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Zlivanje podatkov v relacijskih podatkovnih bazah
ID Bernik, Matic (Author), ID Curk, Tomaž (Mentor) More about this mentor... This link opens in a new window

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Abstract
Analiza podatkov in odkrivanje povezav med entitetnimi tipi znotraj podatkovnih baz sta lahko zelo zahtevni in zamudni opravili. Vsaka baza ima specifično strukturo, raziskovanje katere od uporabnika terja veliko časa. V diplomski nalogi ovrednotimo uporabo rekonstrukcijske napake pri modeliranju z matričnim razcepom kot mero za ocenjevanje stopnje povezanosti med tabelami oz. entitetnimi tipi v podatkovnih bazah. V ta namen smo razvili orodje, ki se poveže na podatkovno bazo in izpiše rangiran seznam relacij med hranjenimi entitetnimi tipi. Uporabnik lahko tako odkrije informativne povezave in usmerjeno raziskuje podatkovno bazo.

Language:Slovenian
Keywords:zlivanje podatkov, podatkovna baza, rangiranje relacij, preiskovalna analiza
Work type:Bachelor thesis/paper
Organization:FRI - Faculty of Computer and Information Science
Year:2018
PID:20.500.12556/RUL-103533 This link opens in a new window
Publication date in RUL:19.09.2018
Views:2068
Downloads:249
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Secondary language

Language:English
Title:Data fusion of relational databases
Abstract:
Data analysis and discovery of relations between connected entity types within databases can be very labour and time intensive. The reason being that every database has its specific structure, which needs to be examined. In this thesis, we evaluated if the reconstruction error of the matrix factorization model can be used to relate tables or entity types within a database. To test this concept, we developed a Python module that connects to a database and returns a ranked list of relations (pairs of entity types). This enables the user to identify the most informative relations and explore them further.

Keywords:data fusion, database, relation ranking, exploratory analysis

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