Search (29 results, page 1 of 2)

  • × theme_ss:"Visualisierung"
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  1. Beagle, D.: Visualizing keyword distribution across multidisciplinary c-space (2003) 0.01 
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    Abstract
    But what happens to this awareness in a digital library? Can discursive formations be represented in cyberspace, perhaps through diagrams in a visualization interface? And would such a schema be helpful to a digital library user? To approach this question, it is worth taking a moment to reconsider what Radford is looking at. First, he looks at titles to see how the books cluster. To illustrate, I scanned one hundred books on the shelves of a college library under subclass HT 101-395, defined by the LCC subclass caption as Urban groups. The City. Urban sociology. Of the first 100 titles in this sequence, fifty included the word "urban" or variants (e.g. "urbanization"). Another thirty-five used the word "city" or variants. These keywords appear to mark their titles as the heart of this discursive formation. The scattering of titles not using "urban" or "city" used related terms such as "town," "community," or in one case "skyscrapers." So we immediately see some empirical correlation between keywords and classification. But we also see a problem with the commonly used search technique of title-keyword. A student interested in urban studies will want to know about this entire subclass, and may wish to browse every title available therein. A title-keyword search on "urban" will retrieve only half of the titles, while a search on "city" will retrieve just over a third. There will be no overlap, since no titles in this sample contain both words. The only place where both words appear in a common string is in the LCC subclass caption, but captions are not typically indexed in library Online Public Access Catalogs (OPACs). In a traditional library, this problem is mitigated when the student goes to the shelf looking for any one of the books and suddenly discovers a much wider selection than the keyword search had led him to expect. But in a digital library, the issue of non-retrieval can be more problematic, as studies have indicated. Micco and Popp reported that, in a study funded partly by the U.S. Department of Education, 65 of 73 unskilled users searching for material on U.S./Soviet foreign relations found some material but never realized they had missed a large percentage of what was in the database.
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  2. Palm, F.: QVIZ : Query and context based visualization of time-spatial cultural dynamics (2007) 0.01 
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    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
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  3. Graphic details : a scientific study of the importance of diagrams to science (2016) 0.00 
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    Content
    As the team describe in a paper posted (http://arxiv.org/abs/1605.04951) on arXiv, they found that figures did indeed matter-but not all in the same way. An average paper in PubMed Central has about one diagram for every three pages and gets 1.67 citations. Papers with more diagrams per page and, to a lesser extent, plots per page tended to be more influential (on average, a paper accrued two more citations for every extra diagram per page, and one more for every extra plot per page). By contrast, including photographs and equations seemed to decrease the chances of a paper being cited by others. That agrees with a study from 2012, whose authors counted (by hand) the number of mathematical expressions in over 600 biology papers and found that each additional equation per page reduced the number of citations a paper received by 22%. This does not mean that researchers should rush to include more diagrams in their next paper. Dr Howe has not shown what is behind the effect, which may merely be one of correlation, rather than causation. It could, for example, be that papers with lots of diagrams tend to be those that illustrate new concepts, and thus start a whole new field of inquiry. Such papers will certainly be cited a lot. On the other hand, the presence of equations really might reduce citations. Biologists (as are most of those who write and read the papers in PubMed Central) are notoriously mathsaverse. If that is the case, looking in a physics archive would probably produce a different result.
  4. Collins, C.: WordNet explorer : applying visualization principles to lexical semantics (2006) 0.00 
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  5. Eckert, K: ¬The ICE-map visualization (2011) 0.00 
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  6. Denton, W.: On dentographs, a new method of visualizing library collections (2012) 0.00 
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  7. Wattenberg, M.; Viégas, F.; Johnson, I.: How to use t-SNE effectively (2016) 0.00 
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  8. Maaten, L. van den: Learning a parametric embedding by preserving local structure (2009) 0.00 
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  9. Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014) 0.00 
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  10. Fowler, R.H.; Wilson, B.A.; Fowler, W.A.L.: Information navigator : an information system using associative networks for display and retrieval (1992) 0.00 
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  11. Slavic, A.: Interface to classification : some objectives and options (2006) 0.00 
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  12. Barton, P.: ¬A missed opportunity : why the benefits of information visualisation seem still out of sight (2005) 0.00 
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  13. Braun, S.: Manifold: a custom analytics platform to visualize research impact (2015) 0.00 
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  14. Lamb, I.; Larson, C.: Shining a light on scientific data : building a data catalog to foster data sharing and reuse (2016) 0.00 
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  15. Kraker, P.; Kittel, C,; Enkhbayar, A.: Open Knowledge Maps : creating a visual interface to the world's scientific knowledge based on natural language processing (2016) 0.00 
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  16. Wu, Y.; Bai, R.: ¬An event relationship model for knowledge organization and visualization (2017) 0.00 
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  17. Maaten, L. van den; Hinton, G.: Visualizing non-metric similarities in multiple maps (2012) 0.00 
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  18. Linden, E.J. van der; Vliegen, R.; Wijk, J.J. van: Visual Universal Decimal Classification (2007) 0.00 
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  19. Xiaoyue M.; Cahier, J.-P.: Iconic categorization with knowledge-based "icon systems" can improve collaborative KM (2011) 0.00 
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  20. Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010) 0.00 
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