Rámec pro dolování asociačních pravidel z datových skladů

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F08%3APU80190" target="_blank" >RIV/00216305:26230/08:PU80190 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Framework for mining of association rules from data warehouse

Popis výsledku v původním jazyce

In this paper, we propose a framework for association rules mining from data warehouses. This framework presents alliance between two business intelligence areas. First area is represented by data warehouse and data cube providing high quality data. Thesecond area is represented by data mining, especially association rules mining providing an additional knowledge.<br>Association rules mining on data warehouses is different from mining on relational or transactional databases, because it deals with couple of dimensions, which form conceptual hierarchies. Thus we mine multi- and inter-dimensional association rules. There are several approaches how to mine such association rules described in literature. This framework presents a novel combination of thedata cube processing - top-down (on product dimensions) and bottom-up (on domain dimensions). We presume division of dimensions on domain and product dimensions. <br>The framework works in the following steps.&nbsp; The first one represen

Název v anglickém jazyce

Framework for mining of association rules from data warehouse

Popis výsledku anglicky

In this paper, we propose a framework for association rules mining from data warehouses. This framework presents alliance between two business intelligence areas. First area is represented by data warehouse and data cube providing high quality data. Thesecond area is represented by data mining, especially association rules mining providing an additional knowledge.<br>Association rules mining on data warehouses is different from mining on relational or transactional databases, because it deals with couple of dimensions, which form conceptual hierarchies. Thus we mine multi- and inter-dimensional association rules. There are several approaches how to mine such association rules described in literature. This framework presents a novel combination of thedata cube processing - top-down (on product dimensions) and bottom-up (on domain dimensions). We presume division of dimensions on domain and product dimensions. <br>The framework works in the following steps.&nbsp; The first one represen

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2008

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

ITAT 2008

ISBN

978-80-969184-8-5

ISSN

—

e-ISSN

—

Počet stran výsledku

4

Strana od-do

—

Název nakladatele

The University of Technology Košice

Místo vydání

Košice

Místo konání akce

Hotel Hrebienok, Starý Smokovec

Datum konání akce

22. 9. 2008

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—