Search (22 results, page 1 of 2)

OWL Web Ontology Language Test Cases (2004) 0.06

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Date: 14. 8.2011 13:33:22
Type: n

Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.05

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Content: Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.

Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.04

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Date: 16.11.2018 14:22:01

Hori, M.; Euzenat, J.; Patel-Schneider, P.F.: OWL Web Ontology Language XML Presentation Syntax (2003) 0.02

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Type: n

OWL Web Ontology Language Use Cases and Requirements (2004) 0.02

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Type: n

OWL 2 Web Ontology Language Document Overview (2009) 0.02

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Type: n

RDF/XML Syntax Specification (Revised) : W3C Recommendation 10 February 2004 (2004) 0.02
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```
Abstract

The Resource Description Framework (RDF) is a general-purpose language for representing information in the Web. This document defines an XML syntax for RDF called RDF/XML in terms of Namespaces in XML, the XML Information Set and XML Base. The formal grammar for the syntax is annotated with actions generating triples of the RDF graph as defined in RDF Concepts and Abstract Syntax. The triples are written using the N-Triples RDF graph serializing format which enables more precise recording of the mapping in a machine processable form. The mappings are recorded as tests cases, gathered and published in RDF Test Cases.

Bechhofer, S.; Harmelen, F. van; Hendler, J.; Horrocks, I.; McGuinness, D.L.; Patel-Schneider, P.F.; Stein, L.A.: OWL Web Ontology Language Reference (2004) 0.02

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Type: n

Suchanek, F.M.; Kasneci, G.; Weikum, G.: YAGO: a large ontology from Wikipedia and WordNet (2008) 0.01
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Abstract

This article presents YAGO, a large ontology with high coverage and precision. YAGO has been automatically derived from Wikipedia and WordNet. It comprises entities and relations, and currently contains more than 1.7 million entities and 15 million facts. These include the taxonomic Is-A hierarchy as well as semantic relations between entities. The facts for YAGO have been extracted from the category system and the infoboxes of Wikipedia and have been combined with taxonomic relations from WordNet. Type checking techniques help us keep YAGO's precision at 95%-as proven by an extensive evaluation study. YAGO is based on a clean logical model with a decidable consistency. Furthermore, it allows representing n-ary relations in a natural way while maintaining compatibility with RDFS. A powerful query model facilitates access to YAGO's data.

Köstlbacher, A. (Übers.): OWL Web Ontology Language Überblick (2004) 0.01

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Type: n

OWL Web Ontology Language Overview (2004) 0.01

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Type: n

OWL Web Ontology Language Semantics and Abstract Syntax (2004) 0.01

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Type: n

SKOS Simple Knowledge Organization System Primer (2009) 0.01

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Type: n

Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01

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Date: 31. 7.2010 16:58:22

OWL Web Ontology Language Guide (2004) 0.01

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Type: n

Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.01

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Date: 12. 2.2011 17:35:22

Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006) 0.01

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Source: Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006

Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010) 0.01

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Date: 26.12.2011 13:40:22

Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015) 0.01

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Source: Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22

Zeng, M.L.; Fan, W.; Lin, X.: SKOS for an integrated vocabulary structure (2008) 0.01
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Abstract

In order to transfer the Chinese Classified Thesaurus (CCT) into a machine-processable format and provide CCT-based Web services, a pilot study has been conducted in which a variety of selected CCT classes and mapped thesaurus entries are encoded with SKOS. OWL and RDFS are also used to encode the same contents for the purposes of feasibility and cost-benefit comparison. CCT is a collected effort led by the National Library of China. It is an integration of the national standards Chinese Library Classification (CLC) 4th edition and Chinese Thesaurus (CT). As a manually created mapping product, CCT provides for each of the classes the corresponding thesaurus terms, and vice versa. The coverage of CCT includes four major clusters: philosophy, social sciences and humanities, natural sciences and technologies, and general works. There are 22 main-classes, 52,992 sub-classes and divisions, 110,837 preferred thesaurus terms, 35,690 entry terms (non-preferred terms), and 59,738 pre-coordinated headings (Chinese Classified Thesaurus, 2005) Major challenges of encoding this large vocabulary comes from its integrated structure. CCT is a result of the combination of two structures (illustrated in Figure 1): a thesaurus that uses ISO-2788 standardized structure and a classification scheme that is basically enumerative, but provides some flexibility for several kinds of synthetic mechanisms Other challenges include the complex relationships caused by differences of granularities of two original schemes and their presentation with various levels of SKOS elements; as well as the diverse coordination of entries due to the use of auxiliary tables and pre-coordinated headings derived from combining classes, subdivisions, and thesaurus terms, which do not correspond to existing unique identifiers. The poster reports the progress, shares the sample SKOS entries, and summarizes problems identified during the SKOS encoding process. Although OWL Lite and OWL Full provide richer expressiveness, the cost-benefit issues and the final purposes of encoding CCT raise questions of using such approaches.

Source

Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas

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