Search (69 results, page 1 of 4)

  • × year_i:[1990 TO 2000}
  • × theme_ss:"Semantisches Umfeld in Indexierung u. Retrieval"
  1. Fieldhouse, M.; Hancock-Beaulieu, M.: ¬The design of a graphical user interface for a highly interactive information retrieval system (1996) 0.02
    0.02491532 = product of:
      0.08720362 = sum of:
        0.026618723 = weight(_text_:system in 6958) [ClassicSimilarity], result of:
          0.026618723 = score(doc=6958,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.34448233 = fieldWeight in 6958, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6958)
        0.010128049 = weight(_text_:information in 6958) [ClassicSimilarity], result of:
          0.010128049 = score(doc=6958,freq=6.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.23515764 = fieldWeight in 6958, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6958)
        0.038822707 = weight(_text_:retrieval in 6958) [ClassicSimilarity], result of:
          0.038822707 = score(doc=6958,freq=10.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.5231199 = fieldWeight in 6958, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6958)
        0.011634145 = product of:
          0.02326829 = sum of:
            0.02326829 = weight(_text_:22 in 6958) [ClassicSimilarity], result of:
              0.02326829 = score(doc=6958,freq=2.0), product of:
                0.085914485 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02453417 = queryNorm
                0.2708308 = fieldWeight in 6958, 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=6958)
          0.5 = coord(1/2)
      0.2857143 = coord(4/14)
    
    Abstract
    Reports on the design of a GUI for the Okapi 'best match' retrieval system developed at the Centre for Interactive Systems Research, City University, UK, for online library catalogues. The X-Windows interface includes an interactive query expansion (IQE) facilty which involves the user in the selection of query terms to reformulate a search. Presents the design rationale, based on a game board metaphor, and describes the features of each of the stages of the search interaction. Reports on the early operational field trial and discusses relevant evaluation issues and objectives
    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
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Beaulieu, M.; Jones, S.: Interactive searching and interface issues in the Okapi best match probabilistic retrieval system (1998) 0.02
    0.01707715 = product of:
      0.07969336 = sum of:
        0.032601144 = weight(_text_:system in 430) [ClassicSimilarity], result of:
          0.032601144 = score(doc=430,freq=6.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.42190298 = fieldWeight in 430, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=430)
        0.008269517 = weight(_text_:information in 430) [ClassicSimilarity], result of:
          0.008269517 = score(doc=430,freq=4.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.1920054 = fieldWeight in 430, 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=430)
        0.038822707 = weight(_text_:retrieval in 430) [ClassicSimilarity], result of:
          0.038822707 = score(doc=430,freq=10.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.5231199 = fieldWeight in 430, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=430)
      0.21428572 = coord(3/14)
    
    Abstract
    Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  3. Fowler, R.H.; Wilson, B.A.; Fowler, W.A.L.: Information navigator : an information system using associative networks for display and retrieval (1992) 0.02
    0.015960252 = product of:
      0.074481174 = sum of:
        0.027943838 = weight(_text_:system in 919) [ClassicSimilarity], result of:
          0.027943838 = score(doc=919,freq=6.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.36163113 = fieldWeight in 919, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=919)
        0.013260729 = weight(_text_:information in 919) [ClassicSimilarity], result of:
          0.013260729 = score(doc=919,freq=14.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.3078936 = fieldWeight in 919, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=919)
        0.033276606 = weight(_text_:retrieval in 919) [ClassicSimilarity], result of:
          0.033276606 = score(doc=919,freq=10.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.44838852 = fieldWeight in 919, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=919)
      0.21428572 = coord(3/14)
    
