Search (10 results, page 1 of 1)

0.117611334 = product of:
  0.176417 = sum of:
    0.15274209 = weight(_text_:book in 7920) [ClassicSimilarity], result of:
      0.15274209 = score(doc=7920,freq=8.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.68277526 = fieldWeight in 7920, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7920)
    0.0236749 = product of:
      0.0473498 = sum of:
        0.0473498 = weight(_text_:search in 7920) [ClassicSimilarity], result of:
          0.0473498 = score(doc=7920,freq=2.0), product of:
            0.17614716 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.050679956 = queryNorm
            0.2688082 = fieldWeight in 7920, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0546875 = fieldNorm(doc=7920)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Part of a larger study which aims to: empirically investigate book-index usage, behaviours, and the extent to which specific print index features affect a user's search for information; and to examine these features in an electronic environment and to determine the optimum specifications for indexes in electronic texts by gathering evidence from a controlled user study. Provides an overview of the research project, focusing on a subset of the results from the study of hard-copy book indexes. Describes observable behaviours of a sample of users when consulting different variations of a hard copy book index. Suggests a preliminary model at 3 levels of abstraction repressing users' behaviours when using a book index

0.0666973 = product of:
  0.10004594 = sum of:
    0.076371044 = weight(_text_:book in 8500) [ClassicSimilarity], result of:
      0.076371044 = score(doc=8500,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.34138763 = fieldWeight in 8500, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.0546875 = fieldNorm(doc=8500)
    0.0236749 = product of:
      0.0473498 = sum of:
        0.0473498 = weight(_text_:search in 8500) [ClassicSimilarity], result of:
          0.0473498 = score(doc=8500,freq=2.0), product of:
            0.17614716 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.050679956 = queryNorm
            0.2688082 = fieldWeight in 8500, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0546875 = fieldNorm(doc=8500)
      0.5 = coord(1/2)
  0.6666667 = coord(2/3)

Abstract

Gives an overview of a research project which had aimed to: empirically investigate book-index usage behaviours and the extent to which specific print index features affect a user's search for information; and to examine these same features in an electronic environment. Aims to determine the optimum specifications for indexes in electronic texts by gathering evidence from a controlled user study. Presents a subset of results from index use in both print and electronic formats. Suggests a preliminay model representing users' behaviours when using an index and suggests implications for system design

0.058187462 = product of:
  0.17456238 = sum of:
    0.17456238 = weight(_text_:book in 7768) [ClassicSimilarity], result of:
      0.17456238 = score(doc=7768,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.78031456 = fieldWeight in 7768, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.125 = fieldNorm(doc=7768)
  0.33333334 = coord(1/3)

0.0436406 = product of:
  0.1309218 = sum of:
    0.1309218 = weight(_text_:book in 7764) [ClassicSimilarity], result of:
      0.1309218 = score(doc=7764,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.58523595 = fieldWeight in 7764, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.09375 = fieldNorm(doc=7764)
  0.33333334 = coord(1/3)

0.036367163 = product of:
  0.10910148 = sum of:
    0.10910148 = weight(_text_:book in 6357) [ClassicSimilarity], result of:
      0.10910148 = score(doc=6357,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.4876966 = fieldWeight in 6357, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.078125 = fieldNorm(doc=6357)
  0.33333334 = coord(1/3)

0.036367163 = product of:
  0.10910148 = sum of:
    0.10910148 = weight(_text_:book in 6855) [ClassicSimilarity], result of:
      0.10910148 = score(doc=6855,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.4876966 = fieldWeight in 6855, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.078125 = fieldNorm(doc=6855)
  0.33333334 = coord(1/3)

0.029093731 = product of:
  0.08728119 = sum of:
    0.08728119 = weight(_text_:book in 3854) [ClassicSimilarity], result of:
      0.08728119 = score(doc=3854,freq=2.0), product of:
        0.2237077 = queryWeight, product of:
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.050679956 = queryNorm
        0.39015728 = fieldWeight in 3854, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          4.414126 = idf(docFreq=1454, maxDocs=44218)
          0.0625 = fieldNorm(doc=3854)
  0.33333334 = coord(1/3)

Footnote

Vgl.: http://www.tandfonline.com/doi/book/10.1081/E-ELIS3.

0.016568977 = product of:
  0.04970693 = sum of:
    0.04970693 = product of:
      0.09941386 = sum of:
        0.09941386 = weight(_text_:search in 3564) [ClassicSimilarity], result of:
          0.09941386 = score(doc=3564,freq=12.0), product of:
            0.17614716 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.050679956 = queryNorm
            0.5643796 = fieldWeight in 3564, product of:
              3.4641016 = tf(freq=12.0), with freq of:
                12.0 = termFreq=12.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.046875 = fieldNorm(doc=3564)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Query formation and expansion is an integral part of nearly every effort to search for information. In the work reported here we investigate the effects of domain knowledge and feedback an search term selection and reformation. We explore differences between experts and novices as they generate search terms over 10 successive trials and under two feedback conditions. Search attempts were coded an quantitative dimensions such as the number of unique terms and average time per trial, and as a whole in an attempt to characterize the user's conceptual map for the topic under differing conditions of participant-defined domain expertise. Nine distinct strategies were identified. Differences emerged as a function of both expertise and feedback. In addition, strategic behavior varied depending an prior search conditions. The results are considered from both a theoretical and design perspective, and have direct implications for digital library usability and metadata generation, and query expansion systems.

0.00801084 = product of:
  0.02403252 = sum of:
    0.02403252 = product of:
      0.04806504 = sum of:
        0.04806504 = weight(_text_:22 in 2345) [ClassicSimilarity], result of:
          0.04806504 = score(doc=2345,freq=2.0), product of:
            0.17747258 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050679956 = queryNorm
            0.2708308 = fieldWeight in 2345, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2345)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 9.1997 19:16:05

0.006764257 = product of:
  0.02029277 = sum of:
    0.02029277 = product of:
      0.04058554 = sum of:
        0.04058554 = weight(_text_:search in 7813) [ClassicSimilarity], result of:
          0.04058554 = score(doc=7813,freq=2.0), product of:
            0.17614716 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.050679956 = queryNorm
            0.230407 = fieldWeight in 7813, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.046875 = fieldNorm(doc=7813)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

Describes an alternative method of representation for documents and queries in information retrieval systems to the 2 most common methods: free text, natural language representation and controlled language representation. The alternative method combines the advantage of both traditional approaches and overcomes the difficulties associated with each. The scheme was developed for use with Longman's Dictionary of Contemporary English and uses a computerized version of the dictionary for the automatic generation of summary level semantic representations of each document and query. The system tags each word in a document with the appropriate Subject Field Code (SFC) from the dictionary and the SFCs are summed and normalized to produce a weighted, fixed length vector of the SFC. The search system matches the query SFC vector to the document SFC vectors in the database. The documents are then ranked on the basis of their vector's similarity to the query