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  1. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.13
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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
  2. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.05
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    Date
    12. 2.2011 17:35:22
  3. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.04
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    Abstract
    PageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor alpha that spreads uniformly part of the rank. The choice of alpha is eminently empirical, and in most cases the original suggestion alpha=0.85 by Brin and Page is still used. Recently, however, the behaviour of PageRank with respect to changes in alpha was discovered to be useful in link-spam detection. Moreover, an analytical justification of the value chosen for alpha is still missing. In this paper, we give the first mathematical analysis of PageRank when alpha changes. In particular, we show that, contrarily to popular belief, for real-world graphs values of alpha close to 1 do not give a more meaningful ranking. Then, we give closed-form formulae for PageRank derivatives of any order, and an extension of the Power Method that approximates them with convergence O(t**k*alpha**t) for the k-th derivative. Finally, we show a tight connection between iterated computation and analytical behaviour by proving that the k-th iteration of the Power Method gives exactly the PageRank value obtained using a Maclaurin polynomial of degree k. The latter result paves the way towards the application of analytical methods to the study of PageRank.
    Date
    16. 1.2016 10:22:28
  4. Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006) 0.04
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    Date
    3.12.2016 18:39:22
  5. Delsey, T.: ¬The Making of RDA (2016) 0.04
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    Date
    17. 5.2016 19:22:40
  6. Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978) 0.04
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    Source
    https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H
  7. Open MIND (2015) 0.03
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    Date
    27. 1.2015 11:48:22
    Editor
    Metzinger, T. u.. J.M. Windt
  8. Wattenberg, M.; Viégas, F.; Johnson, I.: How to use t-SNE effectively (2016) 0.03
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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.
  9. Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014) 0.03
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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.
  10. Baker, T.: ¬A grammar of Dublin Core (2000) 0.03
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    Date
    26.12.2011 14:01:22
  11. Baker, T.; Dekkers, M.; Heery, R.; Patel, M.; Salokhe, G.: What Terms Does Your Metadata Use? : Application Profiles as Machine-Understandable Narratives (2002) 0.03
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    Content
    Teil eines Sonderheftes: Selected papers from the Dublin Core 2001 Conference. Ed. T. Koch
  12. Wen, D.; Sakaguchi, T.; Sugimoto, S.; Tabata, K.: Multilingual Access to Dublin Core Metadata of ULIS Library (2002) 0.03
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    Content
    Teil eines Sonderheftes: Selected papers from the Dublin Core 2001 Conference. Ed. T. Koch
  13. Franklin, B.; Plum, T.: Library usage patterns in the electronic information environment (2004) 0.03
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  14. Koch, T.: Browsing and searching Internet resources (1996) 0.03
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  15. Page, L.; Brin, S.; Motwani, R.; Winograd, T.: ¬The PageRank citation ranking : Bringing order to the Web (1999) 0.03
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  16. DeKlerk, T.: Perspective on names in the South African Nation Bibliography : past, present and future (2001) 0.03
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  17. Maaten, L. van den: Learning a parametric embedding by preserving local structure (2009) 0.03
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    Abstract
    The paper presents a new unsupervised dimensionality reduction technique, called parametric t-SNE, that learns a parametric mapping between the high-dimensional data space and the low-dimensional latent space. Parametric t-SNE learns the parametric mapping in such a way that the local structure of the data is preserved as well as possible in the latent space. We evaluate the performance of parametric t-SNE in experiments on three datasets, in which we compare it to the performance of two other unsupervised parametric dimensionality reduction techniques. The results of experiments illustrate the strong performance of parametric t-SNE, in particular, in learning settings in which the dimensionality of the latent space is relatively low.
  18. Mitchell, J.S.: DDC 22 : an introduction (2003) 0.02
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    Abstract
    Dewey Decimal Classification and Relative Index, Edition 22 (DDC 22) will be issued simultaneously in print and web versions in July 2003. The new edition is the first full print update to the Dewey Decimal Classification system in seven years-it includes several significant updates and many new numbers and topics. DDC 22 also features some fundamental structural changes that have been introduced with the goals of promoting classifier efficiency and improving the DDC for use in a variety of applications in the web environment. Most importantly, the content of the new edition has been shaped by the needs and recommendations of Dewey users around the world. The worldwide user community has an important role in shaping the future of the DDC.
    Object
    DDC-22
  19. Maaten, L. van den; Hinton, G.: Visualizing data using t-SNE (2008) 0.02
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    Abstract
    We present a new technique called "t-SNE" that visualizes high-dimensional data by giving each datapoint a location in a two or three-dimensional map. The technique is a variation of Stochastic Neighbor Embedding (Hinton and Roweis, 2002) that is much easier to optimize, and produces significantly better visualizations by reducing the tendency to crowd points together in the center of the map. t-SNE is better than existing techniques at creating a single map that reveals structure at many different scales. This is particularly important for high-dimensional data that lie on several different, but related, low-dimensional manifolds, such as images of objects from multiple classes seen from multiple viewpoints. For visualizing the structure of very large data sets, we show how t-SNE can use random walks on neighborhood graphs to allow the implicit structure of all of the data to influence the way in which a subset of the data is displayed. We illustrate the performance of t-SNE on a wide variety of data sets and compare it with many other non-parametric visualization techniques, including Sammon mapping, Isomap, and Locally Linear Embedding. The visualizations produced by t-SNE are significantly better than those produced by the other techniques on almost all of the data sets.
  20. Bandholtz, T.; Schulte-Coerne, T.; Glaser, R.; Fock, J.; Keller, T.: iQvoc - open source SKOS(XL) maintenance and publishing tool (2010) 0.02
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