Evaluating Association Rules in Boolean Matrix Factorization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F16%3A33160927" target="_blank" >RIV/61989592:15310/16:33160927 - 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

Evaluating Association Rules in Boolean Matrix Factorization

Popis výsledku v původním jazyce

Association rules, or association rule mining, is a well-established and popular method of data mining and machine learning successfully applied in many different areas since mid-nineties. Association rules form a ground of the Asso algorithm for discovery of the first (presumably most important) factors in Boolean matrix factorization. In Asso, the confidence parameter of association rules heavily influences the quality of factorization. However, association rules, in a more general form, appear already in GUHA, a knowledge discovery method developed since mid-sixties. In the paper, we evaluate the use of various (other) types of association rules from GUHA in Asso and, from the other side, a possible utilization of (particular) association rules in other Boolean matrix factorization algorithms not based on the rules. We compare the quality of factorization produced by the modified algorithms with those produced by the original algorithms.

Název v anglickém jazyce

Evaluating Association Rules in Boolean Matrix Factorization

Popis výsledku anglicky

Association rules, or association rule mining, is a well-established and popular method of data mining and machine learning successfully applied in many different areas since mid-nineties. Association rules form a ground of the Asso algorithm for discovery of the first (presumably most important) factors in Boolean matrix factorization. In Asso, the confidence parameter of association rules heavily influences the quality of factorization. However, association rules, in a more general form, appear already in GUHA, a knowledge discovery method developed since mid-sixties. In the paper, we evaluate the use of various (other) types of association rules from GUHA in Asso and, from the other side, a possible utilization of (particular) association rules in other Boolean matrix factorization algorithms not based on the rules. We compare the quality of factorization produced by the modified algorithms with those produced by the original algorithms.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

<a href="/cs/project/GA15-17899S" target="_blank" >GA15-17899S: Rozklady matic s booleovskými a ordinálními daty: teorie a algoritmy</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 16th ITAT Conference Information Technologies - Applications and Theory, ITAT 2016, Workshop on Computational Intelligence and Data Mining, WCIDM 2016

ISBN

978-1-5370-1674-0

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

147-154

Název nakladatele

CreateSpace Independent Publishing Platform

Místo vydání

Bratislava

Místo konání akce

Tatranské Matliare

Datum konání akce

15. 9. 2016

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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