning.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:192256
Promotion2010
Study programmeTitle: Computer Science
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti (Doktor znanosti)
Type of resourceText
Extent150 str. : graf. prikazi
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2024-03-19 10:50:08