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DKUM
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UM - University of Maribor
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Title:
SISTEM ZA UPORABNIŠKO POMENSKO OZNAČEVANJE VSEBIN
Authors:
ID
Žnidar, Primož
(Author)
ID
Ojsteršek, Milan
(Mentor)
More about this mentor...
Files:
MAG_Znidar_Primoz_2013.pdf
(3,34 MB)
MD5: E8929358DACDA94829A1B1F1A4512571
Language:
Slovenian
Work type:
Master's thesis/paper (mb22)
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V magistrskem delu predstavljamo sisteme za uporabniško pomensko označevanje vsebin in njihovo uporabo. Najprej smo opisali razna orodja in implementacije sistemov, ki se že uporabljajo, nato pa smo v praktičnem delu izdelali lastni sistem. Na njem uporabniki vpišejo spletne naslove strani, katere želijo dodatno obogatiti s pomenskimi oznakami. Sistem vsebuje svojo bazo znanja in dovoljuje uporabnikom dopolnjevanje z novimi izrazi in njihovimi pomeni, manjkajoče znanje pa pridobi iz Wikipedije. Na koncu smo naš sistem primerjali z obstoječimi in podali njegove prednosti ter slabosti.
Keywords:
sistemi za pomensko označevanje
,
pomenski splet
,
metapodatki
Year of publishing:
2013
Publisher:
[P. Žnidar]
Source:
Maribor
PID:
20.500.12556/DKUM-42030
UDC:
004.774.2(043.2)
COBISS.SI-ID:
17526294
NUK URN:
URN:SI:UM:DK:JIYHRQXV
Publication date in DKUM:
20.09.2013
Views:
1178
Downloads:
127
Metadata:
Categories:
KTFMB - FERI
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Hover the mouse pointer over a document title to show the abstract or click on the title to get all document metadata.
Secondary language
Language:
English
Title:
SYSTEM FOR USER SEMANTIC ANNOTATION OF CONTENT
Abstract:
In this thesis we present systems for semantic annotation of user content. First, we describe various tools and implementations of systems, that are already in use. In the practical part of this thesis we developed our own system. On it, users enter web addresses, of which content they want to semantically annotate. The system contains its own knowledge base and allows users to supplement it with new tags and their meanings. Any missing knowledge is acquired from Wikipedia. Finally, we compare our system with existing ones and look for it’s strengths and weaknesses.
Keywords:
systems for semantic annotation
,
semantic web
,
metadata
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