    Abstract
    Document retrieval is a highly interactive process dealing with large amounts of information. Visual representations can provide both a means for managing the complexity of large information structures and an interface style well suited to interactive manipulation. The system we have designed utilizes visually displayed graphic structures and a direct manipulation interface style to supply an integrated environment for retrieval. A common visually displayed network structure is used for query, document content, and term relations. A query can be modified through direct manipulation of its visual form by incorporating terms from any other information structure the system displays. An associative thesaurus of terms and an inter-document network provide information about a document collection that can complement other retrieval aids. Visualization of these large data structures makes use of fisheye views and overview diagrams to help overcome some of the inherent difficulties of orientation and navigation in large information structures.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Srinivasan, P.: Query expansion and MEDLINE (1996) 0.02
    0.015549163 = product of:
      0.07256276 = sum of:
        0.021511177 = weight(_text_:system in 8453) [ClassicSimilarity], result of:
          0.021511177 = score(doc=8453,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.27838376 = fieldWeight in 8453, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0625 = fieldNorm(doc=8453)
        0.006682779 = weight(_text_:information in 8453) [ClassicSimilarity], result of:
          0.006682779 = score(doc=8453,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.1551638 = fieldWeight in 8453, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0625 = fieldNorm(doc=8453)
        0.044368807 = weight(_text_:retrieval in 8453) [ClassicSimilarity], result of:
          0.044368807 = score(doc=8453,freq=10.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.59785134 = fieldWeight in 8453, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0625 = fieldNorm(doc=8453)
      0.21428572 = coord(3/14)
    
    Abstract
    Evaluates the retrieval effectiveness of query expansion strategies on a test collection of the medical database MEDLINE using Cornell University's SMART retrieval system. Tests 3 expansion strategies for their ability to identify appropriate MeSH terms for user queries. Compares retrieval effectiveness using the original unexpanded and the alternative expanded user queries on a collection of 75 queries and 2.334 Medline citations. Recommends query expansions using retrieval feedback for adding MeSH search terms to a user's initial query
    Source
    Information processing and management. 32(1996) no.4, S.431-443
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  5. Hemmje, M.: LyberWorld - a 3D graphical user interface for fulltext retrieval (1995) 0.01
    0.014276061 = product of:
      0.06662162 = sum of:
        0.018822279 = weight(_text_:system in 2385) [ClassicSimilarity], result of:
          0.018822279 = score(doc=2385,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.2435858 = fieldWeight in 2385, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2385)
        0.013075255 = weight(_text_:information in 2385) [ClassicSimilarity], result of:
          0.013075255 = score(doc=2385,freq=10.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.3035872 = fieldWeight in 2385, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2385)
        0.034724083 = weight(_text_:retrieval in 2385) [ClassicSimilarity], result of:
          0.034724083 = score(doc=2385,freq=8.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.46789268 = fieldWeight in 2385, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=2385)
      0.21428572 = coord(3/14)
    
    Abstract
    LyberWorld is a prototype IR user interface. It implements visualizations of an abstract information space: fulltext. The video demonstrates a visual user interface for the probabilistic fulltext retrieval system INQUERY. Visualizations are used to communicate information search and browsing activities in a natural way by applying metaphors of spatial navigation in abstract information spaces. Visualization tools for exploring information spaces and judging relevance of information items are introduced and an example session demonstrates the prototype. The presence of a spatial model in the user's mind is regarded as an essential contribution towards natural interaction and reduction of cognitive costs during retrieval dialogues.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  6. Beaulieu, M.: Experiments on interfaces to support query expansion (1997) 0.01
    0.01340102 = product of:
      0.062538095 = sum of:
        0.026618723 = weight(_text_:system in 4704) [ClassicSimilarity], result of:
          0.026618723 = score(doc=4704,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.34448233 = fieldWeight in 4704, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4704)
        0.0058474317 = weight(_text_:information in 4704) [ClassicSimilarity], result of:
          0.0058474317 = score(doc=4704,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.13576832 = fieldWeight in 4704, 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=4704)
        0.03007194 = weight(_text_:retrieval in 4704) [ClassicSimilarity], result of:
          0.03007194 = score(doc=4704,freq=6.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.40520695 = fieldWeight in 4704, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=4704)
      0.21428572 = coord(3/14)
    
