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Delsey, T.: ¬The Making of RDA (2016)
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- Date
- 17. 5.2016 19:22:40
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Wattenberg, M.; Viégas, F.; Johnson, I.: How to use t-SNE effectively (2016)
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- Abstract
- Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively. We'll walk through a series of simple examples to illustrate what t-SNE diagrams can and cannot show. The t-SNE technique really is useful-but only if you know how to interpret it.
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Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014)
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- Abstract
- The paper investigates the acceleration of t-SNE-an embedding technique that is commonly used for the visualization of high-dimensional data in scatter plots-using two tree-based algorithms. In particular, the paper develops variants of the Barnes-Hut algorithm and of the dual-tree algorithm that approximate the gradient used for learning t-SNE embeddings in O(N*logN). Our experiments show that the resulting algorithms substantially accelerate t-SNE, and that they make it possible to learn embeddings of data sets with millions of objects. Somewhat counterintuitively, the Barnes-Hut variant of t-SNE appears to outperform the dual-tree variant.
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Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010)
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Maaten, L. van den; Hinton, G.: Visualizing non-metric similarities in multiple maps (2012)
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- Abstract
- Techniques for multidimensional scaling visualize objects as points in a low-dimensional metric map. As a result, the visualizations are subject to the fundamental limitations of metric spaces. These limitations prevent multidimensional scaling from faithfully representing non-metric similarity data such as word associations or event co-occurrences. In particular, multidimensional scaling cannot faithfully represent intransitive pairwise similarities in a visualization, and it cannot faithfully visualize "central" objects. In this paper, we present an extension of a recently proposed multidimensional scaling technique called t-SNE. The extension aims to address the problems of traditional multidimensional scaling techniques when these techniques are used to visualize non-metric similarities. The new technique, called multiple maps t-SNE, alleviates these problems by constructing a collection of maps that reveal complementary structure in the similarity data. We apply multiple maps t-SNE to a large data set of word association data and to a data set of NIPS co-authorships, demonstrating its ability to successfully visualize non-metric similarities.
-
Guidi, F.; Sacerdoti Coen, C.: ¬A survey on retrieval of mathematical knowledge (2015)
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- Date
- 22. 2.2017 12:51:57
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Sojka, P.; Liska, M.: ¬The art of mathematics retrieval (2011)
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- Content
- Vgl.: DocEng2011, September 19-22, 2011, Mountain View, California, USA Copyright 2011 ACM 978-1-4503-0863-2/11/09
- Date
- 22. 2.2017 13:00:42
-
Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016)
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Mitchell, J.S.; Zeng, M.L.; Zumer, M.: Modeling classification systems in multicultural and multilingual contexts (2012)
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- Abstract
- This paper reports on the second part of an initiative of the authors on researching classification systems with the conceptual model defined by the Functional Requirements for Subject Authority Data (FRSAD) final report. In an earlier study, the authors explored whether the FRSAD conceptual model could be extended beyond subject authority data to model classification data. The focus of the current study is to determine if classification data modeled using FRSAD can be used to solve real-world discovery problems in multicultural and multilingual contexts. The paper discusses the relationships between entities (same type or different types) in the context of classification systems that involve multiple translations and /or multicultural implementations. Results of two case studies are presented in detail: (a) two instances of the DDC (DDC 22 in English, and the Swedish-English mixed translation of DDC 22), and (b) Chinese Library Classification. The use cases of conceptual models in practice are also discussed.
-
Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013)
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- Date
- 17.12.2013 11:02:22
-
Lange, C.; Mossakowski, T.; Galinski, C.; Kutz, O.: Making heterogeneous ontologies interoperable through standardisation : a Meta Ontology Language to be standardised: Ontology Integration and Interoperability (OntoIOp) (2011)
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Aerts, D.; Broekaert, J.; Sozzo, S.; Veloz, T.: Meaning-focused and quantum-inspired information retrieval (2013)
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Perovsek, M.; Kranjca, J.; Erjaveca, T.; Cestnika, B.; Lavraca, N.: TextFlows : a visual programming platform for text mining and natural language processing (2016)
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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)
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Mäkelä, E.; Hyvönen, E.; Ruotsalo, T.: How to deal with massively heterogeneous cultural heritage data : lessons learned in CultureSampo (2012)
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Metzinger, T.: Why Is Virtual Reality interesting for philosophers? (2018)
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Donahue, J.; Hendricks, L.A.; Guadarrama, S.; Rohrbach, M.; Venugopalan, S.; Saenko, K.; Darrell, T.: Long-term recurrent convolutional networks for visual recognition and description (2014)
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Rajasurya, S.; Muralidharan, T.; Devi, S.; Swamynathan, S.: Semantic information retrieval using ontology in university domain (2012)
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Müller, B.; Poley, C.; Pössel, J.; Hagelstein, A.; Gübitz, T.: LIVIVO - the vertical search engine for life sciences (2017)
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Standage, T.: Information overload is nothing new (2018)
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