Approximate Galois Lattices of Formal Concepts

1993 ◽  
pp. 108-112 ◽  
Author(s):  
I. Van Mechelen
Keyword(s):  
Galois Lattices ◽  
Formal Concepts

Toward Road Safety Recommender Systems: Formal Concepts and Technical Basics

2021 ◽  
pp. 1-20
Author(s):  
Kaoutar Sefrioui Boujemaa ◽  
Ismail Berrada ◽  
Khalid Fardousse ◽  
Othmane Naggar ◽  
Francois Bourzeix
Keyword(s):  
Recommender Systems ◽  
Road Safety ◽  
Formal Concepts ◽  
Technical Basics

scholarly journals A Novel Concept Acquisition Approach Based on Formal Contexts

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Ting Qian ◽  
Ling Wei
Keyword(s):  
Data Analysis ◽  
Formal Concept Analysis ◽  
Real Life ◽  
Experimental Results ◽  
New Method ◽  
Concept Acquisition ◽  
Formal Concept ◽  
Knowledge Processing ◽  
Formal Concepts ◽  
Novel Concept

As an important tool for data analysis and knowledge processing, formal concept analysis (FCA) has been applied to many fields. In this paper, we introduce a new method to find all formal concepts based on formal contexts. The amount of intents calculation is reduced by the method. And the corresponding algorithm of our approach is proposed. The main theorems and the corresponding algorithm are examined by examples, respectively. At last, several real-life databases are analyzed to demonstrate the application of the proposed approach. Experimental results show that the proposed approach is simple and effective.

Scalable computation of the extensional and intensional stability of formal concepts

2018 ◽  
Vol 48 (1) ◽  
pp. 1-32 ◽  
Author(s):  
Amira Mouakher ◽  
Oumaima Ktayfi ◽  
Sadok Ben Yahia
Keyword(s):  
Formal Concepts ◽  
Scalable Computation

scholarly journals Conceptual Coverage Driven by Essential Concepts: A Formal Concept Analysis Approach

Mathematics ◽  
2021 ◽  
Vol 9 (21) ◽  
pp. 2694
Author(s):  
Amira Mouakher ◽  
Axel Ragobert ◽  
Sébastien Gerin ◽  
Andrea Ko
Keyword(s):  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Order Structure ◽  
Formal Concept ◽  
Massive Datasets ◽  
Interestingness Measures ◽  
Galois Lattice ◽  
Formal Concepts ◽  
Representation Method

Formal concept analysis (FCA) is a mathematical theory that is typically used as a knowledge representation method. The approach starts with an input binary relation specifying a set of objects and attributes, finds the natural groupings (formal concepts) described in the data, and then organizes the concepts in a partial order structure or concept (Galois) lattice. Unfortunately, the total number of concepts in this structure tends to grow exponentially as the size of the data increases. Therefore, there are numerous approaches for selecting a subset of concepts to provide full or partial coverage. In this paper, we rely on the battery of mathematical models offered by FCA to introduce a new greedy algorithm, called Concise, to compute minimal and meaningful subsets of concepts. Thanks to its theoretical properties, the Concise algorithm is shown to avoid the sluggishness of its competitors while offering the ability to mine both partial and full conceptual coverage of formal contexts. Furthermore, experiments on massive datasets also underscore the preservation of the quality of the mined formal concepts through interestingness measures agreed upon by the community.

Concrete illustrations of formal concepts

1978 ◽  
Vol 55 (3) ◽  
pp. 173
Author(s):  
David W. Brooks ◽  
John J. Scholz ◽  
Thomas J. Tipton
Keyword(s):  
Formal Concepts
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