Quantitative and Ordinal Association Rules Mining (QAR Mining)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F06%3A00121132" target="_blank" >RIV/68407700:21230/06:00121132 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Quantitative and Ordinal Association Rules Mining (QAR Mining)

Popis výsledku v původním jazyce

Association rules have exhibited an excellent ability to identify interesting association relationships among a set of binary variables describing huge amount of transactions. Although the rules can be relatively easily generalized to other variable types, the generalization can result in a computationally expensive algorithm generating a prohibitive number of redundant rules of little significance. This danger especially applies to quantitative and ordinal variables. This paper presents and verifies analternative approach to the quantitative and ordinal association rule mining. In this approach, quantitative or ordinal variables are not immediately transformed into a set of binary variables. Instead, it applies simple arithmetic operations in order to construct the cedents and searches for areas of increased association which are finally decomposed into conjunctions of literals. This scenario outputs rules that do not syntactically differentiate from classical association rules.

Název v anglickém jazyce

Quantitative and Ordinal Association Rules Mining (QAR Mining)

Popis výsledku anglicky

Association rules have exhibited an excellent ability to identify interesting association relationships among a set of binary variables describing huge amount of transactions. Although the rules can be relatively easily generalized to other variable types, the generalization can result in a computationally expensive algorithm generating a prohibitive number of redundant rules of little significance. This danger especially applies to quantitative and ordinal variables. This paper presents and verifies analternative approach to the quantitative and ordinal association rule mining. In this approach, quantitative or ordinal variables are not immediately transformed into a set of binary variables. Instead, it applies simple arithmetic operations in order to construct the cedents and searches for areas of increased association which are finally decomposed into conjunctions of literals. This scenario outputs rules that do not syntactically differentiate from classical association rules.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

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Návaznosti

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Rok uplatnění

2006

Kód důvěrnosti údajů

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

Název statě ve sborníku

Knowledge-Based Intelligent Information and Engineering Systems, Part I

ISBN

3-540-46535-9

ISSN

0302-9743

e-ISSN

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Počet stran výsledku

8

Strana od-do

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Název nakladatele

Springer

Místo vydání

Berlin

Místo konání akce

Bournemouth

Datum konání akce

9. 10. 2006

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000242122000024