Articles producció científica> Enginyeria Informàtica i Matemàtiques

A New Model to Compute the Information Content of Concepts from Taxonomic Knowledge

  • Identification data

    Identifier: imarina:9385370
    Authors:
    Sanchez, DavidBatet, Montserrat
    Abstract:
    The Information Content (IC) of a concept quantifies the amount of information it provides when appearing in a context. In the past, IC used to be computed as a function of concept appearance probabilities in corpora, but corpora-dependency and data sparseness hampered results. Recently, some other authors tried to overcome previous approaches, estimating IC from the knowledge modeled in an ontology. In this paper, the authors develop this idea, by proposing a new model to compute the IC of a concept exploiting the taxonomic knowledge modeled in an ontology. In comparison with related works, their proposal aims to better capture semantic evidences found in the ontology. To test the authors' approach, they have applied it to well-known semantic similarity measures, which were evaluated using standard benchmarks. Results show that the use of the authors' model produces, in most cases, more accurate similarity estimations than related works.
  • Others:

    Author, as appears in the article.: Sanchez, David; Batet, Montserrat
    Department: Enginyeria Informàtica i Matemàtiques
    URV's Author/s: Batet Sanromà, Montserrat / Sánchez Ruenes, David
    Keywords: Semantic similarity estimation Semantic similarity Semantic similarit Semantic knowledge Relatednes Ontologies Knowledge management Information content Computational linguistics
    Abstract: The Information Content (IC) of a concept quantifies the amount of information it provides when appearing in a context. In the past, IC used to be computed as a function of concept appearance probabilities in corpora, but corpora-dependency and data sparseness hampered results. Recently, some other authors tried to overcome previous approaches, estimating IC from the knowledge modeled in an ontology. In this paper, the authors develop this idea, by proposing a new model to compute the IC of a concept exploiting the taxonomic knowledge modeled in an ontology. In comparison with related works, their proposal aims to better capture semantic evidences found in the ontology. To test the authors' approach, they have applied it to well-known semantic similarity measures, which were evaluated using standard benchmarks. Results show that the use of the authors' model produces, in most cases, more accurate similarity estimations than related works.
    Thematic Areas: Social statistics and informatics Science and technology studies Planejamento urbano e regional / demografia Pedagogical & educational research Linguistics Library and information science Interdisciplinary research in the social sciences Interdisciplinary research in the humanities Information systems Computer science, information systems Computer science, artificial intelligence Computer networks and communications Ciencias sociales Ciencias humanas Business and management
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: montserrat.batet@urv.cat david.sanchez@urv.cat
    Author identifier: 0000-0001-8174-7592 0000-0001-7275-7887
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/submittedVersion
    Link to the original source: https://www.igi-global.com/article/new-model-compute-information-content/70742
    Papper original source: International Journal On Semantic Web And Information Systems. 8 (2): 34-50
    APA: Sanchez, David; Batet, Montserrat (2012). A New Model to Compute the Information Content of Concepts from Taxonomic Knowledge. International Journal On Semantic Web And Information Systems, 8(2), 34-50. DOI: 10.4018/jswis.2012040102
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Article's DOI: 10.4018/jswis.2012040102
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2012
    Publication Type: Journal Publications
  • Keywords:

    Computer Networks and Communications,Computer Science, Artificial Intelligence,Computer Science, Information Systems,Information Systems
    Semantic similarity estimation
    Semantic similarity
    Semantic similarit
    Semantic knowledge
    Relatednes
    Ontologies
    Knowledge management
    Information content
    Computational linguistics
    Social statistics and informatics
    Science and technology studies
    Planejamento urbano e regional / demografia
    Pedagogical & educational research
    Linguistics
    Library and information science
    Interdisciplinary research in the social sciences
    Interdisciplinary research in the humanities
    Information systems
    Computer science, information systems
    Computer science, artificial intelligence
    Computer networks and communications
    Ciencias sociales
    Ciencias humanas
    Business and management
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