    Abstract
    Focuses on the user and human-computer interaction (HCI) aspects of the research based on the Okapi text retrieval system. Describes 3 experiments using different approaches to query expansion, highlighting the relationship between the functionality of a system and different interface designs. These experiments involve both automatic and interactive query expansion, and both character based and GUI (graphical user interface) environments. The effectiveness of the search interaction for query expansion depends on resolving opposing interface and functional aspects, e.g. automatic vs. interactive query expansion, explicit vs. implicit use of a thesaurus, and document vs. query space
    Footnote
    Contribution to a thematic issue on Okapi and information retrieval research
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  7. Hemmje, M.; Kunkel, C.; Willett, A.: LyberWorld - a visualization user interface supporting fulltext retrieval (1994) 0.01
    0.013218651 = product of:
      0.061687037 = sum of:
        0.016133383 = weight(_text_:system in 2384) [ClassicSimilarity], result of:
          0.016133383 = score(doc=2384,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.20878783 = fieldWeight in 2384, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=2384)
        0.012277049 = weight(_text_:information in 2384) [ClassicSimilarity], result of:
          0.012277049 = score(doc=2384,freq=12.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.2850541 = fieldWeight in 2384, 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=2384)
        0.033276606 = weight(_text_:retrieval in 2384) [ClassicSimilarity], result of:
          0.033276606 = score(doc=2384,freq=10.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.44838852 = fieldWeight in 2384, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=2384)
      0.21428572 = coord(3/14)
    
    Abstract
    LyberWorld is a prototype IR user interface. It implements visualizations of an abstract information space-fulltext. The paper derives a model for such visualizations and an exemplar user interface design is implemented for the probabilistic fulltext retrieval system INQUERY. Visualizations are used to communicate information search and browsing activities in a natural way by applying metaphors of spatial navigation in abstract information spaces. Visualization tools for exploring information spaces and judging relevance of information items are introduced and an example session demonstrates the prototype. The presence of a spatial model in the user's mind and interaction with a system's corresponding display methods is regarded as an essential contribution towards natural interaction and reduction of cognitive costs during e.g. query construction, orientation within the database content, relevance judgement and orientation within the retrieval context.
    Source
    Proceeding SIGIR '94: Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  8. Rudolph, S.; Hemmje, M.: Visualisierung von Thesauri zur interaktiven Unterstüzung von visuellen Anfragen an Textdatenbanken (1994) 0.01
    0.012834785 = product of:
      0.05989566 = sum of:
        0.013444485 = weight(_text_:system in 2382) [ClassicSimilarity], result of:
          0.013444485 = score(doc=2382,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.17398985 = fieldWeight in 2382, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2382)
        0.0072343214 = weight(_text_:information in 2382) [ClassicSimilarity], result of:
          0.0072343214 = score(doc=2382,freq=6.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.16796975 = fieldWeight in 2382, 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=2382)
        0.039216854 = weight(_text_:retrieval in 2382) [ClassicSimilarity], result of:
          0.039216854 = score(doc=2382,freq=20.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.5284309 = fieldWeight in 2382, product of:
              4.472136 = tf(freq=20.0), with freq of:
                20.0 = termFreq=20.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2382)
      0.21428572 = coord(3/14)
    
    Abstract
    In der folgenden Studie wird eine Komponente für eine visuelle Benutzerschnittstelle zu Textdatenbanken entworfen. Mit Hilfe einer Terminologievisualisierung wird dem Benutzer eine Hilfestellung bei der Relevanzbewertung von Dokumenten und bei der Erweiterung seiner visuellen Anfrage an das Retrieval-System gegeben. Dazu werden zuerst die grundlegenden Information-Retrieval-Modelle eingehender vorgestellt, d.h., generelle Retrieval-Modelle, Retrievaloperationen und spezielle Retrieval-Modelle wie Text-Retrieval werden erläutert. Die Funktionalität eines Text-Retrieval-Systems wird vorgestellt. Darüber hinaus werden bereits existierende Implementierungen visueller Information-Retrieval-Benutzerschnittstellen vorgestellt. Im weiteren Verlauf der Arbeit werden mögliche Visualisierungen der mit Hilfe eines Text-Retrieval-Systems gefundenen Dokumente aufgezeigt. Es werden mehrere Vorschläge zur Visualisierung von Thesauri diskutiert. Es wird gezeigt, wie neuronale Netze zur Kartierung eines Eingabebereiches benutzt werden können. Klassifikationsebenen einer objekt-orientierten Annäherung eines Information-Retrieval-Systems werden vorgestellt. In diesem Zusammenhang werden auch die Eigenschaften von Thesauri sowie die Architektur und Funktion eines Parsersystems erläutert. Mit diesen Voraussetzung wird die Implementierung einer visuellen Terminologierunterstützung realisiert. Abschließend wird ein Fazit zur vorgestellten Realisierung basierend auf einem Drei-Schichten-Modell von [Agosti et al. 1990] gezogen.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  9. Robertson, S.E.: OKAPI at TREC-3 (1995) 0.01
    0.011730354 = product of:
      0.05474165 = sum of:
        0.018822279 = weight(_text_:system in 5694) [ClassicSimilarity], result of:
          0.018822279 = score(doc=5694,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.2435858 = fieldWeight in 5694, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5694)
        0.0058474317 = weight(_text_:information in 5694) [ClassicSimilarity], result of:
          0.0058474317 = score(doc=5694,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.13576832 = fieldWeight in 5694, 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=5694)
        0.03007194 = weight(_text_:retrieval in 5694) [ClassicSimilarity], result of:
          0.03007194 = score(doc=5694,freq=6.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.40520695 = fieldWeight in 5694, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5694)
      0.21428572 = coord(3/14)
    
