Search (2 results, page 1 of 1)

0.009625921 = product of:
  0.019251842 = sum of:
    0.019251842 = product of:
      0.038503684 = sum of:
        0.038503684 = weight(_text_:systems in 5787) [ClassicSimilarity], result of:
          0.038503684 = score(doc=5787,freq=4.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.24009174 = fieldWeight in 5787, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5787)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This study considers the expressiveness (that is the expressive power or expressivity) of different types of Knowledge Organization Systems (KOS) and discusses its potential to be machine-processable in the context of the Semantic Web. For this purpose, the theoretical foundations of KOS are reviewed based on conceptualizations introduced by the Functional Requirements for Subject Authority Data (FRSAD) and the Simple Knowledge Organization System (SKOS); natural language processing techniques are also implemented. Applying a comparative analysis, the dataset comprises a thesaurus (Eurovoc), a subject headings system (LCSH) and a classification scheme (DDC). These are compared with an ontology (CIDOC-CRM) by focusing on how they define and handle concepts and relations. It was observed that LCSH and DDC focus on the formalism of character strings (nomens) rather than on the modelling of semantics; their definition of what constitutes a concept is quite fuzzy, and they comprise a large number of complex concepts. By contrast, thesauri have a coherent definition of what constitutes a concept, and apply a systematic approach to the modelling of relations. Ontologies explicitly define diverse types of relations, and are by their nature machine-processable. The paper concludes that the potential of both the expressiveness and machine processability of each KOS is extensively regulated by its structural rules. It is harder to represent subject headings and classification schemes as semantic networks with nodes and arcs, while thesauri are more suitable for such a representation. In addition, a paradigm shift is revealed which focuses on the modelling of relations between concepts, rather than the concepts themselves.

0.0068065543 = product of:
  0.013613109 = sum of:
    0.013613109 = product of:
      0.027226217 = sum of:
        0.027226217 = weight(_text_:systems in 5902) [ClassicSimilarity], result of:
          0.027226217 = score(doc=5902,freq=2.0), product of:
            0.16037072 = queryWeight, product of:
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.052184064 = queryNorm
            0.1697705 = fieldWeight in 5902, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.0731742 = idf(docFreq=5561, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5902)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

With networked information access to heterogeneous data sources, the problem of terminology provision and interoperability of controlled vocabulary schemes such as thesauri becomes increasingly urgent. Solutions are needed to improve the performance of full-text retrieval systems and to guide the design of controlled terminology schemes for use in structured data, including metadata. Thesauri are created in different languages, with different scope and points of view and at different levels of abstraction and detail, to accomodate access to a specific group of collections. In any wider search accessing distributed collections, the user would like to start with familiar terminology and let the system find out the correspondences to other terminologies in order to retrieve equivalent results from all addressed collections. This paper investigates possible semantic differences that may hinder the unambiguous mapping and transition from one thesaurus to another. It focusses on the differences of meaning of terms and their relations as intended by their creators for indexing and querying a specific collection, in contrast to methods investigating the statistical relevance of terms for objects in a collection. It develops a notion of optimal mapping, paying particular attention to the intellectual quality of mappings between terms from different vocabularies and to problems of polysemy. Proposals are made to limit the vagueness introduced by the transition from one vocabulary to another. The paper shows ways in which thesaurus creators can improve their methodology to meet the challenges of networked access of distributed collections created under varying conditions. For system implementers, the discussion will lead to a better understanding of the complexity of the problem