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CIDM
2007
IEEE
13 years 11 months ago
Measuring the Validity of Document Relations Discovered from Frequent Itemset Mining
— The extension approach of frequent itemset mining can be applied to discover the relations among documents. Several schemes, i.e., n-gram, stemming, stopword removal and term w...
Kritsada Sriphaew, Thanaruk Theeramunkong
SAC
2010
ACM
13 years 10 months ago
Mining interesting sets and rules in relational databases
In this paper we propose a new and elegant approach toward the generalization of frequent itemset mining to the multirelational case. We define relational itemsets that contain i...
Bart Goethals, Wim Le Page, Michael Mampaey
KDD
2007
ACM
170views Data Mining» more  KDD 2007»
14 years 5 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
DASFAA
2005
IEEE
153views Database» more  DASFAA 2005»
13 years 10 months ago
FASST Mining: Discovering Frequently Changing Semantic Structure from Versions of Unordered XML Documents
Abstract. In this paper, we present a FASST mining approach to extract the frequently changing semantic structures (FASSTs), which are a subset of semantic substructures that chang...
Qiankun Zhao, Sourav S. Bhowmick
CORR
2010
Springer
173views Education» more  CORR 2010»
13 years 2 months ago
Mining Multi-Level Frequent Itemsets under Constraints
Mining association rules is a task of data mining, which extracts knowledge in the form of significant implication relation of useful items (objects) from a database. Mining multi...
Mohamed Salah Gouider, Amine Farhat