    Abstract
    Reports text information retrieval experiments performed as part of the 3 rd round of Text Retrieval Conferences (TREC) using the Okapi online catalogue system at City University, UK. The emphasis in TREC-3 was: further refinement of term weighting functions; an investigation of run time passage determination and searching; expansion of ad hoc queries by terms extracted from the top documents retrieved by a trial search; new methods for choosing query expansion terms after relevance feedback, now split into methods of ranking terms prior to selection and subsequent selection procedures; and the development of a user interface procedure within the new TREC interactive search framework
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  10. Oard, D.W.: Alternative approaches for cross-language text retrieval (1997) 0.01
    0.011457522 = product of:
      0.053468436 = sum of:
        0.013309361 = weight(_text_:system in 1164) [ClassicSimilarity], result of:
          0.013309361 = score(doc=1164,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.17224117 = fieldWeight in 1164, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1164)
        0.0065376274 = weight(_text_:information in 1164) [ClassicSimilarity], result of:
          0.0065376274 = score(doc=1164,freq=10.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.1517936 = fieldWeight in 1164, product of:
              3.1622777 = tf(freq=10.0), with freq of:
                10.0 = termFreq=10.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1164)
        0.03362145 = weight(_text_:retrieval in 1164) [ClassicSimilarity], result of:
          0.03362145 = score(doc=1164,freq=30.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.45303512 = fieldWeight in 1164, product of:
              5.477226 = tf(freq=30.0), with freq of:
                30.0 = termFreq=30.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02734375 = fieldNorm(doc=1164)
      0.21428572 = coord(3/14)
    
