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  • × theme_ss:"Formale Begriffsanalyse"
  1. Priss, U.: Faceted knowledge representation (1999) 0.01 
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    Abstract
    Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
    Date
    22. 1.2016 17:30:31
  2. Priss, U.: Faceted information representation (2000) 0.01 
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    Abstract
    This paper presents an abstract formalization of the notion of "facets". Facets are relational structures of units, relations and other facets selected for a certain purpose. Facets can be used to structure large knowledge representation systems into a hierarchical arrangement of consistent and independent subsystems (facets) that facilitate flexibility and combinations of different viewpoints or aspects. This paper describes the basic notions, facet characteristics and construction mechanisms. It then explicates the theory in an example of a faceted information retrieval system (FaIR)
    Date
    22. 1.2016 17:47:06
  3. Sowa, J.F.: Knowledge representation : logical, philosophical, and computational foundations (2000) 0.01 
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  4. Lex, W.: ¬A representation of concepts for their computerization (1987) 0.00 
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    Abstract
    A lattice theoretical description of concept hierarchies is developed using for attributes the terms "given", "negated", "open" and "impossible" as the truth-values of a four-valued logic. Similar to the theory of B. Ganter and R. Wille so does this framework permit a precise representation of the usual interdependences in a field of related concepts - such as superconcepts, subconcept, contrary concepts etc. -, whenever the concepts under consideration can be sufficiently described by the presence or absence of certain attributes ...
  5. Kent, R.E.: Implications and rules in thesauri (1994) 0.00 
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    Abstract
    A central consideration in the study of whole language semantic space as encoded in thesauri is word sense comparability. Shows how word sense comparability can be adequately expressed by the logical implications and rules from Formal Concept Analysis. Formal concept analysis, a new approach to formal logic initiated by Rudolf Wille, has been used for data modelling, analysis and interpretation, and also for knowledge representation and knowledge discovery
  6. Luksch, P.; Wille, R.: ¬A mathematical model for conceptual knowledge systems (1991) 0.00 
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    Abstract
    Objects, attributes, and concepts are basic notations of conceptual knowledge; they are linked by the following four basic relations: an object has an attribute, an object belongs to a concept, an attribute abstracts from a concept, and a concept is a subconcept of another concept. These structural elements are well mathematized in formal concept analysis. Therefore, conceptual knowledge systems can be mathematically modelled in the frame of formal concept analysis. How such modelling may be performed is indicated by an example of a conceptual knowledge system. The formal definition of the model finally clarifies in which ways representation, inference, acquisition, and communication of conceptual knowledge can be mathematically treated
  7. Kollewe, W.: Data representation by nested line diagrams illustrated by a survey of pensioners (1991) 0.00 
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  8. Working with conceptual structures : contributions to ICCS 2000. 8th International Conference on Conceptual Structures: Logical, Linguistic, and Computational Issues. Darmstadt, August 14-18, 2000 (2000) 0.00 
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    Content
    Concepts & Language: Knowledge organization by procedures of natural language processing. A case study using the method GABEK (J. Zelger, J. Gadner) - Computer aided narrative analysis using conceptual graphs (H. Schärfe, P. 0hrstrom) - Pragmatic representation of argumentative text: a challenge for the conceptual graph approach (H. Irandoust, B. Moulin) - Conceptual graphs as a knowledge representation core in a complex language learning environment (G. Angelova, A. Nenkova, S. Boycheva, T. Nikolov) - Conceptual Modeling and Ontologies: Relationships and actions in conceptual categories (Ch. Landauer, K.L. Bellman) - Concept approximations for formal concept analysis (J. Saquer, J.S. Deogun) - Faceted information representation (U. Priß) - Simple concept graphs with universal quantifiers (J. Tappe) - A framework for comparing methods for using or reusing multiple ontologies in an application (J. van ZyI, D. Corbett) - Designing task/method knowledge-based systems with conceptual graphs (M. Leclère, F.Trichet, Ch. Choquet) - A logical ontology (J. Farkas, J. Sarbo) - Algorithms and Tools: Fast concept analysis (Ch. Lindig) - A framework for conceptual graph unification (D. Corbett) - Visual CP representation of knowledge (H.D. Pfeiffer, R.T. Hartley) - Maximal isojoin for representing software textual specifications and detecting semantic anomalies (Th. Charnois) - Troika: using grids, lattices and graphs in knowledge acquisition (H.S. Delugach, B.E. Lampkin) - Open world theorem prover for conceptual graphs (J.E. Heaton, P. Kocura) - NetCare: a