Search (6 results, page 1 of 1)

  • × author_ss:"Mayr, P."
  • × language_ss:"e"
  • × year_i:[2010 TO 2020}
  1. Mayr, P.; Scharnhorst, A.: Scientometrics and information retrieval - weak-links revitalized (2015) 0.01 
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    Footnote
    Editorial zu einem Special Issue "Combining bibliometrics and information retrieval"
  2. Mutschke, P.; Mayr, P.: Science models for search : a study on combining scholarly information retrieval and scientometrics (2015) 0.01 
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    Footnote
    Beitrag in einem Special Issue "Combining bibliometrics and information retrieval"
  3. Mayr, P.; Schaer, P.; Mutschke, P.: ¬A science model driven retrieval prototype (2011) 0.01 
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    Abstract
    This paper is about a better understanding of the structure and dynamics of science and the usage of these insights for compensating the typical problems that arises in metadata-driven Digital Libraries. Three science model driven retrieval services are presented: co-word analysis based query expansion, re-ranking via Bradfordizing and author centrality. The services are evaluated with relevance assessments from which two important implications emerge: (1) precision values of the retrieval services are the same or better than the tf-idf retrieval baseline and (2) each service retrieved a disjoint set of documents. The different services each favor quite other - but still relevant - documents than pure term-frequency based rankings. The proposed models and derived retrieval services therefore open up new viewpoints on the scientific knowledge space and provide an alternative framework to structure scholarly information systems.
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  4. Mayr, P.; Mutschke, P.; Petras, V.; Schaer, P.; Sure, Y.: Applying science models for search (2010) 0.01 
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    Abstract
    The paper proposes three different kinds of science models as value-added services that are integrated in the retrieval process to enhance retrieval quailty. The paper discusses the approaches Search Term Recommendation, Bradfordizing and Author Centrality on a general level and addresses implementation issues of the models within a real-life retrieval environment.
    Source
    Information und Wissen: global, sozial und frei? Proceedings des 12. Internationalen Symposiums für Informationswissenschaft (ISI 2011) ; Hildesheim, 9. - 11. März 2011. Hrsg.: J. Griesbaum, T. Mandl u. C. Womser-Hacker
  5. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.01 
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    Abstract
    Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.
  6. Carevic, Z.; Krichel, T.; Mayr, P.: Assessing a human mediated current awareness service (2015) 0.00 
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    Source
    Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff

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