    Abstract
    The explosive growth of the Internet and other sources of networked information have made automatic mediation of access to networked information sources an increasingly important problem. Much of this information is expressed as electronic text, and it is becoming practical to automatically convert some printed documents and recorded speech to electronic text as well. Thus, automated systems capable of detecting useful documents are finding widespread application. With even a small number of languages it can be inconvenient to issue the same query repeatedly in every language, so users who are able to read more than one language will likely prefer a multilingual text retrieval system over a collection of monolingual systems. And since reading ability in a language does not always imply fluent writing ability in that language, such users will likely find cross-language text retrieval particularly useful for languages in which they are less confident of their ability to express their information needs effectively. The use of such systems can be also be beneficial if the user is able to read only a single language. For example, when only a small portion of the document collection will ever be examined by the user, performing retrieval before translation can be significantly more economical than performing translation before retrieval. So when the application is sufficiently important to justify the time and effort required for translation, those costs can be minimized if an effective cross-language text retrieval system is available. Even when translation is not available, there are circumstances in which cross-language text retrieval could be useful to a monolingual user. For example, a researcher might find a paper published in an unfamiliar language useful if that paper contains references to works by the same author that are in the researcher's native language.
    Multilingual text retrieval can be defined as selection of useful documents from collections that may contain several languages (English, French, Chinese, etc.). This formulation allows for the possibility that individual documents might contain more than one language, a common occurrence in some applications. Both cross-language and within-language retrieval are included in this formulation, but it is the cross-language aspect of the problem which distinguishes multilingual text retrieval from its well studied monolingual counterpart. At the SIGIR 96 workshop on "Cross-Linguistic Information Retrieval" the participants discussed the proliferation of terminology being used to describe the field and settled on "Cross-Language" as the best single description of the salient aspect of the problem. "Multilingual" was felt to be too broad, since that term has also been used to describe systems able to perform within-language retrieval in more than one language but that lack any cross-language capability. "Cross-lingual" and "cross-linguistic" were felt to be equally good descriptions of the field, but "crosslanguage" was selected as the preferred term in the interest of standardization. Unfortunately, at about the same time the U.S. Defense Advanced Research Projects Agency (DARPA) introduced "translingual" as their preferred term, so we are still some distance from reaching consensus on this matter.
    I will not attempt to draw a sharp distinction between retrieval and filtering in this survey. Although my own work on adaptive cross-language text filtering has led me to make this distinction fairly carefully in other presentations (c.f., (Oard 1997b)), such an proach does little to help understand the fundamental techniques which have been applied or the results that have been obtained in this case. Since it is still common to view filtering (detection of useful documents in dynamic document streams) as a kind of retrieval, will simply adopt that perspective here.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. Efthimiadis, E.N.: User choices : a new yardstick for the evaluation of ranking algorithms for interactive query expansion (1995) 0.01
    0.010952224 = product of:
      0.038332783 = sum of:
        0.013444485 = weight(_text_:system in 5697) [ClassicSimilarity], result of:
          0.013444485 = score(doc=5697,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.17398985 = fieldWeight in 5697, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5697)
        0.004176737 = weight(_text_:information in 5697) [ClassicSimilarity], result of:
          0.004176737 = score(doc=5697,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.09697737 = fieldWeight in 5697, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5697)
        0.012401459 = weight(_text_:retrieval in 5697) [ClassicSimilarity], result of:
          0.012401459 = score(doc=5697,freq=2.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.16710453 = fieldWeight in 5697, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0390625 = fieldNorm(doc=5697)
        0.008310104 = product of:
          0.016620208 = sum of:
            0.016620208 = weight(_text_:22 in 5697) [ClassicSimilarity], result of:
              0.016620208 = score(doc=5697,freq=2.0), product of:
                0.085914485 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02453417 = queryNorm
                0.19345059 = fieldWeight in 5697, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=5697)
          0.5 = coord(1/2)
      0.2857143 = coord(4/14)
    
    Abstract
    The performance of 8 ranking algorithms was evaluated with respect to their effectiveness in ranking terms for query expansion. The evaluation was conducted within an investigation of interactive query expansion and relevance feedback in a real operational environment. Focuses on the identification of algorithms that most effectively take cognizance of user preferences. user choices (i.e. the terms selected by the searchers for the query expansion search) provided the yardstick for the evaluation of the 8 ranking algorithms. This methodology introduces a user oriented approach in evaluating ranking algorithms for query expansion in contrast to the standard, system oriented approaches. Similarities in the performance of the 8 algorithms and the ways these algorithms rank terms were the main focus of this evaluation. The findings demonstrate that the r-lohi, wpq, enim, and porter algorithms have similar performance in bringing good terms to the top of a ranked list of terms for query expansion. However, further evaluation of the algorithms in different (e.g. full text) environments is needed before these results can be generalized beyond the context of the present study
    Date
    22. 2.1996 13:14:10
    Source
    Information processing and management. 31(1995) no.4, S.605-620
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  12. Robertson, S.E.; Walker, S.; Hancock-Beaulieu, M.M.: Large test collection experiments of an operational, interactive system : OKAPI at TREC (1995) 0.01
    0.01067747 = product of:
      0.049828194 = sum of:
        0.026618723 = weight(_text_:system in 6964) [ClassicSimilarity], result of:
          0.026618723 = score(doc=6964,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.34448233 = fieldWeight in 6964, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6964)
        0.0058474317 = weight(_text_:information in 6964) [ClassicSimilarity], result of:
          0.0058474317 = score(doc=6964,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.13576832 = fieldWeight in 6964, 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=6964)
        0.017362041 = weight(_text_:retrieval in 6964) [ClassicSimilarity], result of:
          0.017362041 = score(doc=6964,freq=2.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.23394634 = fieldWeight in 6964, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=6964)
      0.21428572 = coord(3/14)
    
