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Formal Concept Analysis is a field of applied mathematics based on the math­ematization of concept and conceptual hierarchy. It thereby activates math­ematical thinking for conceptual data analysis and knowledge processing. The underlying notion of “concept” evolved early in the philosophical theory of concepts and still has effects today. In mathematics it played a special role during the emergence of mathematical logic in the 19th century. Subsequently, however, it had virtually no impact on mathematical thinking. It was not until 1979 that the topic was revisited and treated more thoroughly. Since then, Formal Concept Analysis has fully emerged, sparking a multitude of publications for which the first edition of this textbook established itself as the standard reference in the literature, with a total of 10000+ citations. This is the second edition, revised and extended, of the textbook published originally in German (1996) and translated into English (1999), giving a systematic presentation of the mathematical foundations while also focusing on their possible applications for data analysis and knowledge processing. In times of digital knowledge processing, formal methods of conceptual analysis are gaining in importance. The book makes the basic theory for such methods accessible in a compact form, and presents graphical methods for representing concept systems that have proved themselves essential in communicating knowledge. The textbook complements each chapter with further notes, references and trends, putting the work in modern context and highlighting potential directions for further research. Additionally, the book contains an entirely new chapter on contextual concept logic, including a section on description logics and relational concept analysis. As such, it should be a valuable resource for students, instructors and researchers at the crossroads of subject areas like Applied and Discrete Mathematics, Logics, Theoretical Computer Science, Knowledge Processing, Data Science, and is meant to be used both for research and in class, as a teaching resource.

Computerscientistscreatemodelsofaperceivedreality.ThroughAItechniques, these models aim at providing the basic support for emulating cognitive - havior such as reasoning and learning, which is one of the main goals of the AI research e?ort. Such computer models are formed through the interaction of various acquisition and inference mechanisms: perception, concept learning, conceptual clustering, hypothesis testing, probabilistic inference, etc., and are represented using di?erent paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (?rst-order logic, modal logic, rule-based s- tems), virtual reality models (object systems, agent systems), probabilistic m- els(Bayesiannets,fuzzylogic),linguisticmodels(conceptualdependencygraphs, language-based representations), etc. OneofthestrengthsoftheConceptualGraph(CG)theoryisitsversatilityin terms of the representation paradigms under which it falls. It can be viewed and therefore used, under di?erent representation paradigms, which makes it a p- ular choice for a wealth of applications. Its full coupling with di?erent cognitive processes lead to the opening of the?eld toward related research communities such as the Description Logic, Formal Concept Analysis, and Computational Linguistic communities. We now see more and more research results from one community enrich the other, laying the foundations of common philosophical grounds from which a successful synergy can emerge.

This volume contains the Proceedings of ICFCA 2005, the 3rd International Conference on Formal Concept Analysis. The ICFCA conference series aims to be the premier forum for the publication of advances in applied lattice and order theory, and in particular scienti?c advances related to formal concept analysis. Formal concept analysis is a?eld of applied mathematics with its mat- matical root in order theory, in particular in the theory of complete lattices. Researchers had long been aware of the fact that these?elds have many - tential applications. Formal concept analysis emerged in the 1980s from e?orts to restructure lattice theory to promote better communication between lattice theorists and potential users of lattice theory. The key theme was the mathe- tization of concept and conceptual hierarchy. Since then, the?eld has developed into a growing research area in its own right with a thriving theoretical com- nity and an increasing number of applications in data and knowledge processing, including data visualization, information retrieval, machine learning, data an- ysis and knowledge management. ICFCA2005re?ectedbothpracticalbene?tsandprogressinthefoundational theory of formal concept analysis. Algorithmic aspects were discussed as well as e?orts to broaden the?eld. All regular papers appearing in this volume were refereed by at least two, in most cases three independent reviewers. The?nal decision to accept the papers was arbitrated by the Program Chairs based on the referee reports. It was the involvement of the Program Committee and the Editorial Board that ensured the scienti?c quality of these proceedings.

Formal concept analysis has been developed as a field of applied mathematics based on the mathematization of concept and concept hierarchy. It thereby allows us to mathematically represent, analyze, and construct conceptual structures. The formal concept analysis approach has been proven successful in a wide range of application fields. This book constitutes a comprehensive and systematic presentation of the state of the art of formal concept analysis and its applications. The first part of the book is devoted to foundational and methodological topics. The contributions in the second part demonstrate how formal concept analysis is successfully used outside of mathematics, in linguistics, text retrieval, association rule mining, data analysis, and economics. The third part presents applications in software engineering.

This volume contains the proceedings of ICCS 2003, the 11th International C- ferenceonConceptualStructures. Thisconferenceseriescontinuestobethemain forum for the presentation and discussion of state-of-the-art research on conc- tualstructures. Thetheories,methodologies,andtechniquespresentedherehave grown considerably in scope in recent years. On the other hand, solid bridges spanning the boundaries between such diverse?elds as Conceptual Graphs, F- mal Concept Analysis, and others are increasingly being built in our community. The theme of this year's conference was “Conceptual Structures for Kno- edge Creation and Communication”. In our increasingly (Inter)networked world, the potential support of information technology for the creation and commu- cation of quality knowledge is almost boundless. However, in reality, many c- ceptual barriers prevent the use of this potential. The main problem is no longer in the technological infrastructure, but in how to navigate, use, and manage the wealth of available data resources. Thus, the question is: how to create and communicate from data the information and ultimately the knowledge required by an ever more complex and dynamic society? Conceptual structures research focuses on what is behind and between the data glut and the information ov- load that need to be overcome in answering this question. In this way, our?eld contributes important ideas on how to actually realize some of the many still ambitious visions. All regular papers were reviewed in a thorough and open process by at least two reviewers and one editor.