Search (2 results, page 1 of 1)

0.010728499 = product of:
  0.021456998 = sum of:
    0.021456998 = product of:
      0.042913996 = sum of:
        0.042913996 = weight(_text_:web in 5023) [ClassicSimilarity], result of:
          0.042913996 = score(doc=5023,freq=2.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.25239927 = fieldWeight in 5023, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0546875 = fieldNorm(doc=5023)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Dieser Beitrag beschreibt eine Studie zur Entwicklung und Evaluierung von Rankingverfahren für bibliothekarische Informationssysteme. Dazu wurden mögliche Faktoren für das Relevanzranking ausgehend von den Verfahren in Websuchmaschinen identifiziert, auf den Bibliothekskontext übertragen und systematisch evaluiert. Mithilfe eines Testsystems, das auf dem ZBW-Informationsportal EconBiz und einer web-basierten Software zur Evaluierung von Suchsystemen aufsetzt, wurden verschiedene Relevanzfaktoren (z. B. Popularität in Verbindung mit Aktualität) getestet. Obwohl die getesteten Rankingverfahren auf einer theoretischen Ebene divers sind, konnten keine einheitlichen Verbesserungen gegenüber den Baseline-Rankings gemessen werden. Die Ergebnisse deuten darauf hin, dass eine Adaptierung des Rankings auf individuelle Nutzer bzw. Nutzungskontexte notwendig sein könnte, um eine höhere Performance zu erzielen.

0.007663213 = product of:
  0.015326426 = sum of:
    0.015326426 = product of:
      0.030652853 = sum of:
        0.030652853 = weight(_text_:web in 2810) [ClassicSimilarity], result of:
          0.030652853 = score(doc=2810,freq=2.0), product of:
            0.17002425 = queryWeight, product of:
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.052098576 = queryNorm
            0.18028519 = fieldWeight in 2810, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.2635105 = idf(docFreq=4597, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2810)
      0.5 = coord(1/2)
  0.5 = coord(1/2)

Abstract

Some Online Public Access Catalogues offer a ranking component. However, ranking there is merely text-based and is doomed to fail due to limited text in bibliographic data. The main assumption for the talk is that we are in a situation where the appropriate ranking factors for OPACs should be defined, while the implementation is no major problem. We must define what we want, and not so much focus on the technical work. Some deep thinking is necessary on the "perfect results set" and how we can achieve it through ranking. The talk presents a set of potential ranking factors and clustering possibilities for further discussion. A look at commercial Web search engines could provide us with ideas how ranking can be improved with additional factors. Search engines are way beyond pure text-based ranking and apply ranking factors in the groups like popularity, freshness, personalisation, etc. The talk describes the main factors used in search engines and how derivatives of these could be used for libraries' purposes. The goal of ranking is to provide the user with the best-suitable results on top of the results list. How can this goal be achieved with the library catalogue and also concerning the library's different collections and databases? The assumption is that ranking of such materials is a complex problem and is yet nowhere near solved. Libraries should focus on ranking to improve user experience.