Contribution in edited book
Efficient Mining of Association Rules Based on Formal Concept Analysis
Publication Details
Authors: | Lakhal, L.; Stumme, G. |
Editor: | Ganter, Bernhard; Stumme, Gerd; Wille, Rudolf |
Publisher: | Springer |
Place: | Heidelberg |
Publication year: | 2005 |
Pages range : | 180-195 |
Book title: | Formal Concept Analysis: Foundations and Applications |
Title of series: | LNAI |
Volume number: | 3626 |
Abstract
Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, TITANIC, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.
Association rules are a popular knowledge discovery technique for warehouse basket analysis. They indicate which items of the warehouse are frequently bought together. The problem of association rule mining has first been stated in 1993. Five years later, several research groups discovered that this problem has a strong connection to Formal Concept Analysis (FCA). In this survey, we will first introduce some basic ideas of this connection along a specific algorithm, TITANIC, and show how FCA helps in reducing the number of resulting rules without loss of information, before giving a general overview over the history and state of the art of applying FCA for association rule mining.
Keywords
analysis, association, book, closed, concept, condensed, data, discovery, fca, formal, itegpub, itemsets, kdd, knowledge, l3s, mining, representations, rules
