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Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014)
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Birmingham, J.: Internet search engines (1996)
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Qin, J.; Paling, S.: Converting a controlled vocabulary into an ontology : the case of GEM (2001)
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Strobel, S.: ¬The complete Linux kit : fully configured LINUX system kernel (1997)
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Zumer, M.; Clavel, G.: EDLproject : one more step towards the European digtial library (2007)
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- Vortrag anläasslich 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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Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978)
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Heflin, J.; Hendler, J.: Semantic interoperability on the Web (2000)
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Schreiber, G.; Amin, A.; Assem, M. van; Boer, V. de; Hardman, L.; Hildebrand, M.; Hollink, L.; Huang, Z.; Kersen, J. van; Niet, M. de; Omelayenko, B.; Ossenbruggen, J. van; Siebes, R.; Taekema, J.; Wielemaker, J.; Wielinga, B.: MultimediaN E-Culture demonstrator (2006)
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OWL Web Ontology Language Test Cases (2004)
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- Date
- 14. 8.2011 13:33:22
- Editor
- Carroll, J.J. u. J. de Roo
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Sojka, P.; Liska, M.: ¬The art of mathematics retrieval (2011)
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- Vgl.: DocEng2011, September 19-22, 2011, Mountain View, California, USA Copyright 2011 ACM 978-1-4503-0863-2/11/09
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- 22. 2.2017 13:00:42
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Greenberg, J.; Pattuelli, M.; Parsia, B.; Robertson, W.: Author-generated Dublin Core Metadata for Web Resources : A Baseline Study in an Organization (2002)
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Riley, J.: Understanding metadata : what is metadata, and what is it for? (2017)
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Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval
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Mao, J.; Xu, W.; Yang, Y.; Wang, J.; Yuille, A.L.: Explain images with multimodal recurrent neural networks (2014)
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- Abstract
- In this paper, we present a multimodal Recurrent Neural Network (m-RNN) model for generating novel sentence descriptions to explain the content of images. It directly models the probability distribution of generating a word given previous words and the image. Image descriptions are generated by sampling from this distribution. The model consists of two sub-networks: a deep recurrent neural network for sentences and a deep convolutional network for images. These two sub-networks interact with each other in a multimodal layer to form the whole m-RNN model. The effectiveness of our model is validated on three benchmark datasets (IAPR TC-12 [8], Flickr 8K [28], and Flickr 30K [13]). Our model outperforms the state-of-the-art generative method. In addition, the m-RNN model can be applied to retrieval tasks for retrieving images or sentences, and achieves significant performance improvement over the state-of-the-art methods which directly optimize the ranking objective function for retrieval.
-
Electronic Dewey (1993)
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- Footnote
- Rez. in: Cataloging and classification quarterly 19(1994) no.1, S.134-137 (M. Carpenter). - Inzwischen existiert auch eine Windows-Version: 'Electronic Dewey for Windows', vgl. Knowledge organization 22(1995) no.1, S.17
-
Lynch, J.D.; Gibson, J.; Han, M.-J.: Analyzing and normalizing type metadata for a large aggregated digital library (2020)
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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.
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Schreiber, G.; Amin, A.; Assem, M. van; Boer, V. de; Hardman, L.; Hildebrand, M.; Omelayenko, B.; Ossenbruggen, J. van; Wielemaker, J.; Wielinga, B.; Tordai, A.; Aroyoa, L.: Semantic annotation and search of cultural-heritage collections : the MultimediaN E-Culture demonstrator (2008)
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-
Voß, J.: Classification of knowledge organization systems with Wikidata (2016)
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- Pages
- S.15-22
