Search (3 results, page 1 of 1)

  • × author_ss:"Das, S."
  • × year_i:[2020 TO 2030}
  1. Das, S.; Paik, J.H.: Gender tagging of named entities using retrieval-assisted multi-context aggregation : an unsupervised approach (2023) 0.01 
    0.0067315903 = product of:
  0.02019477 = sum of:
    0.02019477 = product of:
      0.04038954 = sum of:
        0.04038954 = weight(_text_:22 in 941) [ClassicSimilarity], result of:
          0.04038954 = score(doc=941,freq=2.0), product of:
            0.17398734 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049684696 = queryNorm
            0.23214069 = fieldWeight in 941, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.046875 = fieldNorm(doc=941)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Date
    22. 3.2023 12:00:14
  2. Das, S.; Bagchi, M.; Hussey, P.: How to teach domain ontology-based knowledge graph construction? : an Irish experiment (2023) 0.01 
    0.005609659 = product of:
  0.016828977 = sum of:
    0.016828977 = product of:
      0.033657953 = sum of:
        0.033657953 = weight(_text_:22 in 1126) [ClassicSimilarity], result of:
          0.033657953 = score(doc=1126,freq=2.0), product of:
            0.17398734 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.049684696 = queryNorm
            0.19345059 = fieldWeight in 1126, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1126)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Date
    20.11.2023 17:19:22
  3. Das, S.; Naskar, D.; Roy, S.: Reorganizing educational institutional domain using faceted ontological principles (2022) 0.01 
    0.00536229 = product of:
  0.016086869 = sum of:
    0.016086869 = product of:
      0.032173738 = sum of:
        0.032173738 = weight(_text_:indexing in 1098) [ClassicSimilarity], result of:
          0.032173738 = score(doc=1098,freq=2.0), product of:
            0.19018644 = queryWeight, product of:
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.049684696 = queryNorm
            0.16916946 = fieldWeight in 1098, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.8278677 = idf(docFreq=2614, maxDocs=44218)
              0.03125 = fieldNorm(doc=1098)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    The purpose of this work is to find out how different library classification systems and linguistic ontologies arrange a particular domain of interest and what are the limitations for information retrieval. We use knowledge representation techniques and languages for construction of a domain specific ontology. This ontology would help not only in problem solving, but it would demonstrate the ease with which complex queries can be handled using principles of domain ontology, thereby facilitating better information retrieval. Facet-based methodology has been used for ontology formalization for quite some time. Ontology formalization involves different steps such as, Identification of the terminology, Analysis, Synthesis, Standardization and Ordering. Firstly, for purposes of conceptualization OntoUML has been used which is a well-founded and established language for Ontology driven Conceptual Modelling. Phase transformation of "the same mode" has been subsequently obtained by OWL-DL using Protégé software. The final OWL ontology contains a total of around 232 axioms. These axioms comprise 148 logical axioms, 76 declaration axioms and 43 classes. These axioms glue together classes, properties and data types as well as a constraint. Such data clustering cannot be achieved through general use of simple classification schemes. Hence it has been observed and established that domain ontology using faceted principles provide better information retrieval with enhanced precision. This ontology should be seen not only as an alternative of the existing classification system but as a Knowledge Base (KB) system which can handle complex queries well, which is the ultimate purpose of any classification system or indexing system. In this paper, we try to understand how ontology-based information retrieval systems can prove its utility as a useful tool in the field of library science with a particular focus on the education domain.

Authors

Themes