Search (2 results, page 1 of 1)

  • × author_ss:"Thelwall, M."
  • × author_ss:"Vaughan, L."
  • × theme_ss:"Suchmaschinen"
  1. Vaughan, L.; Thelwall, M.: Search engine coverage bias : evidence and possible causes (2004) 0.00
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    Abstract
    Commercial search engines are now playing an increasingly important role in Web information dissemination and access. Of particular interest to business and national governments is whether the big engines have coverage biased towards the US or other countries. In our study we tested for national biases in three major search engines and found significant differences in their coverage of commercial Web sites. The US sites were much better covered than the others in the study: sites from China, Taiwan and Singapore. We then examined the possible technical causes of the differences and found that the language of a site does not affect its coverage by search engines. However, the visibility of a site, measured by the number of links to it, affects its chance to be covered by search engines. We conclude that the coverage bias does exist but this is due not to deliberate choices of the search engines but occurs as a natural result of cumulative advantage effects of US sites on the Web. Nevertheless, the bias remains a cause for international concern.
    Source
    Information processing and management. 40(2004) no.4, S.693-708
  2. Thelwall, M.; Vaughan, L.: New versions of PageRank employing alternative Web document models (2004) 0.00
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    Abstract
    Introduces several new versions of PageRank (the link based Web page ranking algorithm), based on an information science perspective on the concept of the Web document. Although the Web page is the typical indivisible unit of information in search engine results and most Web information retrieval algorithms, other research has suggested that aggregating pages based on directories and domains gives promising alternatives, particularly when Web links are the object of study. The new algorithms introduced based on these alternatives were used to rank four sets of Web pages. The ranking results were compared with human subjects' rankings. The results of the tests were somewhat inconclusive: the new approach worked well for the set that includes pages from different Web sites; however, it does not work well in ranking pages that are from the same site. It seems that the new algorithms may be effective for some tasks but not for others, especially when only low numbers of links are involved or the pages to be ranked are from the same site or directory.
    Source
    Aslib proceedings. 56(2004) no.1, S.24-33