Search (9 results, page 1 of 1)

  • × language_ss:"e"
  • × theme_ss:"Begriffstheorie"
  • × year_i:[2000 TO 2010}
  1. Evens, M.: Thesaural relations in information retrieval (2002) 0.02 
    0.01536896 = product of:
  0.06147584 = sum of:
    0.06147584 = weight(_text_:retrieval in 1201) [ClassicSimilarity], result of:
      0.06147584 = score(doc=1201,freq=10.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.44838852 = fieldWeight in 1201, product of:
          3.1622777 = tf(freq=10.0), with freq of:
            10.0 = termFreq=10.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=1201)
  0.25 = coord(1/4)
    Abstract
    Thesaural relations have long been used in information retrieval to enrich queries; they have sometimes been used to cluster documents as well. Sometimes the first query to an information retrieval system yields no results at all, or, what can be even more disconcerting, many thousands of hits. One solution is to rephrase the query, improving the choice of query terms by using related terms of different types. A collection of related terms is often called a thesaurus. This chapter describes the lexical-semantic relations that have been used in building thesauri and summarizes some of the effects of using these relational thesauri in information retrieval experiments
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Khoo, C.; Myaeng, S.H.: Identifying semantic relations in text for information retrieval and information extraction (2002) 0.01 
    0.011904745 = product of:
  0.04761898 = sum of:
    0.04761898 = weight(_text_:retrieval in 1197) [ClassicSimilarity], result of:
      0.04761898 = score(doc=1197,freq=6.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.34732026 = fieldWeight in 1197, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=1197)
  0.25 = coord(1/4)
    Abstract
    Automatic identification of semantic relations in text is a difficult problem, but is important for many applications. It has been used for relation matching in information retrieval to retrieve documents that contain not only the concepts but also the relations between concepts specified in the user's query. It is an integral part of information extraction-extracting from natural language text, facts or pieces of information related to a particular event or topic. Other potential applications are in the construction of relational thesauri (semantic networks of related concepts) and other kinds of knowledge bases, and in natural language processing applications such as machine translation and computer comprehension of text. This chapter examines the main methods used for identifying semantic relations automatically and their application in information retrieval and information extraction.
  3. Hetzler, B.: Visual analysis and exploration of relationships (2002) 0.01 
    0.011340214 = product of:
  0.045360856 = sum of:
    0.045360856 = weight(_text_:retrieval in 1189) [ClassicSimilarity], result of:
      0.045360856 = score(doc=1189,freq=4.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.33085006 = fieldWeight in 1189, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0546875 = fieldNorm(doc=1189)
  0.25 = coord(1/4)
    Abstract
    Relationships can provide a rich and powerful set of information and can be used to accomplish application goals, such as information retrieval and natural language processing. A growing trend in the information science community is the use of information visualization-taking advantage of people's natural visual capabilities to perceive and understand complex information. This chapter explores how visualization and visual exploration can help users gain insight from known relationships and discover evidence of new relationships not previously anticipated.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. ¬The semantics of relationships : an interdisciplinary perspective (2002) 0.01 
    0.009920621 = product of:
  0.039682485 = sum of:
    0.039682485 = weight(_text_:retrieval in 1430) [ClassicSimilarity], result of:
      0.039682485 = score(doc=1430,freq=6.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.28943354 = fieldWeight in 1430, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1430)
  0.25 = coord(1/4)
    Abstract
    Work on relationships takes place in many communities, including, among others, data modeling, knowledge representation, natural language processing, linguistics, and information retrieval. Unfortunately, continued disciplinary splintering and specialization keeps any one person from being familiar with the full expanse of that work. By including contributions form experts in a variety of disciplines and backgrounds, this volume demonstrates both the parallels that inform work on relationships across a number of fields and the singular emphases that have yet to be fully embraced, The volume is organized into 3 parts: (1) Types of relationships (2) Relationships in knowledge representation and reasoning (3) Applications of relationships
    Content