    Abstract
    The Okapi system has been used in a series of experiments on the TREC collections, investiganting probabilistic methods, relevance feedback, and query expansion, and interaction issues. Some new probabilistic models have been developed, resulting in simple weigthing functions that take account of document length and within document and within query term frequency. All have been shown to be beneficial when based on large quantities of relevance data as in the routing task. Interaction issues are much more difficult to evaluate in the TREC framework, and no benefits have yet been demonstrated from feedback based on small numbers of 'relevant' items identified by intermediary searchers
    Source
    Information processing and management. 31(1995) no.3, S.345-360
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  13. Chang, C.-H.; Hsu, C.-C.: Integrating query expansion and conceptual relevance feedback for personalized Web information retrieval (1998) 0.01
    0.010260566 = product of:
      0.047882643 = sum of:
        0.011694863 = weight(_text_:information in 1319) [ClassicSimilarity], result of:
          0.011694863 = score(doc=1319,freq=8.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.27153665 = fieldWeight in 1319, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1319)
        0.024553634 = weight(_text_:retrieval in 1319) [ClassicSimilarity], result of:
          0.024553634 = score(doc=1319,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.33085006 = fieldWeight in 1319, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1319)
        0.011634145 = product of:
          0.02326829 = sum of:
            0.02326829 = weight(_text_:22 in 1319) [ClassicSimilarity], result of:
              0.02326829 = score(doc=1319,freq=2.0), product of:
                0.085914485 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02453417 = queryNorm
                0.2708308 = fieldWeight in 1319, 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=1319)
          0.5 = coord(1/2)
      0.21428572 = coord(3/14)
    
    Abstract
    Keyword based querying has been an immediate and efficient way to specify and retrieve related information that the user inquired. However, conventional document ranking based on an automatic assessment of document relevance to the query may not be the best approach when little information is given. Proposes an idea to integrate 2 existing techniques, query expansion and relevance feedback to achieve a concept-based information search for the Web
    Date
    1. 8.1996 22:08:06
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  14. Magennis, M.: Expert rule-based query expansion (1995) 0.01
    0.00961789 = product of:
      0.06732523 = sum of:
        0.032601144 = weight(_text_:system in 5181) [ClassicSimilarity], result of:
          0.032601144 = score(doc=5181,freq=6.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.42190298 = fieldWeight in 5181, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5181)
        0.034724083 = weight(_text_:retrieval in 5181) [ClassicSimilarity], result of:
          0.034724083 = score(doc=5181,freq=8.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.46789268 = fieldWeight in 5181, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5181)
      0.14285715 = coord(2/14)
    
    Abstract
    Examines how, for term based free text retrieval, Interactive Query Expansion (IQE) provides better retrieval performance tahn Automatic Query Expansion (AQE) but the performance of IQE depends on the strategy employed by the user to select expansion terms. The aim is to build an expert query expansion system using term selection rules based on expert users' strategies. It is expected that such a system will achieve better performance for novice or inexperienced users that either AQE or IQE. The procedure is to discover expert IQE users' term selection strategies through observation and interrogation, to construct a rule based query expansion (RQE) system based on these and to compare the resulting retrieval performance with that of comparable AQE and IQE systems
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  15. Chen, H.; Martinez, J.; Kirchhoff, A.; Ng, T.D.; Schatz, B.R.: Alleviating search uncertainty through concept associations : automatic indexing, co-occurence analysis, and parallel computing (1998) 0.01
    0.00959699 = product of:
      0.044785954 = sum of:
        0.022816047 = weight(_text_:system in 5202) [ClassicSimilarity], result of:
          0.022816047 = score(doc=5202,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.29527056 = fieldWeight in 5202, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=5202)
        0.0070881573 = weight(_text_:information in 5202) [ClassicSimilarity], result of:
          0.0070881573 = score(doc=5202,freq=4.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.16457605 = fieldWeight in 5202, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=5202)
        0.014881751 = weight(_text_:retrieval in 5202) [ClassicSimilarity], result of:
          0.014881751 = score(doc=5202,freq=2.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.20052543 = fieldWeight in 5202, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=5202)
      0.21428572 = coord(3/14)
    
