Search (27 results, page 2 of 2)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Suchmaschinen"
  1. Stock, M.; Stock, W.G.: Internet-Suchwerkzeuge im Vergleich (IV) : Relevance Ranking nach "Popularität" von Webseiten: Google (2001) 0.00
    0.0025748524 = product of:
      0.01029941 = sum of:
        0.01029941 = weight(_text_:information in 5771) [ClassicSimilarity], result of:
          0.01029941 = score(doc=5771,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.116372846 = fieldWeight in 5771, 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=5771)
      0.25 = coord(1/4)
    
    Abstract
    In unserem Retrievaltest von Suchwerkzeugen im World Wide Web (Password 11/2000) schnitt die Suchmaschine Google am besten ab. Im Vergleich zu anderen Search Engines setzt Google kaum auf Informationslinguistik, sondern auf Algorithmen, die sich aus den Besonderheiten der Web-Dokumente ableiten lassen. Kernstück der informationsstatistischen Technik ist das "PageRank"- Verfahren (benannt nach dem Entwickler Larry Page), das aus der Hypertextstruktur des Web die "Popularität" von Seiten anhand ihrer ein- und ausgehenden Links berechnet. Google besticht durch das Angebot intuitiv verstehbarer Suchbildschirme sowie durch einige sehr nützliche "Kleinigkeiten" wie die Angabe des Rangs einer Seite, Highlighting, Suchen in der Seite, Suchen innerhalb eines Suchergebnisses usw., alles verstaut in einer eigenen Befehlsleiste innerhalb des Browsers. Ähnlich wie RealNames bietet Google mit dem Produkt "AdWords" den Aufkauf von Suchtermen an. Nach einer Reihe von nunmehr vier Password-Artikeln über InternetSuchwerkzeugen im Vergleich wollen wir abschließend zu einer Bewertung kommen. Wie ist der Stand der Technik bei Directories und Search Engines aus informationswissenschaftlicher Sicht einzuschätzen? Werden die "typischen" Internetnutzer, die ja in der Regel keine Information Professionals sind, adäquat bedient? Und können auch Informationsfachleute von den Suchwerkzeugen profitieren?
  2. Radev, D.; Fan, W.; Qu, H.; Wu, H.; Grewal, A.: Probabilistic question answering on the Web (2005) 0.00
    0.0025748524 = product of:
      0.01029941 = sum of:
        0.01029941 = weight(_text_:information in 3455) [ClassicSimilarity], result of:
          0.01029941 = score(doc=3455,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.116372846 = fieldWeight in 3455, 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=3455)
      0.25 = coord(1/4)
    
    Source
    Journal of the American Society for Information Science and Technology. 56(2005) no.6, S.571-583
  3. Thelwall, M.: Can Google's PageRank be used to find the most important academic Web pages? (2003) 0.00
    0.0025748524 = product of:
      0.01029941 = sum of:
        0.01029941 = weight(_text_:information in 4457) [ClassicSimilarity], result of:
          0.01029941 = score(doc=4457,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.116372846 = fieldWeight in 4457, 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=4457)
      0.25 = coord(1/4)
    
    Abstract
    Google's PageRank is an influential algorithm that uses a model of Web use that is dominated by its link structure in order to rank pages by their estimated value to the Web community. This paper reports on the outcome of applying the algorithm to the Web sites of three national university systems in order to test whether it is capable of identifying the most important Web pages. The results are also compared with simple inlink counts. It was discovered that the highest inlinked pages do not always have the highest PageRank, indicating that the two metrics are genuinely different, even for the top pages. More significantly, however, internal links dominated external links for the high ranks in either method and superficial reasons accounted for high scores in both cases. It is concluded that PageRank is not useful for identifying the top pages in a site and that it must be combined with a powerful text matching techniques in order to get the quality of information retrieval results provided by Google.
  4. Wills, R.S.: Google's PageRank : the math behind the search engine (2006) 0.00
    0.002427594 = product of:
      0.009710376 = sum of:
        0.009710376 = weight(_text_:information in 5954) [ClassicSimilarity], result of:
          0.009710376 = score(doc=5954,freq=4.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.10971737 = fieldWeight in 5954, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=5954)
      0.25 = coord(1/4)
    
