Search (5 results, page 1 of 1)

0.022860084 = product of:
  0.045720167 = sum of:
    0.025228297 = weight(_text_:information in 1451) [ClassicSimilarity], result of:
      0.025228297 = score(doc=1451,freq=12.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.2850541 = fieldWeight in 1451, product of:
          3.4641016 = tf(freq=12.0), with freq of:
            12.0 = termFreq=12.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.046875 = fieldNorm(doc=1451)
    0.02049187 = product of:
      0.04098374 = sum of:
        0.04098374 = weight(_text_:22 in 1451) [ClassicSimilarity], result of:
          0.04098374 = score(doc=1451,freq=2.0), product of:
            0.17654699 = queryWeight, product of:
              3.5018296 = idf(docFreq=3622, maxDocs=44218)
              0.050415643 = 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)
  0.5 = coord(2/4)

Abstract

Research an the use of mathematical, logical, and formal methods, has been central to Information Retrieval research for a long time. Research in this area is important not only because it helps enhancing retrieval effectiveness, but also because it helps clarifying the underlying concepts of Information Retrieval. In this article we outline some of the major aspects of the subject, and summarize the papers of this special issue with respect to how they relate to these aspects. We conclude by highlighting some directions of future research, which are needed to better understand the formal characteristics of Information Retrieval.

Date

22. 3.2003 19:27:36

Footnote

Einführung zu den Beiträgen 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.281-284

0.0042914203 = product of:
  0.017165681 = sum of:
    0.017165681 = weight(_text_:information in 3824) [ClassicSimilarity], result of:
      0.017165681 = score(doc=3824,freq=2.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.19395474 = fieldWeight in 3824, product of:
          1.4142135 = tf(freq=2.0), with freq of:
            2.0 = termFreq=2.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.078125 = fieldNorm(doc=3824)
  0.25 = coord(1/4)

Source

Vocabulary as a central concept in digital libraries: interdisciplinary concepts, challenges, and opportunities : proceedings of the Third International Conference an Conceptions of Library and Information Science (COLIS3), Dubrovnik, Croatia, 23-26 May 1999. Ed. by T. Arpanac et al

0.0042914203 = product of:
  0.017165681 = sum of:
    0.017165681 = weight(_text_:information in 4998) [ClassicSimilarity], result of:
      0.017165681 = score(doc=4998,freq=8.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.19395474 = fieldWeight in 4998, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0390625 = fieldNorm(doc=4998)
  0.25 = coord(1/4)

Abstract

Documents usually have a content and a structure. The content refers to the text of the document, whereas the structure refers to how a document is logically organized. An increasingly common way to encode the structure is through the use of a mark-up language. Nowadays, the most widely used mark-up language for representing structure is the eXtensible Mark-up Language (XML). XML can be used to provide a focused access to documents, i.e. returning XML elements, such as sections and paragraphs, instead of whole documents in response to a query. Such focused strategies are of particular benefit for information repositories containing long documents, or documents covering a wide variety of topics, where users are directed to the most relevant content within a document. The increased adoption of XML to represent a document structure requires the development of tools to effectively access documents marked-up in XML. This book provides a detailed description of query languages, indexing strategies, ranking algorithms, presentation scenarios developed to access XML documents. Major advances in XML retrieval were seen from 2002 as a result of INEX, the Initiative for Evaluation of XML Retrieval. INEX, also described in this book, provided test sets for evaluating XML retrieval effectiveness. Many of the developments and results described in this book were investigated within INEX.

LCSH

Information retrieval

Series

Synthesis lectures on information concepts, retrieval & services; 7

Subject

Information retrieval

0.00424829 = product of:
  0.01699316 = sum of:
    0.01699316 = weight(_text_:information in 3880) [ClassicSimilarity], result of:
      0.01699316 = score(doc=3880,freq=4.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.1920054 = fieldWeight in 3880, product of:
          2.0 = tf(freq=4.0), with freq of:
            4.0 = termFreq=4.0
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.0546875 = fieldNorm(doc=3880)
  0.25 = coord(1/4)

Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

0.0037164795 = product of:
  0.014865918 = sum of:
    0.014865918 = weight(_text_:information in 5169) [ClassicSimilarity], result of:
      0.014865918 = score(doc=5169,freq=6.0), product of:
        0.08850355 = queryWeight, product of:
          1.7554779 = idf(docFreq=20772, maxDocs=44218)
          0.050415643 = queryNorm
        0.16796975 = fieldWeight in 5169, 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=5169)
  0.25 = coord(1/4)

Abstract

Ruthven, Mounia, and van Rijsbergen rank and select terms for query expansion using information gathered on searcher evaluation behavior. Using the TREC Financial Times and Los Angeles Times collections and search topics from TREC-6 placed in simulated work situations, six student subjects each preformed three searches on an experimental system and three on a control system with instructions to search by natural language expression in any way they found comfortable. Searching was analyzed for behavior differences between experimental and control situations, and for effectiveness and perceptions. In three experiments paired t-tests were the analysis tool with controls being a no relevance feedback system, a standard ranking for automatic expansion system, and a standard ranking for interactive expansion while the experimental systems based ranking upon user information on temporal relevance and partial relevance. Two further experiments compare using user behavior (number assessed relevant and similarity of relevant documents) to choose a query expansion technique against a non-selective technique and finally the effect of providing the user with knowledge of the process. When partial relevance data and time of assessment data are incorporated in term ranking more relevant documents were recovered in fewer iterations, however retrieval effectiveness overall was not improved. The subjects, none-the-less, rated the suggested terms as more useful and used them more heavily. Explanations of what the feedback techniques were doing led to higher use of the techniques.

Source

Journal of the American Society for Information Science and technology. 54(2003) no.6, S.528-548