Search (8 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Informetrie"
  1. Karlsson, A.; Hammarfelt, B.; Steinhauer, H.J.; Falkman, G.; Olson, N.; Nelhans, G.; Nolin, J.: Modeling uncertainty in bibliometrics and information retrieval : an information fusion approach (2015) 0.01
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    Footnote
    Beitrag in einem Special Issue "Combining bibliometrics and information retrieval"
  2. White, H. D.: Co-cited author retrieval and relevance theory : examples from the humanities (2015) 0.00
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    Footnote
    Beitrag in einem Special Issue "Combining bibliometrics and information retrieval"
  3. Bar-Ilan, J.; Levene, M.: ¬The hw-rank : an h-index variant for ranking web pages (2015) 0.00
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    Footnote
    Beitrag in einem Special Issue "Combining bibliometrics and information retrieval"
  4. Wiggers, G.; Verberne, S.; Loon, W. van; Zwenne, G.-J.: Bibliometric-enhanced legal information retrieval : combining usage and citations as flavors of impact relevance (2023) 0.00
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    Abstract
    Bibliometric-enhanced information retrieval uses bibliometrics (e.g., citations) to improve ranking algorithms. Using a data-driven approach, this article describes the development of a bibliometric-enhanced ranking algorithm for legal information retrieval, and the evaluation thereof. We statistically analyze the correlation between usage of documents and citations over time, using data from a commercial legal search engine. We then propose a bibliometric boost function that combines usage of documents with citation counts. The core of this function is an impact variable based on usage and citations that increases in influence as citations and usage counts become more reliable over time. We evaluate our ranking function by comparing search sessions before and after the introduction of the new ranking in the search engine. Using a cost model applied to 129,571 sessions before and 143,864 sessions after the intervention, we show that our bibliometric-enhanced ranking algorithm reduces the time of a search session of legal professionals by 2 to 3% on average for use cases other than known-item retrieval or updating behavior. Given the high hourly tariff of legal professionals and the limited time they can spend on research, this is expected to lead to increased efficiency, especially for users with extremely long search sessions.
    Source
    Journal of the Association for Information Science and Technology. 74(2023) no.8, S.1010-1025
  5. Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009) 0.00
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    Abstract
    This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors.
    Source
    Journal of the American Society for Information Science and Technology. 60(2009) no.11, S.2229-2243
  6. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.00
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
  7. Jacso, P.: Testing the calculation of a realistic h-index in Google Scholar, Scopus, and Web of Science for F. W. Lancaster (2008) 0.00
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    Abstract
    This paper focuses on the practical limitations in the content and software of the databases that are used to calculate the h-index for assessing the publishing productivity and impact of researchers. To celebrate F. W. Lancaster's biological age of seventy-five, and "scientific age" of forty-five, this paper discusses the related features of Google Scholar, Scopus, and Web of Science (WoS), and demonstrates in the latter how a much more realistic and fair h-index can be computed for F. W. Lancaster than the one produced automatically. Browsing and searching the cited reference index of the 1945-2007 edition of WoS, which in my estimate has over a hundred million "orphan references" that have no counterpart master records to be attached to, and "stray references" that cite papers which do have master records but cannot be identified by the matching algorithm because of errors of omission and commission in the references of the citing works, can bring up hundreds of additional cited references given to works of an accomplished author but are ignored in the automatic process of calculating the h-index. The partially manual process doubled the h-index value for F. W. Lancaster from 13 to 26, which is a much more realistic value for an information scientist and professor of his stature.
    Content
    Beitrag in einem Themenheft 'The Influence of F. W. Lancaster on Information Science and on Libraries', das als Festschrift für F.W. Lancaster deklariert ist.
  8. Mayr, P.: Bradfordizing als Re-Ranking-Ansatz in Literaturinformationssystemen (2011) 0.00
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    Source
    Information - Wissenschaft und Praxis. 62(2011) H.1, S.3-10