Search (3 results, page 1 of 1)

  • × author_ss:"Sembok, T.M.T."
  • × theme_ss:"Computerlinguistik"
  1. Sembok, T.M.T.; Rijsbergen, C.J. van: SILOL: a simple logical-linguistic document retrieval system (1990) 0.01
    0.00906473 = product of:
      0.022661826 = sum of:
        0.016346768 = weight(_text_:a in 6684) [ClassicSimilarity], result of:
          0.016346768 = score(doc=6684,freq=18.0), product of:
            0.053464882 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046368346 = queryNorm
            0.30574775 = fieldWeight in 6684, product of:
              4.2426405 = tf(freq=18.0), with freq of:
                18.0 = termFreq=18.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=6684)
        0.006315058 = product of:
          0.012630116 = sum of:
            0.012630116 = weight(_text_:information in 6684) [ClassicSimilarity], result of:
              0.012630116 = score(doc=6684,freq=2.0), product of:
                0.08139861 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046368346 = queryNorm
                0.1551638 = fieldWeight in 6684, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0625 = fieldNorm(doc=6684)
          0.5 = coord(1/2)
      0.4 = coord(2/5)
    
    Abstract
    Describes a system called SILOL which is based on a logical-linguistic model of document retrieval systems. SILOL uses a shallow semantic translation of natural language texts into a first order predicate representation in performing a document indexing and retrieval process. Some preliminary experiments have been carried out to test the retrieval effectiveness of this system. The results obtained show improvements in the level of retrieval effectiveness, which demonstrate that the approach of using a semantic theory of natural language and logic in document retrieval systems is a valid one
    Source
    Information processing and management. 26(1990) no.1, S.111-134
    Type
    a
  2. Ahmad, F.; Yusoff, M.; Sembok, T.M.T.: Experiments with a stemming algorithm for Malay words (1996) 0.01
    0.0073474604 = product of:
      0.01836865 = sum of:
        0.009437811 = weight(_text_:a in 6504) [ClassicSimilarity], result of:
          0.009437811 = score(doc=6504,freq=6.0), product of:
            0.053464882 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046368346 = queryNorm
            0.17652355 = fieldWeight in 6504, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0625 = fieldNorm(doc=6504)
        0.0089308405 = product of:
          0.017861681 = sum of:
            0.017861681 = weight(_text_:information in 6504) [ClassicSimilarity], result of:
              0.017861681 = score(doc=6504,freq=4.0), product of:
                0.08139861 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046368346 = queryNorm
                0.21943474 = fieldWeight in 6504, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.0625 = fieldNorm(doc=6504)
          0.5 = coord(1/2)
      0.4 = coord(2/5)
    
    Abstract
    Stemming is used in information retrieval systems to reduce variant word forms to common roots in order to improve retrieval effectiveness. As in other languages, there is a need for an effective stemming algorithm for the indexing and retrieval of Malay documents. The Malay stemming algorithm developed by Othman is studied and new versions proposed to enhance its performance. The improvements relate to the order in which the dictionary id looked-up, the order in which the morphological rules are applied, and the number of rules
    Source
    Journal of the American Society for Information Science. 47(1996) no.12, S.909-918
    Type
    a
  3. Bakar, Z.A.; Sembok, T.M.T.; Yusoff, M.: ¬An evaluation of retrieval effectiveness using spelling-correction and string-similarity matching methods on Malay texts (2000) 0.01
    0.0051638708 = product of:
      0.012909677 = sum of:
        0.008173384 = weight(_text_:a in 4804) [ClassicSimilarity], result of:
          0.008173384 = score(doc=4804,freq=8.0), product of:
            0.053464882 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046368346 = queryNorm
            0.15287387 = fieldWeight in 4804, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=4804)
        0.0047362936 = product of:
          0.009472587 = sum of:
            0.009472587 = weight(_text_:information in 4804) [ClassicSimilarity], result of:
              0.009472587 = score(doc=4804,freq=2.0), product of:
                0.08139861 = queryWeight, product of:
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046368346 = queryNorm
                0.116372846 = fieldWeight in 4804, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  1.7554779 = idf(docFreq=20772, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4804)
          0.5 = coord(1/2)
      0.4 = coord(2/5)
    
    Abstract
    This article evaluates the effectiveness of spelling-correction and string-similarity matching methods in retrieving similar words in a Maly dictionary associated with a set of query words. The spelling-correction techniques used are SPEEDCOP, Soundex, Davidson, Phonic, and Hartlib. 2 dynamic-programming methods that measure longest common subsequence and edit-cost-distance are used. Several search combinations od query and doctionary words are performed in the experiments, the best being one that stems both query and dictionary words using an existing Malay stemming algorithm. the retrieval effectivness (E) and retrieved and relevant (R&R) mean measure are calculated from weighted combination of recall and precision values. Results from these experiments are then compared with available diagram, a string-similarity method. The best R&R and E results are given by using diagram. Editcost-distances produce the best E results, and both dynamic-programming methods rank second in finding R&R mean measures
    Source
    Journal of the American Society for Information Science. 51(2000) no.8, S.691-706
    Type
    a