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DKUM
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Title:
Implementacija infrastrukture za podporo pomenskemu rudarjenju v poslovnih informacijskih sistemih
Authors:
ID
Repnik, Lovro
(
Author
)
ID
Ojsteršek, Milan
(
Mentor
)
More about this mentor...
Files:
MAG_Repnik_Lovro_2016.pdf
(3,05 MB)
MD5: 07D8F146D99BF8E5BA4A7DB754B27A3E
Language:
Slovenian
Work type:
Master's thesis
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
V preteklem desetletju so potekale intenzivne raziskave in razvoj na področju podatkovnega rudarjenja. Še posebej tehnologije pomenskega spleta so se izkazale kot zelo primerne za rudarjenje po velikih količinah pomensko bogatih in heterogenih podatkov. Vendar je večina podatkov poslovnih informacijskih sistemov shranjenih v relacijskih podatkovnih bazah. Za uspešno uporabo metod pomenskega spleta v informacijskih sistemih je tako nujno ta dva svetova povezati. V predloženem delu smo raziskali potrebne tehnike in orodja za vključitev funkcionalnosti pomenskega rudarjenja v ogrodje za izdelavo poslovne programske opreme. Na podlagi obstoječe podatkovne baze smo kreirali domensko specifično ontologijo, za katero smo definirali preslikave med njo in izvorno relacijsko podatkovno bazo. S prosto dostopnimi orodji in knjižnicami smo postavili okolje za sprotno izvajanje poizvedb SPARQL v relacijski podatkovni bazi informacijskega sistema.
Keywords:
podatkovno rudarjenje
,
pomenski splet
,
ontologija
,
RDB2RDF
Place of publishing:
Maribor
Publisher:
[L. Repnik]
Year of publishing:
2016
PID:
20.500.12556/DKUM-60388
UDC:
004.652.4:004.774.2(043)
COBISS.SI-ID:
19696918
NUK URN:
URN:SI:UM:DK:TSMLCXLC
Publication date in DKUM:
07.07.2016
Views:
1230
Downloads:
152
Metadata:
Categories:
KTFMB - FERI
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Secondary language
Language:
English
Title:
Implementing Infrastructure for semantic Data Mining in Business Information Systems
Abstract:
In the past decade, there was intensive research and development in the field of data mining. Especially Semantic Web technologies have proven to be very suitable for mining large quantities of semantically rich and heterogeneous data. However, most business information systems store data in relational databases. It is essential to connect these two worlds and use semantic web techniques in information systems. In this thesis we study the required techniques and tools for integration of semantic data mining in a business software building framework. Based on the existing database, we have created a domain-specific ontology with definitions, used for reverse mapping back to the source relational database. Using open source tools and libraries we set up the environment for on-the-fly execution of SPARQL queries over data in the relational database of the information system.
Keywords:
data mining
,
semantic web
,
ontology
,
RDB2RDF
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