Generating frequent itemsets incrementally: two novel approaches based on Galois lattice theory

DOI10.1080/09528130210164198zbMath1022.68043OpenAlexW2084144744MaRDI QIDQ4409021

Petko Valtchev, Rokia Missaoui, Mohamed Meridji, Robert Godin

Publication date: 28 October 2003

Published in: Journal of Experimental & Theoretical Artificial Intelligence (Search for Journal in Brave)

Full work available at URL: http://www.archipel.uqam.ca/8330/1/Valtchev-2002a-preprint.pdf

zbMATH Keywords

data miningfrequent closed itemsets

Mathematics Subject Classification ID

Database theory (68P15) Lattices (06B99)

Related Items (6)

Fast factorization by similarity in formal concept analysis of data with fuzzy attributes ⋮ Representation of algebraic domains by formal association rule systems ⋮ Abstract Concept Lattices ⋮ A framework for incremental generation of closed itemsets ⋮ An incremental algorithm to construct a lattice of set intersections ⋮ Meta itemset: a new concise representation of frequent itemset

Uses Software

• CLOSET

Cites Work

• An incremental concept formation approach for learning from databases
• A partition-based approach towards constructing Galois (concept) lattices
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