Search (3 results, page 1 of 1)

  • × author_ss:"Chen, L."
  1. Chen, L.; Zeng, J.; Tokuda, N.: ¬A "stereo" document representation for textual information retrieval (2006) 0.00
    0.003154703 = product of:
      0.014196163 = sum of:
        0.009630327 = product of:
          0.02889098 = sum of:
            0.02889098 = weight(_text_:t in 5292) [ClassicSimilarity], result of:
              0.02889098 = score(doc=5292,freq=2.0), product of:
                0.11063053 = queryWeight, product of:
                  3.9394085 = idf(docFreq=2338, maxDocs=44218)
                  0.02808303 = queryNorm
                0.26114836 = fieldWeight in 5292, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.9394085 = idf(docFreq=2338, maxDocs=44218)
                  0.046875 = fieldNorm(doc=5292)
          0.33333334 = coord(1/3)
        0.0045658355 = product of:
          0.022829177 = sum of:
            0.022829177 = weight(_text_:22 in 5292) [ClassicSimilarity], result of:
              0.022829177 = score(doc=5292,freq=2.0), product of:
                0.09834199 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02808303 = queryNorm
                0.23214069 = fieldWeight in 5292, 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=5292)
          0.2 = coord(1/5)
      0.22222222 = coord(2/9)
    
    Abstract
    A new document representation model is presented in this paper. This model is based on the idea of representing a document by two or more pictures of the document taken from different perspectives. It is shown that by applying the stereo representation model, enhanced textual retrieval performance is achieved because the new model improves the capability of capturing individual features of the document. Experiments have been conducted on two standard corpora, TIME and ADI, using the standard term vector method and the latent semantic indexing (LSI) method based upon both the stereo representation model and the traditional representation model. Statistical t-tests on the experimental results have convincingly illustrated that these methods achieve significant improvements in retrieval performances with the stereo representation model over those with the traditional representation model.
    Date
    22. 7.2006 17:33:43
  2. Xie, H.; Li, X.; Wang, T.; Lau, R.Y.K.; Wong, T.-L.; Chen, L.; Wang, F.L.; Li, Q.: Incorporating sentiment into tag-based user profiles and resource profiles for personalized search in folksonomy (2016) 0.00
    0.0010088399 = product of:
      0.00907956 = sum of:
        0.00907956 = product of:
          0.027238678 = sum of:
            0.027238678 = weight(_text_:t in 2671) [ClassicSimilarity], result of:
              0.027238678 = score(doc=2671,freq=4.0), product of:
                0.11063053 = queryWeight, product of:
                  3.9394085 = idf(docFreq=2338, maxDocs=44218)
                  0.02808303 = queryNorm
                0.24621303 = fieldWeight in 2671, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.9394085 = idf(docFreq=2338, maxDocs=44218)
                  0.03125 = fieldNorm(doc=2671)
          0.33333334 = coord(1/3)
      0.11111111 = coord(1/9)
    
  3. Tang, X.; Chen, L.; Cui, J.; Wei, B.: Knowledge representation learning with entity descriptions, hierarchical types, and textual relations (2019) 0.00
    5.0731504E-4 = product of:
      0.0045658355 = sum of:
        0.0045658355 = product of:
          0.022829177 = sum of:
            0.022829177 = weight(_text_:22 in 5101) [ClassicSimilarity], result of:
              0.022829177 = score(doc=5101,freq=2.0), product of:
                0.09834199 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02808303 = queryNorm
                0.23214069 = fieldWeight in 5101, 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=5101)
          0.2 = coord(1/5)
      0.11111111 = coord(1/9)
    
    Date
    17. 3.2019 13:22:53