-
Palm, F.: QVIZ : Query and context based visualization of time-spatial cultural dynamics (2007)
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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".
- Date
- 20. 1.2008 17:28:29
-
Slavic, A.: Interface to classification : some objectives and options (2006)
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- Theme
- Klassifikationssysteme im Online-Retrieval
-
Eckert, K: ¬The ICE-map visualization (2011)
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- Theme
- Konzeption und Anwendung des Prinzips Thesaurus
-
Maaten, L. van den: Learning a parametric embedding by preserving local structure (2009)
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- Source
- Proceedings of the Twelfth International Conference on Artificial Intelligence & Statistics (AI-STATS), JMLR W&CP 5, 2009. S.384-391
-
Linden, E.J. van der; Vliegen, R.; Wijk, J.J. van: Visual Universal Decimal Classification (2007)
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- Source
- Extensions and corrections to the UDC. 29(2007), S.297-300
-
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)
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- Content
- Beitrag in einem Themenschwerpunkt 'Computerlinguistik und Bibliotheken'. Vgl.: http://0277.ch/ojs/index.php/cdrs_0277/article/view/157/355.
-
Xiaoyue M.; Cahier, J.-P.: Iconic categorization with knowledge-based "icon systems" can improve collaborative KM (2011)
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- Source
- Collaboration Technologies and Systems (CTS), 2011 International Conference on Collaboration Technologies and Systems (CTS 2011), May 23-27, 2011,The Sheraton University City Hotel, Philadelphia, Pennsylvania, USA
-
Beagle, D.: Visualizing keyword distribution across multidisciplinary c-space (2003)
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- Theme
- Klassifikationssysteme im Online-Retrieval
-
Fowler, R.H.; Wilson, B.A.; Fowler, W.A.L.: Information navigator : an information system using associative networks for display and retrieval (1992)
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- Series
- Report NAG9-551, No. 92-1
-
Maaten, L. van den; Hinton, G.: Visualizing non-metric similarities in multiple maps (2012)
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- Source
- Machine learning. 87(2012) no.1, S.33-55
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Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010)
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- Abstract
- Documents in rich text corpora usually contain multiple facets of information. For example, an article about a specific disease often consists of different facets such as symptom, treatment, cause, diagnosis, prognosis, and prevention. Thus, documents may have different relations based on different facets. Powerful search tools have been developed to help users locate lists of individual documents that are most related to specific keywords. However, there is a lack of effective analysis tools that reveal the multifaceted relations of documents within or cross the document clusters. In this paper, we present FacetAtlas, a multifaceted visualization technique for visually analyzing rich text corpora. FacetAtlas combines search technology with advanced visual analytical tools to convey both global and local patterns simultaneously. We describe several unique aspects of FacetAtlas, including (1) node cliques and multifaceted edges, (2) an optimized density map, and (3) automated opacity pattern enhancement for highlighting visual patterns, (4) interactive context switch between facets. In addition, we demonstrate the power of FacetAtlas through a case study that targets patient education in the health care domain. Our evaluation shows the benefits of this work, especially in support of complex multifaceted data analysis.
