TY - JOUR AU - Pasquier, Nicolas AU - Taouil, Rafik AU - Bastide, Yves AU - Stumme, Gerd AU - Lakhal, Lotfi T1 - Generating a Condensed Representation for Association Rules JO - Journal Intelligent Information Systems (JIIS) PY - 2005/ VL - 24 IS - 1 SP - 29 EP - 60 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2005/pasquier2005generating.pdf M3 - KW - 2005 KW - OntologyHandbook KW - analysis KW - association KW - closed KW - concept KW - condensed KW - data KW - discovery KW - fca KW - formal KW - itegpub KW - itemset KW - kdd KW - knowledge KW - l3s KW - mining KW - myown KW - representations KW - rule KW - rules KW - sets L1 - SN - N1 - alpha N1 - AB - ER - TY - GEN AU - Lakhal, Lotfi AU - Stumme, Gerd A2 - Ganter, Bernhard A2 - Stumme, Gerd A2 - Wille, Rudolf T1 - Efficient Mining of Association Rules Based on Formal Concept Analysis JO - PB - Springer AD - Heidelberg PY - 2005/ VL - 3626 IS - SP - 180 EP - 195 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2005/lakhal2005efficient.pdf M3 - KW - 2005 KW - analysis KW - association KW - book KW - closed KW - concept KW - condensed KW - data KW - discovery KW - fca KW - formal KW - itegpub KW - itemsets KW - kdd KW - knowledge KW - l3s KW - mining KW - myown KW - representations KW - rules L1 - N1 - N1 - AB - 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, 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. ER -