practical conceptual graphs software tool (S. Polovina, D. Strang) - CGWorld - a web based workbench for conceptual graphs management and applications (P. Dobrev, K. Toutanova) - Position papers: The edition project: Peirce's existential graphs (R. Mülller) - Mining association rules using formal concept analysis (N. Pasquier) - Contextual logic summary (R Wille) - Information channels and conceptual scaling (K.E. Wolff) - Spatial concepts - a rule exploration (S. Rudolph) - The TEXT-TO-ONTO learning environment (A. Mädche, St. Staab) - Controlling the semantics of metadata on audio-visual documents using ontologies (Th. Dechilly, B. Bachimont) - Building the ontological foundations of a terminology from natural language to conceptual graphs with Ribosome, a knowledge extraction system (Ch. Jacquelinet, A. Burgun) - CharGer: some lessons learned and new directions (H.S. Delugach) - Knowledge management using conceptual graphs (W.K. Pun)
  9. Priss, U.: Lattice-based information retrieval (2000) 0.00 
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    Abstract
    A lattice-based model for information retrieval was suggested in the 1960's but has been seen as a theoretical possibility hard to practically apply ever since. This paper attempts to revive the lattice model and demonstrate its applicability in an information retrieval system, FalR, that incorporates a graphical representation of a faceted thesaurus. It shows how Boolean queries can be lattice-theoretically related to the concepts of the thesaurus and visualized within the thesaurus display. An advantage of FaIR is that it allows for a high level of transparency of the system, which can be controlled by the user
  10. Priss, U.: ¬A graphical interface for conceptually navigating faceted thesauri (1998) 0.00 
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    Abstract
    This paper describes a graphical interface for the navigation and construction of faceted thesauri that is based on formal concept analysis. Each facet of a thesaurus is represented as a mathematical lattice that is further subdivided into components. Users can graphically navigate through the Java implementation of the interface by clicking on terms that connect facets and components. Since there are many applications for thesauri in the knowledge representation field, such a graphical interface has the potential of being very useful
  11. Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000) 0.00 
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    Abstract
    Computer scientists create models of a perceived reality. Through AI techniques, these models aim at providing the basic support for emulating cognitive behavior such as reasoning and learning, which is one of the main goals of the Al research effort. 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 different paradigms tightly linked to the processes that use them. Among these paradigms let us cite: biological models (neural nets, genetic programming), logic-based models (first-order logic, modal logic, rule-based systems), virtual reality models (object systems, agent systems), probabilistic models (Bayesian nets, fuzzy logic), linguistic models (conceptual dependency graphs, language-based rep resentations), etc. One of the strengths of the Conceptual Graph (CG) theory is its versatility in terms of the representation paradigms under which it falls. It can be viewed and therefore used, under different representation paradigms, which makes it a popular choice for a wealth of applications. Its full coupling with different cognitive processes lead to the opening of the field 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. ICCS 2000 embodies this spirit of research collaboration. It presents a set of papers that we believe, by their exposure, will benefit the whole community. For instance, the technical program proposes tracks on Conceptual Ontologies, Language, Formal Concept Analysis, Computational Aspects of Conceptual Structures, and Formal Semantics, with some papers on pragmatism and human related aspects of computing. Never before was the program of ICCS formed by so heterogeneously rooted theories of knowledge representation and use. We hope that this swirl of ideas will benefit you as much as it already has benefited us while putting together this program
    Content
    Concepts and Language: The Role of Conceptual Structure in Human Evolution (Keith Devlin) - Concepts in Linguistics - Concepts in Natural Language (Gisela Harras) - Patterns, Schemata, and Types: Author Support through Formalized Experience (Felix H. Gatzemeier) - Conventions and Notations for Knowledge Representation and Retrieval (Philippe Martin) - Conceptual Ontology: Ontology, Metadata, and Semiotics (John F. Sowa) - Pragmatically Yours (Mary Keeler) - Conceptual Modeling for Distributed Ontology Environments (Deborah L. McGuinness) - Discovery of Class Relations in Exception Structured Knowledge Bases (Hendra Suryanto, Paul Compton) - Conceptual Graphs: Perspectives: CGs Applications: Where Are We 7 Years after the First ICCS ? (Michel Chein, David Genest) - The Engineering of a CC-Based System: Fundamental Issues (Guy W. Mineau) - Conceptual Graphs, Metamodeling, and Notation of Concepts (Olivier Gerbé, Guy W. Mineau, Rudolf K. Keller) - Knowledge Representation and Reasonings: Based on Graph Homomorphism (Marie-Laure Mugnier) - User Modeling Using Conceptual Graphs