Search (2 results, page 1 of 1)

0.01421536 = product of:
  0.02843072 = sum of:
    0.02843072 = product of:
      0.05686144 = sum of:
        0.05686144 = weight(_text_:g in 4684) [ClassicSimilarity], result of:
          0.05686144 = score(doc=4684,freq=2.0), product of:
            0.19574708 = queryWeight, product of:
              3.7559474 = idf(docFreq=2809, maxDocs=44218)
              0.052116565 = queryNorm
            0.29048425 = fieldWeight in 4684, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.7559474 = idf(docFreq=2809, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4684)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Editor

Dean, M. u. G. Schreiber

0.010577417 = product of:
  0.021154834 = sum of:
    0.021154834 = product of:
      0.084619336 = sum of:
        0.084619336 = weight(_text_:authors in 5073) [ClassicSimilarity], result of:
          0.084619336 = score(doc=5073,freq=4.0), product of:
            0.23758973 = queryWeight, product of:
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.052116565 = queryNorm
            0.35615736 = fieldWeight in 5073, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              4.558814 = idf(docFreq=1258, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5073)
      0.25 = coord(1/4)
  0.5 = coord(1/2)

Abstract

As ontologies become common in more applications and as those applications become larger and longer-lived, it is becoming increasingly common for ontologies to be developed in distributed environments by authors with disparate backgrounds. Ontologies that are expected to be collaboratively created and maintained over time by authors in many locations present special challenges to the problem of conceptual modeling. In this paper, we will discuss conceptual modeling issues and focus on those topics with elevated importance in distributed environments. We will draw on our experience creating and maintaining ontologies in differing knowledge representation and reasoning environments over the last decade. Many of our recent observations are drawn from our experiences in the DARPA High Performance Knowledge Base Program. This program generated dozens of knowledge bases authored by people of varying expertise in both knowledge representation and reasoning as well as domain experience. Our efforts in merging the ontologies, loading them for coordinated use, and modifying them to meet evolving needs shape much of the material in this paper. Additional sources of observations are from designing and building a number of e-commerce ontologies (with content merged from multiple sources) and also from a few families of description logic applications including the PROSE/QUESTAR family of configurators and the FindUR knowledge-enhanced search applications