Search (2 results, page 1 of 1)

  • × author_ss:"Robertson, S.E."
  • × language_ss:"e"
  • × theme_ss:"Computerlinguistik"
  1. Robertson, S.E.; Sparck Jones, K.: Relevance weighting of search terms (1976) 0.02
    0.020541014 = product of:
      0.03081152 = sum of:
        0.014795236 = weight(_text_:in in 71) [ClassicSimilarity], result of:
          0.014795236 = score(doc=71,freq=6.0), product of:
            0.07104705 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.052230705 = queryNorm
            0.2082456 = fieldWeight in 71, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.0625 = fieldNorm(doc=71)
        0.016016284 = product of:
          0.032032568 = sum of:
            0.032032568 = weight(_text_:science in 71) [ClassicSimilarity], result of:
              0.032032568 = score(doc=71,freq=2.0), product of:
                0.1375819 = queryWeight, product of:
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.052230705 = queryNorm
                0.23282544 = fieldWeight in 71, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.6341193 = idf(docFreq=8627, maxDocs=44218)
                  0.0625 = fieldNorm(doc=71)
          0.5 = coord(1/2)
      0.6666667 = coord(2/3)
    
    Abstract
    Examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general. A series of relevance weighting functions is derived and is justified by theoretical considerations. In particular, it is shown that specific weighted search methods are implied by a general probabilistic theory of retrieval. Different applications of relevance weighting are illustrated by experimental results for test collections
    Source
    Journal of the American Society for Information Science. 27(1976), S.129-146
  2. Vechtomova, O.; Karamuftuoglum, M.; Robertson, S.E.: On document relevance and lexical cohesion between query terms (2006) 0.01
    0.0056500244 = product of:
      0.016950073 = sum of:
        0.016950073 = weight(_text_:in in 987) [ClassicSimilarity], result of:
          0.016950073 = score(doc=987,freq=14.0), product of:
            0.07104705 = queryWeight, product of:
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.052230705 = queryNorm
            0.23857531 = fieldWeight in 987, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.3602545 = idf(docFreq=30841, maxDocs=44218)
              0.046875 = fieldNorm(doc=987)
      0.33333334 = coord(1/3)
    
    Abstract
    Lexical cohesion is a property of text, achieved through lexical-semantic relations between words in text. Most information retrieval systems make use of lexical relations in text only to a limited extent. In this paper we empirically investigate whether the degree of lexical cohesion between the contexts of query terms' occurrences in a document is related to its relevance to the query. Lexical cohesion between distinct query terms in a document is estimated on the basis of the lexical-semantic relations (repetition, synonymy, hyponymy and sibling) that exist between there collocates - words that co-occur with them in the same windows of text. Experiments suggest significant differences between the lexical cohesion in relevant and non-relevant document sets exist. A document ranking method based on lexical cohesion shows some performance improvements.