Frequent itemset mining of distributed uncertain data under user-defined constraints
Loading...
Date
2012
Authors
Cuzzocrea, Alfredo
Leung, Carson K.
Journal Title
Journal ISSN
Volume Title
Publisher
Edizioni Libreria Progetto
Abstract
Many existing distributed data mining algorithms do not allow users to express the patterns to be mined according to their intention via the use of constraints. Consequently, these unconstrained mining algorithms can yield numerous patterns that are not interesting to users. Moreover, due to inherited measurement inaccuracies and/or network latencies, data are often riddled with uncertainty. These call for constrained mining and uncertain data mining. In this paper, we propose a tree-based system for mining frequent itemsets that satisfy user-defined constraints from a distributed environment such as a wireless sensor network of uncertain data.
Description
Cuzzocrea, A., Leung, C.K.: Frequent itemset mining of distributed uncertain data under user-defined constraints. In: SEBD 2012, pp. 243-250. Copyright (c) 2012 - Edizioni Libreria Progetto and the authors
Keywords
data mining, knowledge discovery, constraints, distributed data, frequent itemsets, uncertain data
Citation
Cuzzocrea, A., Leung, C.K.: Frequent itemset mining of distributed uncertain data under user-defined constraints. In: SEBD 2012, pp. 243-250.