Léonard Kwuida – författare

FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining.Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge.This edited book examines a set of important and relevant research directions in complex data management, and updates the  contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts.  For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.

FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining.Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge.

This edited book examines a set of important and relevant research directions in complex data management, and updates the  contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts.  For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.

FCA is an important formalism that is associated with a variety of research areas such as lattice theory, knowledge representation, data mining, machine learning, and semantic Web. It is successfully exploited in an increasing number of application domains such as software engineering, information retrieval, social network analysis, and bioinformatics. Its mathematical power comes from its concept lattice formalization in which each element in the lattice captures a formal concept while the whole structure represents a conceptual hierarchy that offers browsing, clustering and association rule mining.Complex data analytics refers to advanced methods and tools for mining and analyzing data with complex structures such as XML/Json data, text and image data, multidimensional data, graphs, sequences and streaming data. It also covers visualization mechanisms used to highlight the discovered knowledge.This edited book examines a set of important and relevant research directions in complex data management, and updates the  contribution of the FCA community in analyzing complex and large data such as knowledge graphs and interlinked contexts.  For example, Formal Concept Analysis and some of its extensions are exploited, revisited and coupled with recent processing parallel and distributed paradigms to maximize the benefits in analyzing large data.

This volume contains selected papers presented at ICFCA 2010, the 8th Int- national Conference on Formal Concept Analysis. The ICFCA conference series aims to be the prime forum for dissemination of advances in applied lattice and order theory, and in particular advances in theory and applications of Formal Concept Analysis. Formal Concept Analysis (FCA) is a ?eld of applied mathematics with its mathematical root in order theory, in particular the theory of complete lattices. Researchershadlongbeenawareofthefactthatthese?eldshavemanypotential applications.FCAemergedinthe1980sfrome?ortstorestructurelattice theory to promote better communication between lattice theorists and potential users of lattice theory. The key theme was the mathematical formalization of c- cept and conceptual hierarchy. Since then, the ?eld has developed into a growing research area in its own right with a thriving theoretical community and an - creasingnumberofapplicationsindataandknowledgeprocessingincludingdatavisualization, information retrieval, machine learning, sofware engineering, data analysis, data mining in Web 2.0, analysis of social networks, concept graphs, contextual logic and description logics. ICFCA 2010 took place during March 15–18, 2010 in Agadir, Morocco. We received 37 high-quality submissions out of which 17 were chosen as regular papers in these proceedings after a competitive selection process. Less mature works that were still considered valuable for discussion at the conference were collected in the supplementary proceedings. The papers in the present volume coveradvancesinvariousaspectsofFCArangingfromitstheoreticalfoundations to its applications in numerous other ?elds. In addition to the regular papers, thisvolumealsocontainsfourkeynotepapersarisingfromtheseveninvitedtalks given at the conference. We are also delighted to include a reprint of Bernhard Ganter’sseminalpaper on hiswell-knownalgorithmfor enumerating closedsets.