    Enthält die Beiträge: Pt.1: Types of relationships: CRUDE, D.A.: Hyponymy and its varieties; FELLBAUM, C.: On the semantics of troponymy; PRIBBENOW, S.: Meronymic relationships: from classical mereology to complex part-whole relations; KHOO, C. u.a.: The many facets of cause-effect relation - Pt.2: Relationships in knowledge representation and reasoning: GREEN, R.: Internally-structured conceptual models in cognitive semantics; HOVY, E.: Comparing sets of semantic relations in ontologies; GUARINO, N., C. WELTY: Identity and subsumption; JOUIS; C.: Logic of relationships - Pt.3: Applications of relationships: EVENS, M.: Thesaural relations in information retrieval; KHOO, C., S.H. MYAENG: Identifying semantic relations in text for information retrieval and information extraction; McCRAY, A.T., O. BODENREICHER: A conceptual framework for the biiomedical domain; HETZLER, B.: Visual analysis and exploration of relationships
  5. Hovy, E.: Comparing sets of semantic relations in ontologies (2002) 0.01 
    0.0068732076 = product of:
  0.02749283 = sum of:
    0.02749283 = weight(_text_:retrieval in 2178) [ClassicSimilarity], result of:
      0.02749283 = score(doc=2178,freq=2.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.20052543 = fieldWeight in 2178, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.046875 = fieldNorm(doc=2178)
  0.25 = coord(1/4)
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  6. Hjoerland, B.: Concept theory (2009) 0.01 
    0.005727673 = product of:
  0.022910692 = sum of:
    0.022910692 = weight(_text_:retrieval in 3461) [ClassicSimilarity], result of:
      0.022910692 = score(doc=3461,freq=2.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.16710453 = fieldWeight in 3461, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0390625 = fieldNorm(doc=3461)
  0.25 = coord(1/4)
    Abstract
    Concept theory is an extremely broad, interdisciplinary and complex field of research related to many deep fields with very long historical traditions without much consensus. However, information science and knowledge organization cannot avoid relating to theories of concepts. Knowledge organizing systems (e.g., classification systems, thesauri, and ontologies) should be understood as systems basically organizing concepts and their semantic relations. The same is the case with information retrieval systems. Different theories of concepts have different implications for how to construe, evaluate, and use such systems. Based on a post-Kuhnian view of paradigms, this article put forward arguments that the best understanding and classification of theories of concepts is to view and classify them in accordance with epistemological theories (empiricism, rationalism, historicism, and pragmatism). It is also argued that the historicist and pragmatist understandings of concepts are the most fruitful views and that this understanding may be part of a broader paradigm shift that is also beginning to take place in information science. The importance of historicist and pragmatic theories of concepts for information science is outlined.
  7. Jouis, C.: Logic of relationships (2002) 0.00 
    0.0038380611 = product of:
  0.0153522445 = sum of:
    0.0153522445 = product of:
      0.030704489 = sum of:
        0.030704489 = weight(_text_:22 in 1204) [ClassicSimilarity], result of:
          0.030704489 = score(doc=1204,freq=2.0), product of:
            0.15872006 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045324896 = queryNorm
            0.19345059 = fieldWeight in 1204, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1204)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    1.12.2002 11:12:22
  8. Olson, H.A.: How we construct subjects : a feminist analysis (2007) 0.00 
    0.0038380611 = product of:
  0.0153522445 = sum of:
    0.0153522445 = product of:
      0.030704489 = sum of:
        0.030704489 = weight(_text_:22 in 5588) [ClassicSimilarity], result of:
          0.030704489 = score(doc=5588,freq=2.0), product of:
            0.15872006 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.045324896 = queryNorm
            0.19345059 = fieldWeight in 5588, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5588)
      0.5 = coord(1/2)
  0.25 = coord(1/4)
    Date
    11.12.2019 19:00:22
  9. Conceptual structures : logical, linguistic, and computational issues. 8th International Conference on Conceptual Structures, ICCS 2000, Darmstadt, Germany, August 14-18, 2000 (2000) 0.00 
    0.0034366038 = product of:
  0.013746415 = sum of:
    0.013746415 = weight(_text_:retrieval in 691) [ClassicSimilarity], result of:
      0.013746415 = score(doc=691,freq=2.0), product of:
        0.13710396 = queryWeight, product of:
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.045324896 = queryNorm
        0.10026272 = fieldWeight in 691, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          3.024915 = idf(docFreq=5836, maxDocs=44218)
          0.0234375 = fieldNorm(doc=691)
  0.25 = coord(1/4)
    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)

Authors

Types

Themes