for Intelligent Agents (James F. Baldwin, Trevor P. Martin, Aimilia Tzanavari) - Towards a Unified Querying System of Both Structured and Semi-structured Imprecise Data Using Fuzzy View (Patrice Buche, Ollivier Haemmerlé) - Formal Semantics of Conceptual Structures: The Extensional Semantics of the Conceptual Graph Formalism (Guy W. Mineau) - Semantics of Attribute Relations in Conceptual Graphs (Pavel Kocura) - Nested Concept Graphs and Triadic Power Context Families (Susanne Prediger) - Negations in Simple Concept Graphs (Frithjof Dau) - Extending the CG Model by Simulations (Jean-François Baget) - Contextual Logic and Formal Concept Analysis: Building and Structuring Description Logic Knowledge Bases: Using Least Common Subsumers and Concept Analysis (Franz Baader, Ralf Molitor) - On the Contextual Logic of Ordinal Data (Silke Pollandt, Rudolf Wille) - Boolean Concept Logic (Rudolf Wille) - Lattices of Triadic Concept Graphs (Bernd Groh, Rudolf Wille) - Formalizing Hypotheses with Concepts (Bernhard Ganter, Sergei 0. Kuznetsov) - Generalized Formal Concept Analysis (Laurent Chaudron, Nicolas Maille) - A Logical Generalization of Formal Concept Analysis (Sébastien Ferré, Olivier Ridoux) - On the Treatment of Incomplete Knowledge in Formal Concept Analysis (Peter Burmeister, Richard Holzer) - Conceptual Structures in Practice: Logic-Based Networks: Concept Graphs and Conceptual Structures (Peter W. Eklund) - Conceptual Knowledge Discovery and Data Analysis (Joachim Hereth, Gerd Stumme, Rudolf Wille, Uta Wille) - CEM - A Conceptual Email Manager (Richard Cole, Gerd Stumme) - A Contextual-Logic Extension of TOSCANA (Peter Eklund, Bernd Groh, Gerd Stumme, Rudolf Wille) - A Conceptual Graph Model for W3C Resource Description Framework (Olivier Corby, Rose Dieng, Cédric Hébert) - Computational Aspects of Conceptual Structures: Computing with Conceptual Structures (Bernhard Ganter) - Symmetry and the Computation of Conceptual Structures (Robert Levinson) An Introduction to SNePS 3 (Stuart C. Shapiro) - Composition Norm Dynamics Calculation with Conceptual Graphs (Aldo de Moor) - From PROLOG++ to PROLOG+CG: A CG Object-Oriented Logic Programming Language (Adil Kabbaj, Martin Janta-Polczynski) - A Cost-Bounded Algorithm to Control Events Generalization (Gaël de Chalendar, Brigitte Grau, Olivier Ferret)
  12. Ganter, B.; Wille, R.: Formal concept analysis : mathematical foundations (1998) 0.00 
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    Abstract
    This is the first textbook on formal concept analysis. It gives a systematic presentation of the mathematical foundations and their relation to applications in computer science, especially data analysis and knowledge processing. Above all, it presents graphical methods for representing conceptual systems that have proved themselves in communicating knowledge. Theory and graphical representation are thus closely coupled together. The mathematical foundations are treated thouroughly and illuminated by means of numerous examples. Since computers are being used ever more widely for knowledge processing, formal methods for conceptual analysis are gaining in importance. This book makes the basic theory for such methods accessible in a compact form
  13. Burmeister, P.; Holzer, R.: On the treatment of incomplete knowledge in formal concept analysis (2000) 0.00 
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    Abstract
    Some possible treatments of incomplete knowledge in conceptual data representation, data analysis and knowledge acquisition are presented. In particular, some ways of conceptual scalings as well as the role of the three-valued KLEENE-logic are briefly investigated. This logic is also one background in attribute exploration, a conceptual tool for knowledge acquisition. For this method a strategy is given to obtain as much of (attribute) implicational knowledge about a given "universe" as possible; and we show how to represent incomplete knowledge in order to be able to pin down the questions still to be answered in order to obtain complete knowledge in this situation
  14. De Maio, C.; Fenza, G.; Loia, V.; Senatore, S.: Hierarchical web resources retrieval by exploiting Fuzzy Formal Concept Analysis (2012) 0.00 
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    Abstract
    In recent years, knowledge structuring is assuming important roles in several real world applications such as decision support, cooperative problem solving, e-commerce, Semantic Web and, even in planning systems. Ontologies play an important role in supporting automated processes to access information and are at the core of new strategies for the development of knowledge-based systems. Yet, developing an ontology is a time-consuming task which often needs an accurate domain expertise to tackle structural and logical difficulties in the definition of concepts as well as conceivable relationships. This work presents an ontology-based retrieval approach, that supports data organization and visualization and provides a friendly navigation model. It exploits the fuzzy extension of the Formal Concept Analysis theory to elicit conceptualizations from datasets and generate a hierarchy-based representation of extracted knowledge. An intuitive graphical interface provides a multi-facets view of the built ontology. Through a transparent query-based retrieval, final users navigate across concepts, relations and population.
