-
Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009)
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- Date
- 31. 7.2010 16:58:22
- Pages
- S.41-54
-
Priss, U.: Faceted information representation (2000)
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- Date
- 22. 1.2016 17:47:06
- Pages
- S.84-94
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Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Date
- 11. 2.2011 18:22:58
- Source
- Information - Wissenschaft und Praxis. 56(2005) H.5/6, S.281-290
-
Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006)
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- Pages
- S.426-437
- Source
- Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
-
Renear, A.H.; Wickett, K.M.; Urban, R.J.; Dubin, D.; Shreeves, S.L.: Collection/item metadata relationships (2008)
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- Pages
- S.80-89
- 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
-
Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009)
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- Date
- 1. 8.2010 12:35:22
- Pages
- S.203-214
-
Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006)
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- Date
- 3.12.2016 18:39:22
-
Zeng, M.L.; Fan, W.; Lin, X.: SKOS for an integrated vocabulary structure (2008)
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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.
- Pages
- S.200-201
- 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
-
Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007)
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- Pages
- S.192-205
- Source
- Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
-
Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008)
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- Date
- 28.11.2016 12:43:22
-
Weller, K.: Kooperativer Ontologieaufbau (2006)
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- Pages
- S.227-234
-
Grzonkowski, S.; Kruk, S.R.; Gzella, A.; Demczuk, J.; McDaniel, B.: Community-aware ontologies (2009)
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- Pages
- S.123-135
-
Aitken, S.; Reid, S.: Evaluation of an ontology-based information retrieval tool (2000)
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-
Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004)
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- Abstract
- Ontologies will play a central role in the development of the Semantic Web. It is unrealistic to assume that such ontologies will be developed from scratch. Rather, we assume that existing resources such as thesauri and lexical data bases will be reused in the development of ontologies for the Semantic Web. In this paper we describe a method for converting existing source material to a representation that is compatible with Semantic Web languages such as RDF(S) and OWL. The method is illustrated with three case studies: converting Wordnet, AAT and MeSH to RDF(S) and OWL.
- Source
- Proceedings of the First European Semantic Web Symposium (ESWS2004), Eds.: C. Bussler, J. Davies, D. Fensel and R. Studer. 2004. S.299-311
-
Güldner, D.; Wich, M.; Keil, S.: Überblick über aktuelle Programme zur Erschaffung von Ontologien (2006)
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- Source
- Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.337-342
-
Loehrlein, A.; Jacob, E.K.; Lee, S.; Yang, K.: Development of heuristics in a hybrid approach to faceted classification (2006)
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- Pages
- S.255-261
-
Fensel, D.; Staab, S.; Studer, R.; Harmelen, F. van; Davies, J.: ¬A future perspective : exploiting peer-to-peer and the Semantic Web for knowledge management (2004)
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- Pages
- S.245-264
-
Panzer, M.; Zeng, M.L.: Modeling classification systems in SKOS : Some challenges and best-practice (2009)
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- Pages
- 12 S. (S.3-14)
-
Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004)
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- Abstract
- This paper describes a method for converting existing thesauri and related resources from their native format to RDF(S) and OWL. The method identifies four steps in the conversion process. In each step, decisions have to be taken with respect to the syntax or semantics of the resulting representation. Each step is supported through a number of guidelines. The method is illustrated through conversions of two large thesauri: MeSH and WordNet.
- Pages
- S.17-31
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Hepp, M.; Bruijn, J. de: GenTax : a generic methodology for deriving OWL and RDF-S ontologies from hierarchical classifications, thesauri, and inconsistent taxonomies (2007)
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- Abstract
- Hierarchical classifications, thesauri, and informal taxonomies are likely the most valuable input for creating, at reasonable cost, non-toy ontologies in many domains. They contain, readily available, a wealth of category definitions plus a hierarchy, and they reflect some degree of community consensus. However, their transformation into useful ontologies is not as straightforward as it appears. In this paper, we show that (1) it often depends on the context of usage whether an informal hierarchical categorization schema is a classification, a thesaurus, or a taxonomy, and (2) present a novel methodology for automatically deriving consistent RDF-S and OWL ontologies from such schemas. Finally, we (3) demonstrate the usefulness of this approach by transforming the two e-business categorization standards eCl@ss and UNSPSC into ontologies that overcome the limitations of earlier prototypes. Our approach allows for the script-based creation of meaningful ontology classes for a particular context while preserving the original hierarchy, even if the latter is not a real subsumption hierarchy in this particular context. Human intervention in the transformation is limited to checking some conceptual properties and identifying frequent anomalies, and the only input required is an informal categorization plus a notion of the target context. In particular, the approach does not require instance data, as ontology learning approaches would usually do.
- Pages
- S.129-144
