Formal Concept Analysis as Applied Lattice Theory

2008 ◽  
pp. 42-67 ◽  
Author(s):  
Rudolf Wille
Keyword(s):  
Formal Concept Analysis ◽  
Lattice Theory ◽  
Concept Analysis ◽  
Formal Concept

Formal Concept Analysis Based Clustering

2011 ◽  
pp. 514-518
Author(s):  
Jamil M. Saquer
Keyword(s):  
Data Mining ◽  
Formal Concept Analysis ◽  
Lattice Theory ◽  
Applied Mathematics ◽  
Concept Analysis ◽  
Grocery Store ◽  
Association Mining ◽  
Formal Concept ◽  
Area Of Application

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.

Formal Concept Analysis Based Clustering

2011 ◽  
pp. 895-900 ◽  
Author(s):  
Jamil M. Saquer
Keyword(s):  
Data Mining ◽  
Formal Concept Analysis ◽  
Lattice Theory ◽  
Applied Mathematics ◽  
Concept Analysis ◽  
Grocery Store ◽  
Association Mining ◽  
Formal Concept ◽  
Area Of Application

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.

scholarly journals Formal concept analysis for amino acids classification and visualization

2020 ◽  
Vol 12 (1) ◽  
pp. 22-38 ◽  
Author(s):  
Adrian-Sorin Telcian ◽  
Daniela-Maria Cristea ◽  
Ioan Sima
Keyword(s):  
Amino Acids ◽  
Information System ◽  
Formal Concept Analysis ◽  
Lattice Theory ◽  
Concept Analysis ◽  
Formal Concept ◽  
Structure And Properties ◽  
Conceptual Information ◽  
Hasse Diagrams

AbstractFormal concept analysis (FCA) is a method based on lattice theory, widely used for data visualization, data analysis and knowledge discovery. Amino acids (AAs) are chemical molecules that constitute the proteins. In this paper is presented a new and easy way of visualizing of the structure and properties of AAs. In addition, we performed a new Hydrophobic-Polar classification of AAs using FCA. For this, the 20 proteinogenic AAs were clustered, classified by hydrophobicity and visualized in Hasse-diagrams. Exploring and processing the dataset was done with Elba and ToscanaJ, some FCA tools and Conceptual Information System (CIS).

scholarly journals Continuous Domains in Formal Concept Analysis*

2021 ◽  
Vol 179 (3) ◽  
pp. 295-319
Author(s):  
Longchun Wang ◽  
Lankun Guo ◽  
Qingguo Li
Keyword(s):  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Continuous Functions ◽  
Formal Context ◽  
Formal Concept ◽  
Contractive Mappings ◽  
Continuous Domains ◽  
Algebraic Domains ◽  
Scott Continuous ◽  
Continuous Domain

Formal Concept Analysis (FCA) has been proven to be an effective method of restructuring complete lattices and various algebraic domains. In this paper, the notion of contractive mappings over formal contexts is proposed, which can be viewed as a generalization of interior operators on sets into the framework of FCA. Then, by considering subset-selections consistent with contractive mappings, the notions of attribute continuous formal contexts and continuous concepts are introduced. It is shown that the set of continuous concepts of an attribute continuous formal context forms a continuous domain, and every continuous domain can be restructured in this way. Moreover, the notion of F-morphisms is identified to produce a category equivalent to that of continuous domains with Scott continuous functions. The paper also investigates the representations of various subclasses of continuous domains including algebraic domains and stably continuous semilattices.

The Research of Semantic Web Service Matching Algorithm Based on the Formal Concept Analysis

2013 ◽  
Vol 760-762 ◽  
pp. 1708-1712
Author(s):  
Ying Fang Li ◽  
Ying Jiang Li ◽  
Yan Li ◽  
Yang Bo
Keyword(s):  
Semantic Web ◽  
Web Service ◽  
Formal Concept Analysis ◽  
Service Discovery ◽  
Concept Lattice ◽  
Concept Analysis ◽  
Formal Concept ◽  
Semantic Web Service ◽  
Matching Algorithm ◽  
Service Matching

At present, as the number of web services resources on the network drastically increased, how to quickly and efficiently find the needed services from publishing services has become a problem to resolve. Aiming at the problems of low efficiency in service discovery of traditional web service, the formal concept analysis ( FCA) is introduced into the semantic Web service matching, and a Matching Algorithm based semantic web service is proposed. With considering the concept of limited inheritance,this method introduces the concept of limited inheritance to the semantic similarity calculation based on the concept lattice. It is significant in enhancing the service function matching in practical applications through adjust the calculation.

Set approximations in fuzzy formal concept analysis

2007 ◽  
Vol 158 (23) ◽  
pp. 2627-2640 ◽  
Author(s):  
Ming-Wen Shao ◽  
Min Liu ◽  
Wen-Xiu Zhang
Keyword(s):  
Formal Concept Analysis ◽  
Concept Analysis ◽  
Formal Concept ◽  
Fuzzy Formal Concept ◽  
Fuzzy Formal Concept Analysis
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