Generation of frequent item sets in multidimensional data by means of templates for mining inter-dimensional association rules

Autor:	Mykola Fisun, Inessa Kulakovska, Hlib Horban
Rok vydání:	2015
Předmět:	Apriori algorithm Template Association rule learning Computer science Representation (systemics) Multidimensional data Algorithm design Data mining computer.software_genre computer
Zdroj:	IDAACS
DOI:	10.1109/idaacs.2015.7340760
Popis:	This paper presents the formalized apparatus of mining inter-dimensional association rules in multidimensional data, their representation by means of templates, and also the method of all frequent item sets generation in multidimensional data with help of which association rules can be generated by preset templates.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::21a549397a71a10860519ff418eb1c70 https://doi.org/10.1109/idaacs.2015.7340760 Zobrazit plný text záznamu