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  • × year_i:[2010 TO 2020}
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  1. Ford, N.: Introduction to information behaviour (2015) 0.08
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    Date
    22. 1.2017 16:45:48
    Pages
    X, 252 S
  2. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.07
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    Content
    PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.
    Type
    x
  3. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.05
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
    Type
    x
  4. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.05
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    Date
    10. 1.2013 19:22:47
    Type
    x
  5. Wan, X.; Liu, F.: Are all literature citations equally important? : automatic citation strength estimation and its applications (2014) 0.05
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    Date
    22. 8.2014 17:12:35
  6. Ahn, J.-w.; Soergel, D.; Lin, X.; Zhang, M.: Mapping between ARTstor terms and the Getty Art and Architecture Thesaurus (2014) 0.05
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  7. Ding, Y.; Zhang, G.; Chambers, T.; Song, M.; Wang, X.; Zhai, C.: Content-based citation analysis : the next generation of citation analysis (2014) 0.05
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    Date
    22. 8.2014 16:52:04
  8. Tang, X.-B.; Liu, G.-C.; Yang, J.; Wei, W.: Knowledge-based financial statement fraud detection system : based on an ontology and a decision tree (2018) 0.05
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    Date
    21. 6.2018 10:22:43
  9. Tang, X.; Chen, L.; Cui, J.; Wei, B.: Knowledge representation learning with entity descriptions, hierarchical types, and textual relations (2019) 0.05
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    Date
    17. 3.2019 13:22:53
  10. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.04
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  11. Zhu, Q.; Kong, X.; Hong, S.; Li, J.; He, Z.: Global ontology research progress : a bibliometric analysis (2015) 0.04
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    Date
    20. 1.2015 18:30:22
    17. 9.2018 18:22:23
  12. Gu, X.; Blackmore, K.L.: Developing a scholar classification scheme from publication patterns in academic science : a cluster analysis approach (2019) 0.04
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    Abstract
    The impact of university rankings has driven scholars to increase productivity, and expanding collaboration has dramatically changed the publishing patterns in the academic publication system. The aim of this study was to develop a scholar classification scheme from publication patterns in academic science. Classification schemes are ways of describing groups that display different clusters of behaviors, approaches, or perspectives, and useful in the development of typologies. In this research, sample data are selected from three representative universities, considered a leading university, a middle-tier university, and a noncomprehensive university. A final set of 11,427 effective scholars and their 284,128 journal publication records were used to develop the classification scheme via cluster analysis. The results identify six types of scholars, labeled as: singleton (8%), small-team low performer (16%), small-team high performer (17%), big-team strategist (22%), free-style follower (21%), and life-time warrior (17%). These six scholar types demonstrate different approaches to publishing that can be used to understand both individual and research team performance across different institutional settings. Additionally, possible future work was identified that uses the scholar classification scheme to define the behavior for agents in an agent-based model to simulate the strategic-behavior-driven academic publication system.
    Date
    8.10.2019 19:18:22
  13. Yuan, X. (J.); Belkin, N.J.: Applying an information-seeking dialogue model in an interactive information retrieval system (2014) 0.04
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    Date
    6. 4.2015 19:22:59
  14. Geisriegler, E.: Enriching electronic texts with semantic metadata : a use case for the historical Newspaper Collection ANNO (Austrian Newspapers Online) of the Austrian National Libraryhek (2012) 0.04
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    Date
    3. 2.2013 18:00:22
    Type
    x
  15. Li, X.; Thelwall, M.; Kousha, K.: ¬The role of arXiv, RePEc, SSRN and PMC in formal scholarly communication (2015) 0.04
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