    Abstract
    Approximately 91 million American adults use the Internet on a typical day The number-one Internet activity is reading and writing e-mail. Search engine use is next in line and continues to increase in popularity. In fact, survey findings indicate that nearly 60 million American adults use search engines on a given day. Even though there are many Internet search engines, Google, Yahoo!, and MSN receive over 81% of all search requests. Despite claims that the quality of search provided by Yahoo! and MSN now equals that of Google, Google continues to thrive as the search engine of choice, receiving over 46% of all search requests, nearly double the volume of Yahoo! and over four times that of MSN. I use Google's search engine on a daily basis and rarely request information from other search engines. One day, I decided to visit the homepages of Google. Yahoo!, and MSN to compare the quality of search results. Coffee was on my mind that day, so I entered the simple query "coffee" in the search box at each homepage. Table 1 shows the top ten (unsponsored) results returned by each search engine. Although ordered differently, two webpages, www.peets.com and www.coffeegeek.com, appear in all three top ten lists. In addition, each pairing of top ten lists has two additional results in common. Depending on the information I hoped to obtain about coffee by using the search engines, I could argue that any one of the three returned better results: however, I was not looking for a particular webpage, so all three listings of search results seemed of equal quality. Thus, I plan to continue using Google. My decision is indicative of the problem Yahoo!, MSN, and other search engine companies face in the quest to obtain a larger percentage of Internet search volume. Search engine users are loyal to one or a few search engines and are generally happy with search results. Thus, as long as Google continues to provide results deemed high in quality, Google likely will remain the top search engine. But what set Google apart from its competitors in the first place? The answer is PageRank. In this article I explain this simple mathematical algorithm that revolutionized Web search.
  5. Chen, Z.; Meng, X.; Fowler, R.H.; Zhu, B.: Real-time adaptive feature and document learning for Web search (2001) 0.00
    0.0021457102 = product of:
      0.008582841 = sum of:
        0.008582841 = weight(_text_:information in 5209) [ClassicSimilarity], result of:
          0.008582841 = score(doc=5209,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.09697737 = fieldWeight in 5209, 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=5209)
      0.25 = coord(1/4)
    
    Source
    Journal of the American Society for Information Science and technology. 52(2001) no.8, S.655-665
  6. Agosti, M.; Pretto, L.: ¬A theoretical study of a generalized version of kleinberg's HITS algorithm (2005) 0.00
    0.0021457102 = product of:
      0.008582841 = sum of:
        0.008582841 = weight(_text_:information in 4) [ClassicSimilarity], result of:
          0.008582841 = score(doc=4,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.09697737 = fieldWeight in 4, 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=4)
      0.25 = coord(1/4)
    
    Source
    Advances in mathematical/formal methods in information retrieval. 8(2005) no.2 , S.219-243
  7. Bar-Ilan, J.; Levene, M.; Mat-Hassan, M.: Methods for evaluating dynamic changes in search engine rankings : a case study (2006) 0.00
    0.0017165683 = product of:
      0.006866273 = sum of:
        0.006866273 = weight(_text_:information in 616) [ClassicSimilarity], result of:
          0.006866273 = score(doc=616,freq=2.0), product of:
            0.08850355 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.050415643 = queryNorm
            0.0775819 = fieldWeight in 616, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.03125 = fieldNorm(doc=616)
      0.25 = coord(1/4)
    
    Abstract
    Purpose - The objective of this paper is to characterize the changes in the rankings of the top ten results of major search engines over time and to compare the rankings between these engines. Design/methodology/approach - The papers compare rankings of the top-ten results of the search engines Google and AlltheWeb on ten identical queries over a period of three weeks. Only the top-ten results were considered, since users do not normally inspect more than the first results page returned by a search engine. The experiment was repeated twice, in October 2003 and in January 2004, in order to assess changes to the top-ten results of some of the queries during the three months interval. In order to assess the changes in the rankings, three measures were computed for each data collection point and each search engine. Findings - The findings in this paper show that the rankings of AlltheWeb were highly stable over each period, while the rankings of Google underwent constant yet minor changes, with occasional major ones. Changes over time can be explained by the dynamic nature of the web or by fluctuations in the search engines' indexes. The top-ten results of the two search engines had surprisingly low overlap. With such small overlap, the task of comparing the rankings of the two engines becomes extremely challenging. Originality/value - The paper shows that because of the abundance of information on the web, ranking search results is of extreme importance. The paper compares several measures for computing the similarity between rankings of search tools, and shows that none of the measures is fully satisfactory as a standalone measure. It also demonstrates the apparent differences in the ranking algorithms of two widely used search engines.

Languages

  • e 21
  • d 6

Types

  • a 22
  • m 3
  • el 2
  • r 1
  • More… Less…