Formal Concept Analysis as a Framework for Business Intelligence Technologies

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F12%3A33141587" target="_blank" >RIV/61989592:15310/12:33141587 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-642-29892-9_20" target="_blank" >http://dx.doi.org/10.1007/978-3-642-29892-9_20</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-642-29892-9_20" target="_blank" >10.1007/978-3-642-29892-9_20</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Formal Concept Analysis as a Framework for Business Intelligence Technologies

Popis výsledku v původním jazyce

Numerical datasets in data mining are handled using various methods. In this paper, data mining of numerical data using FCA in combination with some interesting ideas from OLAP technology is proposed. This novel method is an enhancement of FCA, in whichmeasures are assigned to objects and/or attributes and then various numeric operations are applied to these measures (e.g. summarization, aggregation functions etc.). This new approach results in a structure, which is a concept lattice and where the extent and/or intent have aggregated values assigned to them. This structure could be seen as a generalization of OLAP technology. A concept lattice can be constrained by using various closure operators. The new closure operators presented here are based onvalues with very clear meaning for the user. Finally, a fuzzy OLAP formalization based on FCA in a fuzzy setting and using measures is proposed. Examples are shown for each introduced topic.

Název v anglickém jazyce

Formal Concept Analysis as a Framework for Business Intelligence Technologies

Popis výsledku anglicky

Numerical datasets in data mining are handled using various methods. In this paper, data mining of numerical data using FCA in combination with some interesting ideas from OLAP technology is proposed. This novel method is an enhancement of FCA, in whichmeasures are assigned to objects and/or attributes and then various numeric operations are applied to these measures (e.g. summarization, aggregation functions etc.). This new approach results in a structure, which is a concept lattice and where the extent and/or intent have aggregated values assigned to them. This structure could be seen as a generalization of OLAP technology. A concept lattice can be constrained by using various closure operators. The new closure operators presented here are based onvalues with very clear meaning for the user. Finally, a fuzzy OLAP formalization based on FCA in a fuzzy setting and using measures is proposed. Examples are shown for each introduced topic.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

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

Název periodika

Lecture Notes in Artificial Intelligence

ISSN

0302-9743

e-ISSN

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Svazek periodika

7278

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

DE - Spolková republika Německo

Počet stran výsledku

16

Strana od-do

195-210

Kód UT WoS článku

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EID výsledku v databázi Scopus

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