    Abstract
    In this article, we report research on an algorithmic approach to alleviating search uncertainty in a large information space. Grounded on object filtering, automatic indexing, and co-occurence analysis, we performed a large-scale experiment using a parallel supercomputer (SGI Power Challenge) to analyze 400.000+ abstracts in an INSPEC computer engineering collection. Two system-generated thesauri, one based on a combined object filtering and automatic indexing method, and the other based on automatic indexing only, were compaed with the human-generated INSPEC subject thesaurus. Our user evaluation revealed that the system-generated thesauri were better than the INSPEC thesaurus in 'concept recall', but in 'concept precision' the 3 thesauri were comparable. Our analysis also revealed that the terms suggested by the 3 thesauri were complementary and could be used to significantly increase 'variety' in search terms the thereby reduce search uncertainty
    Source
    Journal of the American Society for Information Science. 49(1998) no.3, S.206-216
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  16. Fidel, R.; Efthimiadis, E.N.: Terminological knowledge structure for intermediary expert systems (1995) 0.01
    0.0090410225 = product of:
      0.04219144 = sum of:
        0.016133383 = weight(_text_:system in 5695) [ClassicSimilarity], result of:
          0.016133383 = score(doc=5695,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.20878783 = fieldWeight in 5695, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=5695)
        0.0050120843 = weight(_text_:information in 5695) [ClassicSimilarity], result of:
          0.0050120843 = score(doc=5695,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.116372846 = fieldWeight in 5695, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=5695)
        0.021045974 = weight(_text_:retrieval in 5695) [ClassicSimilarity], result of:
          0.021045974 = score(doc=5695,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.2835858 = fieldWeight in 5695, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=5695)
      0.21428572 = coord(3/14)
    
    Abstract
    To provide advice for online searching about term selection and query expansion, an intermediary expert system should indicate a terminological knowledge structure. Terminological attributes could provide the foundation of a knowledge base, and knowledge acquisition could rely on knowledge base techniques coupled with statistical techniques. The strategies of expert searchers would provide 1 source of knowledge. The knowledge structure would include 3 constructs for each term: frequency data, a hedge, and a position in a classification scheme. Switching vocabularies could provide a meta-scheme and facilitate the interoperability of databases in similar subjects. To develop such knowledge structure, research should focus on terminological attributes, word and phrase disambiguation, automated text processing, and the role of thesauri and classification schemes in indexing and retrieval. It should develop techniques that combine knowledge base and statistical methods and that consider user preferences
    Source
    Information processing and management. 31(1995) no.1, S.15-27
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  17. Walker, S.; DeVere, R.: Improving subject retrieval in online catalogues : T.2: Relevance feedback and query expansion (1990) 0.01
    0.008852228 = product of:
      0.061965592 = sum of:
        0.02688897 = weight(_text_:system in 1816) [ClassicSimilarity], result of:
          0.02688897 = score(doc=1816,freq=2.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.3479797 = fieldWeight in 1816, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.078125 = fieldNorm(doc=1816)
        0.035076622 = weight(_text_:retrieval in 1816) [ClassicSimilarity], result of:
          0.035076622 = score(doc=1816,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.47264296 = fieldWeight in 1816, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.078125 = fieldNorm(doc=1816)
      0.14285715 = coord(2/14)
    
