Search (2 results, page 1 of 1)

  • × author_ss:"Huang, S.-L."
  1. Huang, S.-L.; Lin, S.-C.; Chan, Y.-C.: Investigating effectiveness and user acceptance of semantic social tagging for knowledge sharing (2012) 0.00 
    0.0033478998 = product of:
  0.010043699 = sum of:
    0.010043699 = product of:
      0.020087399 = sum of:
        0.020087399 = weight(_text_:of in 2732) [ClassicSimilarity], result of:
          0.020087399 = score(doc=2732,freq=16.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2932045 = fieldWeight in 2732, product of:
              4.0 = tf(freq=16.0), with freq of:
                16.0 = termFreq=16.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=2732)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    Social tagging systems enable users to assign arbitrary tags to various digital resources. However, they face vague-meaning problems when users retrieve or present resources with the keyword-based tags. In order to solve these problems, this study takes advantage of Semantic Web technology and the topological characteristics of knowledge maps to develop a system that comprises a semantic tagging mechanism and triple-pattern and visual searching mechanisms. A field experiment was conducted to evaluate the effectiveness and user acceptance of these mechanisms in a knowledge sharing context. The results show that the semantic social tagging system is more effective than a keyword-based system. The visualized knowledge map helps users capture an overview of the knowledge domain, reduce cognitive effort for the search, and obtain more enjoyment. Traditional keyword tagging with a keyword search still has the advantage of ease of use and the users had higher intention to use it. This study also proposes directions for future development of semantic social tagging systems.
  2. Huang, S.-L.: ¬The conceptual model of computer aided Chinese classification system (1997) 0.00 
    0.0031316737 = product of:
  0.009395021 = sum of:
    0.009395021 = product of:
      0.018790042 = sum of:
        0.018790042 = weight(_text_:of in 1807) [ClassicSimilarity], result of:
          0.018790042 = score(doc=1807,freq=14.0), product of:
            0.06850986 = queryWeight, product of:
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.043811057 = queryNorm
            0.2742677 = fieldWeight in 1807, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.5637573 = idf(docFreq=25162, maxDocs=44218)
              0.046875 = fieldNorm(doc=1807)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)
    Abstract
    In a prototype model of a computer aided Chinese classification system, 4 different modules were included: the keyword searching type, user's predomination type, expert wizard type and versatile type. These 4 modules work in different ways whilst sharing the same concept. The keyword searching type finds the most suitable category by scanning the keywords of all categories in a database; it is useful for entrance level staff. The user's predomination type allows the user to key in the proper category to size down the number of returning data; the user then picks the best category by browsing the built in keywords. This module is suitable for professional librarians. The expert wizard type actively leads the user to choose the best category one by one. The versatile type is a mixture of the other 3 types
    Source
    Bulletin of the Library Association of China. 1997, no.59, Dec., S.65-74

Authors

Years

Languages