Search (6 results, page 1 of 1)

0.034684885 = product of:
  0.10405465 = sum of:
    0.10405465 = weight(_text_:objects in 150) [ClassicSimilarity], result of:
      0.10405465 = score(doc=150,freq=2.0), product of:
        0.25313336 = queryWeight, product of:
          5.315071 = idf(docFreq=590, maxDocs=44218)
          0.047625583 = queryNorm
        0.41106653 = fieldWeight in 150, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.315071 = idf(docFreq=590, maxDocs=44218)
          0.0546875 = fieldNorm(doc=150)
  0.33333334 = coord(1/3)

Abstract

Introduces what automatic authoring of a hypertext for information retrieval means. The most difficult part of the automatic construction of a hypertext is the creation of links connecting documents or document fragments that are related. Becaus of this, to many researchers it seemed natural to use information retrieval techniques for this purpose, since information retrieval has always dealt with the construction of relationships between objects mutually relevant. Presents a survey of some of the attempts toward the automatic construction of hypertexts for information retrieval. Identifies and compares scope, advantages and limitations of different approaches. Points out the main and most successful current lines of research

0.034684885 = product of:
  0.10405465 = sum of:
    0.10405465 = weight(_text_:objects in 2860) [ClassicSimilarity], result of:
      0.10405465 = score(doc=2860,freq=2.0), product of:
        0.25313336 = queryWeight, product of:
          5.315071 = idf(docFreq=590, maxDocs=44218)
          0.047625583 = queryNorm
        0.41106653 = fieldWeight in 2860, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          5.315071 = idf(docFreq=590, maxDocs=44218)
          0.0546875 = fieldNorm(doc=2860)
  0.33333334 = coord(1/3)

Abstract

Although retrieval systems based on probabilistic models will rank the objects (e.g., documents) being retrieved according to the probability of some matching criterion (e.g., relevance), they rarely yield an actual probability, and the scoring function is interpreted to be purely ordinal within a given retrieval task. In this brief communication, it is shown that some scoring functions possess the likelihood property, which means that the scoring function indicates the likelihood of matching when compared to other retrieval tasks, which is potentially more useful than pure ranking although it cannot be interpreted as an actual probability. This property can be detected by using two modified effectiveness measures: entire precision and entire recall.

0.02405369 = product of:
  0.07216106 = sum of:
    0.07216106 = product of:
      0.14432213 = sum of:
        0.14432213 = weight(_text_:fusion in 4987) [ClassicSimilarity], result of:
          0.14432213 = score(doc=4987,freq=2.0), product of:
            0.35273543 = queryWeight, product of:
              7.406428 = idf(docFreq=72, maxDocs=44218)
              0.047625583 = queryNorm
            0.4091512 = fieldWeight in 4987, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              7.406428 = idf(docFreq=72, maxDocs=44218)
              0.0390625 = fieldNorm(doc=4987)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Abstract

The goal in blog search is to rank blogs according to their recurrent relevance to the topic of the query. State-of-the-art approaches view it as an expert search or resource selection problem. We investigate the effect of content-based similarity between posts on the performance of the retrieval system. We test two different approaches for smoothing (regularizing) relevance scores of posts based on their dependencies. In the first approach, we smooth term distributions describing posts by performing a random walk over a document-term graph in which similar posts are highly connected. In the second, we directly smooth scores for posts using a regularization framework that aims to minimize the discrepancy between scores for similar documents. We then extend these approaches to consider the time interval between the posts in smoothing the scores. The idea is that if two posts are temporally close, then they are good sources for smoothing each other's relevance scores. We compare these methods with the state-of-the-art approaches in blog search that employ Language Modeling-based resource selection algorithms and fusion-based methods for aggregating post relevance scores. We show performance gains over the baseline techniques which do not take advantage of the relation between posts for smoothing relevance estimates.

0.006452609 = product of:
  0.019357827 = sum of:
    0.019357827 = product of:
      0.038715653 = sum of:
        0.038715653 = weight(_text_:22 in 6967) [ClassicSimilarity], result of:
          0.038715653 = score(doc=6967,freq=2.0), product of:
            0.16677667 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047625583 = queryNorm
            0.23214069 = fieldWeight in 6967, 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=6967)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Source

Information retrieval: new systems and current research. Proceedings of the 16th Research Colloquium of the British Computer Society Information Retrieval Specialist Group, Drymen, Scotland, 22-23 Mar 94. Ed.: R. Leon

0.006452609 = product of:
  0.019357827 = sum of:
    0.019357827 = product of:
      0.038715653 = sum of:
        0.038715653 = weight(_text_:22 in 1451) [ClassicSimilarity], result of:
          0.038715653 = score(doc=1451,freq=2.0), product of:
            0.16677667 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047625583 = queryNorm
            0.23214069 = fieldWeight in 1451, 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=1451)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

22. 3.2003 19:27:36

0.006452609 = product of:
  0.019357827 = sum of:
    0.019357827 = product of:
      0.038715653 = sum of:
        0.038715653 = weight(_text_:22 in 5047) [ClassicSimilarity], result of:
          0.038715653 = score(doc=5047,freq=2.0), product of:
            0.16677667 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.047625583 = queryNorm
            0.23214069 = fieldWeight in 5047, 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=5047)
      0.5 = coord(1/2)
  0.33333334 = coord(1/3)

Date

5. 6.2006 11:22:23