Knowledge representation and processing with formal concept analysis

Abstract

During the last three decades, formal concept analysis (FCA) became a well‐known formalism in data analysis and knowledge discovery because of its usefulness in important domains of knowledge discovery in databases (KDD) such as ontology engineering, association rule mining, machine learning, as well as relation to other established theories for representing knowledge processing, like description logics, conceptual graphs, and rough sets. In early days, FCA was sometimes misconceived as a static crisp hardly scalable formalism for binary data tables. In this paper, we will try to show that FCA actually provides support for processing large dynamical complex (may be uncertain) data augmented with additional knowledge. © 2013 Wiley Periodicals, Inc. This article is categorized under: Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining Fundamental Concepts of Data and Knowledge > Knowledge Representation Technologies > Computational Intelligence

An Overview of Knowledge Management Techniques for e-Recruitment

“…FCA can be applied to generate information context from a tentative domain specific scientific text, corpus or database which is then mapped to a formal ontology (Jia, Newman & Tianfield 2007). This paradigm can be applied in many different realms like psychology, sociology, anthropology, linguistics, computer science, mathematics and industrial engineering (Kuznetsov & Poelmans, 2013). In this scenario, it is necessary to generate content from a database of job applicants in order to build and/or enrich HR-Knowledge Bases concerning human resources.…”

The Structure of Oppositions in Rough Set Theory and Formal Concept Analysis - Toward a New Bridge between the Two Settings

“…Several authors have investigated the possibility of mixing the two theories or finding common points (see [25,48]), e.g. relating concept lattices and partitions [20], or the place of Galois connections in RST [43], or computing rough concepts [19].…”

“…In the attempt at mixing the two theories, several authors considered rough approximations of concepts in the FCA settings [16,25,37,48]. The basic idea is (see for instance p.205 of [25]) that given any set of objects T , the lower and upper approximations are…”

“…The basic idea is (see for instance p.205 of [25]) that given any set of objects T , the lower and upper approximations are…”

Parallelization of the next Closure algorithm for generating the minimum set of implication rules

“…[1][2][3] Its formalization was born in 1982 with the work of Wille, [4] who proposed considering each lattice element as a formal concept and the lattice itself as representing a conceptual hierarchy. [5] However, the applicability of FCA is limited by its capacity of dealing with huge data sets.…”