  15. Carpineto, C.; Romano, G.: Order-theoretical ranking (2000) 0.00 
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    Abstract
    Current best-match ranking (BMR) systems perform well but cannot handle word mismatch between a query and a document. The best known alternative ranking method, hierarchical clustering-based ranking (HCR), seems to be more robust than BMR with respect to this problem, but it is hampered by theoretical and practical limitations. We present an approach to document ranking that explicitly addresses the word mismatch problem by exploiting interdocument similarity information in a novel way. Document ranking is seen as a query-document transformation driven by a conceptual representation of the whole document collection, into which the query is merged. Our approach is nased on the theory of concept (or Galois) lattices, which, er argue, provides a powerful, well-founded, and conputationally-tractable framework to model the space in which documents and query are represented and to compute such a transformation. We compared information retrieval using concept lattice-based ranking (CLR) to BMR and HCR. The results showed that HCR was outperformed by CLR as well as BMR, and suggested that, of the two best methods, BMR achieved better performance than CLR on the whole document set, whereas CLR compared more favorably when only the first retrieved documents were used for evaluation. We also evaluated the three methods' specific ability to rank documents that did not match the query, in which case the speriority of CLR over BMR and HCR was apparent
  16. Hereth, J.; Stumme, G.; Wille, R.; Wille, U.: Conceptual knowledge discovery and data analysis (2000) 0.00 
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    Abstract
    In this paper, we discuss Conceptual Knowledge Discovery in Databases (CKDD) in its connection with Data Analysis. Our approach is based on Formal Concept Analysis, a mathematical theory which has been developed and proven useful during the last 20 years. Formal Concept Analysis has led to a theory of conceptual information systems which has been applied by using the management system TOSCANA in a wide range of domains. In this paper, we use such an application in database marketing to demonstrate how methods and procedures of CKDD can be applied in Data Analysis. In particular, we show the interplay and integration of data mining and data analysis techniques based on Formal Concept Analysis. The main concern of this paper is to explain how the transition from data to knowledge can be supported by a TOSCANA system. To clarify the transition steps we discuss their correspondence to the five levels of knowledge representation established by R. Brachman and to the steps of empirically grounded theory building proposed by A. Strauss and J. Corbin
  17. Kaytoue, M.; Kuznetsov, S.O.; Assaghir, Z.; Napoli, A.: Embedding tolerance relations in concept lattices : an application in information fusion (2010) 0.00 
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    Series
    Knowledge and data representation and management; no.7353
  18. Priss, U.: Formal concept analysis in information science (2006) 0.00 
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    Date
    13. 7.2008 19:29:59
  19. Prediger, S.: Kontextuelle Urteilslogik mit Begriffsgraphen : Ein Beitrag zur Restrukturierung der mathematischen Logik (1998) 0.00 
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    Date
    26. 2.2008 15:58:22
  20. Vogt, F.; Wille, R.: TOSCANA - a graphical tool for analyzing and exploring data (1995) 0.00 
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    Source
    Knowledge organization. 22(1995) no.2, S.78-81

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