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CLA
2006
13 years 6 months ago
An Algorithm to Find Frequent Concepts of a Formal Context with Taxonomy
Formal Concept Analysis (FCA) considers attributes as a non-ordered set. This is appropriate when the data set is not structured. When an attribute taxonomy exists, existing techni...
Peggy Cellier, Sébastien Ferré, Oliv...
ICFCA
2007
Springer
13 years 10 months ago
A Parameterized Algorithm for Exploring Concept Lattices
Kuznetsov shows that Formal Concept Analysis (FCA) is a natural framework for learning from positive and negative examples. Indeed, the results of learning from positive examples (...
Peggy Cellier, Sébastien Ferré, Oliv...
ISCC
2002
IEEE
147views Communications» more  ISCC 2002»
13 years 9 months ago
A new method for finding generalized frequent itemsets in generalized association rule mining
Generalized association rule mining is an extension of traditional association rule mining to discover more informative rules, given a taxonomy. In this paper, we describe a forma...
Kritsada Sriphaew, Thanaruk Theeramunkong
KDD
2005
ACM
145views Data Mining» more  KDD 2005»
14 years 5 months ago
Using and Learning Semantics in Frequent Subgraph Mining
The search for frequent subgraphs is becoming increasingly important in many application areas including Web mining and bioinformatics. Any use of graph structures in mining, howev...
Bettina Berendt
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