Formal Concept Analysis Based Clustering

Formal Concept Analysis Based Clustering

Author: 
Saquer, Jamil M.
Place: 
Hershey
Publisher: 
IGI Global
Date published: 
2008
Editor: 
Wang, John
Journal Title: 
Encyclopedia of Data Warehousing and Mining, Second Edition
Source: 
Encyclopedia of Data Warehousing and Mining, Second Edition
Subject: 
Abstract: 

Formal concept analysis (FCA) is a branch of applied mathematics with roots in lattice theory (Wille, 1982; Ganter & Wille, 1999). It deals with the notion of a concept in a given universe, which it calls context. For example, consider the context of transactions at a grocery store where each transaction consists of the items bought together. A concept here is a pair of two sets (A, B). A is the set of transactions that contain all the items in B and B is the set of items common to all the transactions in A. A successful area of application for FCA has been data mining. In particular, techniques from FCA have been successfully used in the association mining problem and in clustering (Kryszkiewicz, 1998; Saquer, 2003; Zaki & Hsiao, 2002). In this article, we review the basic notions of FCA and show how they can be used in clustering.

CITATION: Saquer, Jamil M.. Formal Concept Analysis Based Clustering edited by Wang, John . Hershey : IGI Global , 2008. Encyclopedia of Data Warehousing and Mining, Second Edition - Available at: https://library.au.int/frformal-concept-analysis-based-clustering