Search (8 results, page 1 of 1)

0.004759258 = product of:
  0.019037032 = sum of:
    0.019037032 = weight(_text_:information in 192) [ClassicSimilarity], result of:
      0.019037032 = score(doc=192,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.3103276 = fieldWeight in 192, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.125 = fieldNorm(doc=192)
  0.25 = coord(1/4)

Source

Information processing and management. 28(1992), S.389-405

0.0044618044 = product of:
  0.017847218 = sum of:
    0.017847218 = weight(_text_:information in 4036) [ClassicSimilarity], result of:
      0.017847218 = score(doc=4036,freq=18.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.2909321 = fieldWeight in 4036, product of:
          4.2426405 = tf(freq=18.0), with freq of:
            18.0 = termFreq=18.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4036)
  0.25 = coord(1/4)

Abstract

When searching information in a hypertext is limited to navigation, it is not an easy task, especially when the number of nodes and/or links becomes very large. A query based access mechanism must therefore be provided to complement the navigational tools inherent in hypertext systems. Most mechanisms currently proposed are based on conventional information retrieval models which consider documents as indepent entities, and ignore hypertext links. To promote the use of other information retrieval mechnaisms adapted to hypertext systems, responds to the following questions; how can we integrate information given by hypertext links into an information retrieval scheme; are these hypertext links (and link semantics) clues to the enhancement of retrieval effectiveness; if so, how can we use them. 2 solutions are: using a default weight function based on link tape or assigning the same strength to all link types; or using a specific weight for each particular link, i.e. the level of association or a similarity measure. Proposes an extended vector processing scheme which extracts additional information from hypertext links to enhance retrieval effectiveness. A hypertext based on 2 medium size collections, the CACM and the CISI collection has been built. The hypergraph is composed of explicit links (bibliographic references), computed links based on bibliographic information, or on hypertext links established according to document representatives (nearest neighbour)

Source

Information processing and management. 32(1996) no.2, S.155-170

0.004121639 = product of:
  0.016486555 = sum of:
    0.016486555 = weight(_text_:information in 757) [ClassicSimilarity], result of:
      0.016486555 = score(doc=757,freq=6.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.2687516 = fieldWeight in 757, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0625 = fieldNorm(doc=757)
  0.25 = coord(1/4)

Abstract

Hypertext may represent a new paradigm capable of exploring legal sources within which links are established according to pertinent relationships found between statute texts and case law. However, to discover relvant information in such a network, a browsing mechanism is not enough when faced with a large column of texts. Describes a new retrieval model where documents are represented according to both their content and relationship with other sources of information

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 4452) [ClassicSimilarity], result of:
      0.013461215 = score(doc=4452,freq=4.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 4452, 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=4452)
  0.25 = coord(1/4)

Abstract

The emphasis in most hypertext systems is on the navigational methods, rather than on the global document retrieval mechanisms. When a search mechanism is provided, it is often restricted to simple string matching or to the Boolean model (as an alternate method). proposes a retrieval mechanism using Bayesian inference networks. The main contribution of this approach is the automatic construction of this network using the expected mutual information measure to build the inference tree, and using Jaccard's formula to define fixed conditional probability relationships

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 6511) [ClassicSimilarity], result of:
      0.013461215 = score(doc=6511,freq=4.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 6511, 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=6511)
  0.25 = coord(1/4)

Abstract

In most hypertext systems, information retrieval techniques emphasize browsing or navigational methods which are not thorough enough to find all relevant material, especially when the number of nodes and/or links becomes very large. Reviews the main query-based search techniques currently used in hypertext environments. Explains the experimental methodology. Concentrates on the retrieval effectiveness of these retrieval strategies. Considers ways of improving search effectiveness

0.0033653039 = product of:
  0.013461215 = sum of:
    0.013461215 = weight(_text_:information in 7292) [ClassicSimilarity], result of:
      0.013461215 = score(doc=7292,freq=4.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.21943474 = fieldWeight in 7292, 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=7292)
  0.25 = coord(1/4)

Source

Information processing and management. 30(1994) no.4, S.515-533

0.0025760243 = product of:
  0.010304097 = sum of:
    0.010304097 = weight(_text_:information in 1427) [ClassicSimilarity], result of:
      0.010304097 = score(doc=1427,freq=6.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.16796975 = fieldWeight in 1427, product of:
          2.4494898 = tf(freq=6.0), with freq of:
            6.0 = termFreq=6.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=1427)
  0.25 = coord(1/4)

Abstract

Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information an the ever-increasing World Wide Web. In that respect, different strategies have been suggested to take hypertext links into account. For example, hyperlinks have been used to (1) enhance document representation, (2) improve document ranking by propagating document score, (3) provide an indicator of popularity, and (4) find hubs and authorities for a given topic. Although the TREC experiments have not demonstrated the usefulness of hyperlinks for retrieval, the hypertext structure is nevertheless an essential aspect of the Web, and as such, should not be ignored. The development of abstract models of the IR task was a key factor to the improvement of search engines. However, at this time conceptual tools for modeling the hypertext retrieval task are lacking, making it difficult to compare, improve, and reason an the existing techniques. This article proposes a general model for using hyperlinks based an Probabilistic Argumentation Systems, in which each of the above-mentioned techniques can be stated. This model will allow to discover some inconsistencies in the mentioned techniques, and to take a higher level and systematic approach for using hyperlinks for retrieval.

Footnote

Beitrag eines Themenheftes: Mathematical, logical, and formal methods in information retrieval

Source

Journal of the American Society for Information Science and technology. 54(2003) no.4, S.347-355

0.0020821756 = product of:
  0.008328702 = sum of:
    0.008328702 = weight(_text_:information in 7254) [ClassicSimilarity], result of:
      0.008328702 = score(doc=7254,freq=2.0), product of:
        0.06134496 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.034944877 = queryNorm
        0.13576832 = fieldWeight in 7254, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=7254)
  0.25 = coord(1/4)