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RELEVANCE: A review of and a framework for the thinking on the notion in information science

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  • Tefko Saracevic

Abstract

Information science emerged as the third subject, along with logic and philosophy, to deal with relevance‐an elusive, human notion. The concern with relevance, as a key notion in information science, is traced to the problems of scientific communication. Relevance is considered as a measure of the effectiveness of a contact between a source and a destination in a communication process. The different views of relevance that emerged are interpreted and related within a framework of communication of knowledge. Different views arose because relevance was considered at a number of different points in the process of knowledge communication. It is suggested that there exists an interlocking, interplaying cycle of various systems of relevances.

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  • Tefko Saracevic, 1975. "RELEVANCE: A review of and a framework for the thinking on the notion in information science," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 26(6), pages 321-343, November.
    • Handle: RePEc:bla:jamest:v:26:y:1975:i:6:p:321-343
    DOI: 10.1002/asi.4630260604
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    Cited by:

    1. Anton van der Vegt & Guido Zuccon & Bevan Koopman, 2021. "Do better search engines really equate to better clinical decisions? If not, why not?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(2), pages 141-155, February.
    2. P. K. Paul & A. Bhuimali & R. Rajesh & K. L. Dangwal & P. Das & J. Ganguly, 2016. "Green Computing for Eco Enriched Information Services and Systems: Environmental & Bio Informatics Perspective," Journal of Biotechnology Research, Academic Research Publishing Group, vol. 2(6), pages 44-48, 06-2016.
    3. Antonio Maria Rinaldi & Cristiano Russo & Cristian Tommasino, 2020. "A Knowledge-Driven Multimedia Retrieval System Based on Semantics and Deep Features," Future Internet, MDPI, vol. 12(11), pages 1-20, October.
    4. Malcolm Dow & Peter Willett & Roderick McDonald & Belver Griffith & Michael Greenacre & Peter Bryant & Daniel Wartenberg & Ove Frank, 1987. "Book reviews," Journal of Classification, Springer;The Classification Society, vol. 4(2), pages 245-278, September.
    5. Aurora González-Teruel & Gregorio González-Alcaide & Maite Barrios & María-Francisca Abad-García, 2015. "Mapping recent information behavior research: an analysis of co-authorship and co-citation networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 687-705, May.
    6. Lutz Bornmann & Loet Leydesdorff, 2020. "Historical roots of Judit Bar-Ilan’s research: a cited-references analysis using CRExplorer," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(3), pages 1193-1200, June.
    7. Olof Sundin & Dirk Lewandowski & Jutta Haider, 2022. "Whose relevance? Web search engines as multisided relevance machines," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(5), pages 637-642, May.
    8. Howard D. White, 2010. "Some new tests of relevance theory in information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 653-667, June.
    9. Xiaoli Huang & Dagobert Soergel, 2013. "Relevance: An improved framework for explicating the notion," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 18-35, January.
    10. Peter Mutschke & Philipp Mayr, 2015. "Science models for search: a study on combining scholarly information retrieval and scientometrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2323-2345, March.
    11. Adan Ortiz-Cordova & Bernard J. Jansen, 2012. "Classifying web search queries to identify high revenue generating customers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(7), pages 1426-1441, July.
    12. Jingfei Li & Peng Zhang & Dawei Song & Yue Wu, 2017. "Understanding an enriched multidimensional user relevance model by analyzing query logs," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(12), pages 2743-2754, December.
    13. Dietmar Wolfram, 2015. "The symbiotic relationship between information retrieval and informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2201-2214, March.
    14. Nathalie Demoulin & Kristof Coussement, 2018. "Acceptance of text-mining systems: The signaling role of information quality," Post-Print hal-02111772, HAL.
    15. Gineke Wiggers & Suzan Verberne & Wouter van Loon & Gerrit‐Jan Zwenne, 2023. "Bibliometric‐enhanced legal information retrieval: Combining usage and citations as flavors of impact relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(8), pages 1010-1025, August.
    16. Anton Oleinik, 2022. "Relevance in Web search: between content, authority and popularity," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(1), pages 173-194, February.

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