Search (1 results, page 1 of 1)

  • × subject_ss:"Semantic Web."
  • × subject_ss:"Ontologies (Information retrieval)"
  1. Lu, J.; Xu, Q.: Ontologies and big data considerations for effective intelligence (2017) 0.03
    0.03217734 = product of:
      0.04826601 = sum of:
        0.030111905 = weight(_text_:resources in 3468) [ClassicSimilarity], result of:
          0.030111905 = score(doc=3468,freq=2.0), product of:
            0.18665522 = queryWeight, product of:
              3.650338 = idf(docFreq=3122, maxDocs=44218)
              0.051133685 = queryNorm
            0.16132367 = fieldWeight in 3468, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.650338 = idf(docFreq=3122, maxDocs=44218)
              0.03125 = fieldNorm(doc=3468)
        0.018154101 = product of:
          0.036308203 = sum of:
            0.036308203 = weight(_text_:management in 3468) [ClassicSimilarity], result of:
              0.036308203 = score(doc=3468,freq=4.0), product of:
                0.17235184 = queryWeight, product of:
                  3.3706124 = idf(docFreq=4130, maxDocs=44218)
                  0.051133685 = queryNorm
                0.21066327 = fieldWeight in 3468, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.3706124 = idf(docFreq=4130, maxDocs=44218)
                  0.03125 = fieldNorm(doc=3468)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Abstract
    Ontologies and Big Data Considerations for Effective Intelligence is a key source on the latest advancements in multidisciplinary research methods and applications and examines effective techniques for managing and utilizing information resources. Featuring extensive coverage across a range of relevant perspectives and topics, such as visual analytics, spatial databases, retrieval systems, and ontology models, this book is ideally designed for researchers, graduate students, academics, and industry professionals seeking ways to optimize knowledge management processes.
    Series
    Advances in information quality and management (AIQM) book series