Title:	OLAP recommender: supporting navigation in OLAP cubes using association rule mining
Authors:	Koukal, Bohumil Chudán, David Svátek, Vojtěch
Citation:	STEINBERGER, Josef ed.; ZÍMA, Martin ed.; FIALA, Dalibor ed.; DOSTAL, Martin ed.; NYKL, Michal ed. Data a znalosti 2017: sborník konference, Plzeň, Hotel Angelo 5. - 6. října 2017. 1. vyd. Plzeň: Západočeská univerzita v Plzni, 2017, s. 46-50. ISBN 978-80-261-0720-0.
Issue Date:	2017
Publisher:	Západočeská univerzita v Plzni
Document type:	konferenční příspěvek conferenceObject
URI:	https://www.zcu.cz/export/sites/zcu/pracoviste/vyd/online/DataAZnalosti2017.pdf http://hdl.handle.net/11025/26333
ISBN:	978-80-261-0720-0
Keywords:	OLAP navigace;pravidla sdružení GUHA;řízené analýzy
Keywords in different language:	OLAP navigation;GUHA association rules;guided analytics
Abstract in different language:	The OLAP Recommender tool automates the multidimensional data exploration process and recommends potentially interesting views on the data to the user. It integrates two data analytics methods – OLAP visualisation and data mining, the latter being represented by GUHA association rule mining. Algo-rithms implemented in the tool include automated data discretization, setup of dimensions’ commensurability, automatic design of the data mining task based on the data structure, and mapping between the mined association rules and the corresponding OLAP visualisation. The system was tested with real retail data and with EU structural funds data. The experiments indicate that complemen-tary usage of association rule mining and OLAP analysis identifies relationships in the data with higher success rate than the isolated use of both techniques.
Rights:	© Západočeská univerzita v Plzni
Appears in Collections:	Data a znalosti 2017 Data a znalosti 2017

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.