Search (2 results, page 1 of 1)

  • × year_i:[2020 TO 2030}
  • × author_ss:"Szostak, R."
  1. Szostak, R.: Basic Concepts Classification (BCC) (2020) 0.00
    0.0014647468 = product of:
      0.0029294936 = sum of:
        0.0029294936 = product of:
          0.005858987 = sum of:
            0.005858987 = weight(_text_:a in 5883) [ClassicSimilarity], result of:
              0.005858987 = score(doc=5883,freq=6.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.11032722 = fieldWeight in 5883, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5883)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Abstract
    The Basics Concept Classification (BCC) is a "universal" scheme: it attempts to encompass all areas of human understanding. Whereas most universal schemes are organized around scholarly disciplines, the BCC is instead organized around phenomena (things), the relationships that exist among phenomena, and the properties that phenomena and relators may possess. This structure allows the BCC to apply facet analysis without requiring the use of "facet indicators." The main motivation for the BCC was a recognition that existing classifications that are organized around disciplines serve interdisciplinary scholarship poorly. Complex concepts that might be understood quite differently across groups and individuals can generally be broken into basic concepts for which there is enough shared understanding for the purposes of classification. Documents, ideas, and objects are classified synthetically by combining entries from the schedules of phenomena, relators, and properties. The inclusion of separate schedules of-generally verb-like-relators is one of the most unusual aspects of the BCC. This (and the schedules of properties that serve as adjectives or adverbs) allows the production of sentence-like subject strings. Documents can then be classified in terms of the main arguments made in the document. BCC provides very precise descriptors of documents by combining phenomena, relators, and properties synthetically. The terminology employed in the BCC reduces terminological ambiguity. The BCC is still being developed and it needs to be fleshed out in certain respects. Yet it also needs to be applied; only in application can the feasibility and desirability of the classification be adequately assessed.
    Type
    a
  2. Szostak, R.; Lee, D.: Classifying musical genres : building musical form and genre into BCC: repurposing LCGFT terms for music into the Basic Concepts Classification (2022) 0.00
    0.001353075 = product of:
      0.00270615 = sum of:
        0.00270615 = product of:
          0.0054123 = sum of:
            0.0054123 = weight(_text_:a in 227) [ClassicSimilarity], result of:
              0.0054123 = score(doc=227,freq=2.0), product of:
                0.053105544 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.046056706 = queryNorm
                0.10191591 = fieldWeight in 227, 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=227)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Type
    a