Mining association rules from imprecise ordinal data
type: Item
instance of: scholarly article
title: Mining association rules from imprecise ordinal data
zbMATH Open document ID: 1176.68157
author: Yen-Liang Chen
author: Cheng-Hsiung Weng
published in: Fuzzy Sets and Systems
publication date: 2009-08-26T00:00:00Z
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 5598524
zbMATH Keywords: data mining
zbMATH Keywords: association rules
zbMATH Keywords: imprecise ordinal data
MaRDI profile type: Publication
full work available at URL: j.fss.2007.10.005
OpenAlex ID: W1971539696
cites work: A new approach for discovering fuzzy quantitative sequential patterns in sequence databases
cites work: Mining generalized knowledge from ordered data through attribute-oriented induction techniques
cites work: Clustering web transactions using rough approximation
cites work: Mining association rules using inverted hashing and pruning.
cites work: Algorithms for mining association rules in bag databases
cites work: Q2766981
cites work: Mining optimized support rules for numeric attributes
cites work: Database classification for multi-database mining
DOI: 10.1016/J.FSS.2007.10.005
description: scientific article; zbMATH DE number 5598524