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The Galois (or concept) lattice produced from a binary relation has been proved useful for many applications. Building the Galois lattice can be considered as a conceptual clustering method since it results in a concept hierarchy. This article presents incremental algorithms for updating the Galois lattice and corresponding graph, resulting in an(More)
1. Software reuse is one of the most advertised advantages of object-orientation. Inheritance, in all its forms, plays an important part in achieving greater reuse, at all stages of development. Class hierarchies start taking shape at the analysis level, where classes that share application-significant data and application-meaningful external behavior are(More)
Building and maintaining the class hierarchy has been recognized as an important but one of the most difficult activities of object-oriented design. Concept (or Galois) lattices and related structures are presented as a framework for dealing with the design and maintenance of class hierarchies. Because the design of class hierarchies is inherently an(More)
This paper describes a concept formation approach to the discovery of new concepts and implication rules from data. This machine learning approach is based on the Galois lattice theory, and starts from a binary relation between a set of objects and a set of properties (descriptors) to build a concept lattice and a set of rules. Each node (concept) of the(More)
Galois (concept) lattice theory has been successfully applied to the resolution of the association rule problem in data mining. In particular, structural results about lattices have been used in the design of efficient procedures for mining the frequent patterns (itemsets) in a transaction database. As transaction databases are often dynamic, we propose a(More)
Association rule mining from a transaction database (TDB) requires the detection of frequently occurring patterns, called frequent itemsets (FIs), whereby the number of FIs may be potentially huge. Recent approaches for FI mining use the closed itemset paradigm to limit the mining effort to a subset of the entire FI family, the frequent closed itemsets(More)