Search (5 results, page 1 of 1)

0.0030444188 = product of:
  0.0060888375 = sum of:
    0.0060888375 = product of:
      0.012177675 = sum of:
        0.012177675 = weight(_text_:a in 894) [ClassicSimilarity], result of:
          0.012177675 = score(doc=894,freq=18.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.22931081 = fieldWeight in 894, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=894)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Several authors emphasize the need for a change in classification theory due to the influence of a dogmatic and monistic ontology supported by an outdated essentialism. These claims tend to focus on the fallibility of knowledge, the need for a pluralistic view, and the theoretical burden of observations. Regardless of the legitimacy of these concerns, there is the risk, when not moderate, to fall into the opposite relativistic extreme. Based on a narrative review of the literature, we aim to reflectively discuss the theoretical foundations that can serve as a basis for a realist position supporting pluralistic ontological classifications. The goal is to show that, against rather conventional solutions, objective scientific-based approaches to natural classifications are presented to be viable, allowing a proper distinction between ontological and taxonomic questions. Supported by critical scientific realism, we consider that such an approach is suitable for the development of ontological Knowledge Organization Systems (KOS). We believe that ontological perspectivism can provide the necessary adaptation to the different granularities of reality.

Type

a

0.0024392908 = product of:
  0.0048785815 = sum of:
    0.0048785815 = product of:
      0.009757163 = sum of:
        0.009757163 = weight(_text_:a in 311) [ClassicSimilarity], result of:
          0.009757163 = score(doc=311,freq=26.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.18373153 = fieldWeight in 311, product of:
              5.0990195 = tf(freq=26.0), with freq of:
                26.0 = termFreq=26.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.03125 = fieldNorm(doc=311)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

This paper looks at Simple Knowledge Organization System (SKOS) to investigate how a faceted classification can be expressed in RDF and shared on the Semantic Web. Statement of the Problem Faceted classification outlines facets as well as subfacets and facet values. Hierarchical relationships and associative relationships are established in a faceted classification. RDF is used to describe how a specific URI has a relationship to a facet value. Not only does RDF decompose "information into pieces," but by incorporating facet values RDF also given the URI the hierarchical and associative relationships expressed in the faceted classification. Combining faceted classification and RDF creates more knowledge than if the two stood alone. An application understands the subjectpredicate-object relationship in RDF and can display hierarchical and associative relationships based on the object (facet) value. This paper continues to investigate if the above idea is indeed useful, used, and applicable. If so, how can a faceted classification be expressed in RDF? What would this expression look like? Literature Review This paper used the same articles as the paper A Survey of Faceted Classification: History, Uses, Drawbacks and the Semantic Web (Putkey, 2010). In that paper, appropriate resources were discovered by searching in various databases for "faceted classification" and "faceted search," either in the descriptor or title fields. Citations were also followed to find more articles as well as searching the Internet for the same terms. To retrieve the documents about RDF, searches combined "faceted classification" and "RDF, " looking for these words in either the descriptor or title.
Methodology Based on information from research papers, more research was done on SKOS and examples of SKOS and shared faceted classifications in the Semantic Web and about SKOS and how to express SKOS in RDF/XML. Once confident with these ideas, the author used a faceted taxonomy created in a Vocabulary Design class and encoded it using SKOS. Instead of writing RDF in a program such as Notepad, a thesaurus tool was used to create the taxonomy according to SKOS standards and then export the thesaurus in RDF/XML format. These processes and tools are then analyzed. Results The initial statement of the problem was simply an extension of the survey paper done earlier in this class. To continue on with the research, more research was done into SKOS - a standard for expressing thesauri, taxonomies and faceted classifications so they can be shared on the semantic web.

Type

a

0.0020714647 = product of:
  0.0041429293 = sum of:
    0.0041429293 = product of:
      0.008285859 = sum of:
        0.008285859 = weight(_text_:a in 3869) [ClassicSimilarity], result of:
          0.008285859 = score(doc=3869,freq=12.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.15602624 = fieldWeight in 3869, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3869)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

The changes in KO systems induced by sociocultural influences may include those in both classificatory principles and cultural features. The proposed study will examine the Korean Decimal Classification (KDC)'s adaptation of the Dewey Decimal Classification (DDC) by comparing the two systems. This case manifests the sociocultural influences on KOSs in a cross-cultural context. Therefore, the study aims at an in-depth investigation of sociocultural influences by situating a KOS in a cross-cultural environment and examining the dynamics between two classification systems designed to organize information resources in two distinct sociocultural contexts. As a preceding stage of the comparison, the analysis was conducted on the changes that result from the meeting of different sociocultural feature in a descriptive method. The analysis aims to identify variations between the two schemes in comparison of the knowledge structures of the two classifications, in terms of the quantity of class numbers that represent concepts and their relationships in each of the individual main classes. The most effective analytic strategy to show the patterns of the comparison was visualizations of similarities and differences between the two systems. Increasing or decreasing tendencies in the class through various editions were analyzed. Comparing the compositions of the main classes and distributions of concepts in the KDC and DDC discloses the differences in their knowledge structures empirically. This phase of quantitative analysis and visualizing techniques generates empirical evidence leading to interpretation.

Type

a

0.0016913437 = product of:
  0.0033826875 = sum of:
    0.0033826875 = product of:
      0.006765375 = sum of:
        0.006765375 = weight(_text_:a in 3183) [ClassicSimilarity], result of:
          0.006765375 = score(doc=3183,freq=8.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.12739488 = fieldWeight in 3183, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=3183)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Division is obviously important to Knowledge Organization. Typically, an organizational infrastructure might acknowledge three types of connecting relationships: class hierarchies, where some classes are subclasses of others, partitive hierarchies, where some items are parts of others, and instantiation, where some items are members of some classes (see Z39.19 ANSI/NISO 2005 as an example). The first two of these involve division (the third, instantiation, does not involve division). Logical division would usually be a part of hierarchical classification systems, which, in turn, are central to shelving in libraries, to subject classification schemes, to controlled vocabularies, and to thesauri. Partitive hierarchies, and partitive division, are often essential to controlled vocabularies, thesauri, and subject tagging systems. Partitive hierarchies also relate to the bearers of information; for example, a journal would typically have its component articles as parts and, in turn, they might have sections as their parts, and, of course, components might be arrived at by partitive division (see Tillett 2009 as an illustration). Finally, verbal division, disambiguating homographs, is basic to controlled vocabularies. Thus Division is a broad and relevant topic. This article, though, is going to focus on Logical Division.

Type

a

0.001353075 = product of:
  0.00270615 = sum of:
    0.00270615 = product of:
      0.0054123 = sum of:
        0.0054123 = weight(_text_:a in 675) [ClassicSimilarity], result of:
          0.0054123 = score(doc=675,freq=2.0), product of:
            0.053105544 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046056706 = queryNorm
            0.10191591 = fieldWeight in 675, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=675)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Type

a