    Content
    1. Introduction // 2. Query modification through relevance feedback // 3. System design & description 4. Evaluation // 5. Analysis & results // 6. Conclusions and recommendations
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  18. Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996) 0.01
    0.007720753 = product of:
      0.03603018 = sum of:
        0.0050120843 = weight(_text_:information in 2230) [ClassicSimilarity], result of:
          0.0050120843 = score(doc=2230,freq=2.0), product of:
            0.04306919 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.02453417 = queryNorm
            0.116372846 = fieldWeight in 2230, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2230)
        0.021045974 = weight(_text_:retrieval in 2230) [ClassicSimilarity], result of:
          0.021045974 = score(doc=2230,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.2835858 = fieldWeight in 2230, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=2230)
        0.009972124 = product of:
          0.019944249 = sum of:
            0.019944249 = weight(_text_:22 in 2230) [ClassicSimilarity], result of:
              0.019944249 = score(doc=2230,freq=2.0), product of:
                0.085914485 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.02453417 = queryNorm
                0.23214069 = fieldWeight in 2230, 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=2230)
          0.5 = coord(1/2)
      0.21428572 = coord(3/14)
    
    Source
    Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  19. Beaulieu, M.; Payne, A.; Do, T.; Jones, S.: ENQUIRE Okapi project (1996) 0.01
    0.0076161064 = product of:
      0.05331274 = sum of:
        0.032266766 = weight(_text_:system in 3369) [ClassicSimilarity], result of:
          0.032266766 = score(doc=3369,freq=8.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.41757566 = fieldWeight in 3369, product of:
              2.828427 = tf(freq=8.0), with freq of:
                8.0 = termFreq=8.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.046875 = fieldNorm(doc=3369)
        0.021045974 = weight(_text_:retrieval in 3369) [ClassicSimilarity], result of:
          0.021045974 = score(doc=3369,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.2835858 = fieldWeight in 3369, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.046875 = fieldNorm(doc=3369)
      0.14285715 = coord(2/14)
    
    Abstract
    The ENQUIRE project forms part of a series of investigations on query expansion in the Okapi experimental text retrieval system. A configurable user interface was implemented as an evaluative tool and tested in two locations on two different databases: the library catalogue of The London Business SChool and the computing section of INSPEC. The system offered a range of possible strategies based on thesaural terms for reformulating queries. These could be initiated automatically by the system or interactively with the user. The formative phase of the evaluation established the appropriateness and usability of the interface as well as users' perceptions of the underlying functionality. The aim of the large scale field trial was to determine to what extent user would select thesaural terms suggested by the system to reformulate queries, and to evaluate the effectiveness of a new dynamic form of query expansion implemented for this project
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  20. Hancock-Beaulieu, M.; Fieldhouse, M.; Do, T.: ¬A graphical interface for OKAPI : the design and evaluation of an online catalogue system with direct manipulation interaction for subject access (1994) 0.01
    0.007310337 = product of:
      0.051172357 = sum of:
        0.026618723 = weight(_text_:system in 1318) [ClassicSimilarity], result of:
          0.026618723 = score(doc=1318,freq=4.0), product of:
            0.07727166 = queryWeight, product of:
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.02453417 = queryNorm
            0.34448233 = fieldWeight in 1318, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.1495528 = idf(docFreq=5152, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1318)
        0.024553634 = weight(_text_:retrieval in 1318) [ClassicSimilarity], result of:
          0.024553634 = score(doc=1318,freq=4.0), product of:
            0.07421378 = queryWeight, product of:
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.02453417 = queryNorm
            0.33085006 = fieldWeight in 1318, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              3.024915 = idf(docFreq=5836, maxDocs=44218)
              0.0546875 = fieldNorm(doc=1318)
      0.14285715 = coord(2/14)
    
    Abstract
    A project to design a graphical user interface for the OKAPI online catalogue search system which uses the basic term weighting probabilistic search engine. Presents a research context of the project with a discussion of interface and functionality issues relating to the design of OPACs. Describes the design methodology and evaluation methodology. Presents the preliminary results of the field trial evaluation. Considers problems encountered in the field trial and discusses contributory factors to the effectiveness of interactive query expansion. Highlights the tension between usability and functionality in highly interactive retrieval and suggests further areas of research
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval

Languages

  • e 61
  • d 5
  • chi 1
  • f 1
  • More… Less…

Types

  • a 57
  • r 7
  • el 5
  • m 4
  • p 1
  • More… Less…

Classifications