Search (1 results, page 1 of 1)

  • × author_ss:"Hooland, S. van"
  • × author_ss:"Hubain, R."
  • × theme_ss:"Semantische Interoperabilität"
  1. Hubain, R.; Wilde, M. De; Hooland, S. van: Automated SKOS vocabulary design for the biopharmaceutical industry (2016) 0.00
    8.2263234E-4 = product of:
      0.0032905294 = sum of:
        0.0032905294 = product of:
          0.009871588 = sum of:
            0.009871588 = weight(_text_:a in 5132) [ClassicSimilarity], result of:
              0.009871588 = score(doc=5132,freq=8.0), product of:
                0.055348642 = queryWeight, product of:
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.04800207 = queryNorm
                0.17835285 = fieldWeight in 5132, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  1.153047 = idf(docFreq=37942, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=5132)
          0.33333334 = coord(1/3)
      0.25 = coord(1/4)
    
    Abstract
    Ensuring quick and consistent access to large collections of unstructured documents is one of the biggest challenges facing knowledge-intensive organizations. Designing specific vocabularies to index and retrieve documents is often deemed too expensive, full-text search being preferred despite its known limitations. However, the process of creating controlled vocabularies can be partly automated thanks to natural language processing and machine learning techniques. With a case study from the biopharmaceutical industry, we demonstrate how small organizations can use an automated workflow in order to create a controlled vocabulary to index unstructured documents in a semantically meaningful way.
    Type
    a