Search (2 results, page 1 of 1)

  • × author_ss:"Lewandowski, D."
  • × language_ss:"e"
  • × year_i:[2000 TO 2010}
  1. Lewandowski, D.: ¬The retrieval effectiveness of web search engines : considering results descriptions (2008) 0.00
    0.0049634436 = product of:
      0.014890331 = sum of:
        0.014890331 = product of:
          0.04467099 = sum of:
            0.04467099 = weight(_text_:retrieval in 2345) [ClassicSimilarity], result of:
              0.04467099 = score(doc=2345,freq=6.0), product of:
                0.15433937 = queryWeight, product of:
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.051022716 = queryNorm
                0.28943354 = fieldWeight in 2345, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.024915 = idf(docFreq=5836, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2345)
          0.33333334 = coord(1/3)
      0.33333334 = coord(1/3)
    
    Abstract
    Purpose - The purpose of this paper is to compare five major web search engines (Google, Yahoo, MSN, Ask.com, and Seekport) for their retrieval effectiveness, taking into account not only the results, but also the results descriptions. Design/methodology/approach - The study uses real-life queries. Results are made anonymous and are randomized. Results are judged by the persons posing the original queries. Findings - The two major search engines, Google and Yahoo, perform best, and there are no significant differences between them. Google delivers significantly more relevant result descriptions than any other search engine. This could be one reason for users perceiving this engine as superior. Research limitations/implications - The study is based on a user model where the user takes into account a certain amount of results rather systematically. This may not be the case in real life. Practical implications - The paper implies that search engines should focus on relevant descriptions. Searchers are advised to use other search engines in addition to Google. Originality/value - This is the first major study comparing results and descriptions systematically and proposes new retrieval measures to take into account results descriptions.
  2. Lewandowski, D.: How can library materials be ranked in the OPAC? (2009) 0.00
    0.0028845975 = product of:
      0.008653793 = sum of:
        0.008653793 = product of:
          0.025961377 = sum of:
            0.025961377 = weight(_text_:online in 2810) [ClassicSimilarity], result of:
              0.025961377 = score(doc=2810,freq=2.0), product of:
                0.1548489 = queryWeight, product of:
                  3.0349014 = idf(docFreq=5778, maxDocs=44218)
                  0.051022716 = queryNorm
                0.16765618 = fieldWeight in 2810, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.0349014 = idf(docFreq=5778, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2810)
          0.33333334 = coord(1/3)
      0.33333334 = coord(1/3)
    
    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.

Types