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  1. Hemmert, F.: Information spaces : building bridges between the digital and the physical world (2017) 0.03 
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    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
  2. Christoforidis, A.; Heuwing, B.; Mandl, T.: Visualising topics in document collections : an analysis of the interpretation process of historians (2017) 0.03 
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    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
  3. Vogler, E.; Schindler, C.; Botte, A.; Rittberger, M.: Are altmetrics effective in transdisciplinary research fields? : altmetric coverage of outputs in educational research (2017) 0.03 
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    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
  4. Stiller, J.; Király, P.: Multitlinguality of metadata : measuring the miltilingual degree of Europeana's metadata (2017) 0.03 
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    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
  5. Broughton, V.: Essential classification (2015) 0.03 
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  6. Freire, N.; Charles, V.; Isaac, A.: Subject information and multilingualism in European bibliographic datasets : experiences with Universal Decimal Classification (2015) 0.03 
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  7. Boer, V. de; Porter, A.L.; Someren, M. v.: Extracting historical time periods from the Web (2010) 0.03 
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  8. Haustein, S.; Sugimoto, C.; Larivière, V.: Social media in scholarly communication : Guest editorial (2015) 0.03 
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    Date
    20. 1.2015 18:30:22
  9. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.03 
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  10. Ye, F.Y.; Leydesdorff, L.: ¬The "academic trace" of the performance matrix : a mathematical synthesis of the h-index and the integrated impact indicator (I3) (2014) 0.03 
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    Abstract
    The h-index provides us with 9 natural classes which can be written as a matrix of 3 vectors. The 3 vectors are: X = (X1, X2, X3) and indicates publication distribution in the h-core, the h-tail, and the uncited ones, respectively; Y = (Y1, Y2, Y3) denotes the citation distribution of the h-core, the h-tail and the so-called "excess" citations (above the h-threshold), respectively; and Z = (Z1, Z2, Z3) = (Y1-X1, Y2-X2, Y3-X3). The matrix V = (X,Y,Z)T constructs a measure of academic performance, in which the 9 numbers can all be provided with meanings in different dimensions. The "academic trace" tr(V) of this matrix follows naturally, and contributes a unique indicator for total academic achievements by summarizing and weighting the accumulation of publications and citations. This measure can also be used to combine the advantages of the h-index and the integrated impact indicator (I3) into a single number with a meaningful interpretation of the values. We illustrate the use of tr(V) for the cases of 2 journal sets, 2 universities, and ourselves as 2 individual authors.
  11. Manguinhas, H.; Charles, V.; Isaac, A.; Miles, T.; Lima, A.; Neroulidis, A.; Ginouves, V.; Atsidis, D.; Hildebrand, M.; Brinkerink, M.; Gordea, S.: Linking subject labels in cultural heritage metadata to MIMO vocabulary using CultuurLink (2016) 0.03 
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  12. Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017 (2017) 0.03 
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    Editor
    Gäde, M., V. Trkulja u. V. Petras
  13. Mayr, P.; Mutschke, P.; Petras, V.; Schaer, P.; Sure, Y.: Applying science models for search (2010) 0.02 
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  14. Broughton, V.: Brian Vickery, September 11, 1918-October 17, 2009 (2011) 0.02 
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  15. Harej, V.; Zumer, M.: Analysis of FRBR user tasks (2013) 0.02 
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  16. Gültekin, V.: ¬An historical look at the studies on the subject authority file in Turkey (2019) 0.02 
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  17. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.02 
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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.
  18. Cronin, B.: Thinking about data (2013) 0.02 
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    Date
    22. 3.2013 16:18:36
  19. Grudin, J.: Human-computer interaction (2011) 0.02 
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    Date
    27.12.2014 18:54:22
  20. Vinkler, P.: Application of the distribution of citations among publications in scientometric evaluations (2011) 0.02 
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    Abstract
    The ?-indicator (or ?v-indicator) of a set of journal papers is equal to a hundredth of the total number of citations obtained by the elite set of publications. The number of publications in the elite set P(?) is calculated as the square root of total papers. For greater sets the following equation is used: P(?v) = (10 log P) - 10, where P is the total number of publications. For sets comprising a single or several extreme frequently cited paper, the ?-index may be distorted. Therefore, a new indicator based on the distribution of citations is suggested. Accordingly, the publications are classified into citation categories, of which lower limits are given as 0, and (2n + 1), whereas the upper limits as 2n (n = 0, 2, 3, etc.). The citations distribution score (CDS) index is defined as the sum of weighted numbers of publications in the individual categories. The CDS-index increases logarithmically with the increasing number of citations. The citation distribution rate indicator is introduced by relating the actual CDS-index to the possible maximum. Several size-dependent and size-independent indicators were calculated. It has been concluded that relevant, already accepted scientometric indicators may validate novel indices through resulting in similar conclusions ("converging validation of indicators").

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