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  • × theme_ss:"Semantic Web"
  1. Fluit, C.; Horst, H. ter; Meer, J. van der; Sabou, M.; Mika, P.: Spectacle (2004) 0.01
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  2. Wielinga, B.; Wielemaker, J.; Schreiber, G.; Assem, M. van: Methods for porting resources to the Semantic Web (2004) 0.01
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    Source
    Proceedings of the First European Semantic Web Symposium (ESWS2004), Eds.: C. Bussler, J. Davies, D. Fensel and R. Studer. 2004. S.299-311
  3. Menzel, C.: Knowledge representation, the World Wide Web, and the evolution of logic (2011) 0.01
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  4. 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
  5. Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018) 0.01
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    Date
    16.11.2018 14:22:01
  6. Metadata and semantics research : 7th Research Conference, MTSR 2013 Thessaloniki, Greece, November 19-22, 2013. Proceedings (2013) 0.01
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    Date
    17.12.2013 12:51:22
  7. OWL Web Ontology Language Guide (2004) 0.01
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    Editor
    Smith, M.K., C. Welty u. D.L. Mc Guinness
  8. Maltese, V.; Farazi, F.: Towards the integration of knowledge organization systems with the linked data cloud (2011) 0.01
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    Abstract
    In representing the shared view of all the people involved, building a knowledge organization system (KOS) from scratch is extremely costly, and it is therefore fundamental to reuse existing resources. This can be done by progressively extending the KOS with knowledge coming from similar KOSs and by promoting interoperability among them. The linked data initiative is indeed encouraging people to share and integrate their datasets into a giant network of interconnected resources. This enables different applications to interoperate and share their data. The integration should take into account the purpose of the datasets, however, and make explicit the semantics. In fact, the difference in the purpose is reflected in the difference in the semantics. With this paper we (a) highlight the potential problems that may arise by not taking into account purpose and semantics; (b) make clear how the difference in the purpose is reflected in totally different semantics and (c) provide an algorithm to translate from one semantics into another as a preliminary step towards the integration of ontologies designed for different purposes. This will allow reusing the ontologies even in contexts different from those in which they were designed.
  9. Lassalle, E.; Lassalle, E.: Semantic models in information retrieval (2012) 0.01
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    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  10. Ghorbel, H.; Bahri, A.; Bouaziz, R.: Fuzzy ontologies building platform for Semantic Web : FOB platform (2012) 0.01
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    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  11. Djioua, B.; Desclés, J.-P.; Alrahabi, M.: Searching and mining with semantic categories (2012) 0.01
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    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  12. Allocca, C.; Aquin, M.d'; Motta, E.: Impact of using relationships between ontologies to enhance the ontology search results (2012) 0.01
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  13. Ioannou, E.; Nejdl, W.; Niederée, C.; Velegrakis, Y.: Embracing uncertainty in entity linking (2012) 0.01
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  14. Maltese, V.; Farazi, F.: Towards the integration of knowledge organization systems with the linked data cloud (2011) 0.01
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    Abstract
    In representing the shared view of all the people involved, building a Knowledge Organization System (KOS) from scratch is extremely costly, and it is therefore fundamental to reuse existing resources. This can be done by progressively extending the KOS with knowledge coming from similar KOS and by promoting interoperability among them. The linked data initiative is indeed fostering people to share and integrate their datasets into a giant network of interconnected resources. This enables different applications to interoperate and share their data. However, the integration should take into account the purpose of the datasets and make explicit the semantics. In fact, the difference in the purpose is reflected in the difference in the semantics. With this paper we (a) highlight the potential problems that may arise by not taking into account purpose and semantics, (b) make clear how the difference in the purpose is reflected in totally different semantics and (c) provide an algorithm to translate from one semantic into another as a preliminary step towards the integration of ontologies designed for different purposes. This will allow reusing the ontologies even in contexts different from those in which they were designed.
  15. Pattuelli, C.; Rubinow, S.: ¬The knowledge organization of DBpedia : a case study (2013) 0.01
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  16. Harlow, C.: Data munging tools in Preparation for RDF : Catmandu and LODRefine (2015) 0.01
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  17. Rousset, M.-C.; Atencia, M.; David, J.; Jouanot, F.; Ulliana, F.; Palombi, O.: Datalog revisited for reasoning in linked data (2017) 0.01
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  18. Bruhn, C.; Syn, S.Y.: Pragmatic thought as a philosophical foundation for collaborative tagging and the Semantic Web (2018) 0.01
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  19. Isaac, A.: Aligning thesauri for an integrated access to Cultural Heritage Resources (2007) 0.01
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    Abstract
    Currently, a number of efforts are being carried out to integrate collections from different institutions and containing heterogeneous material. Examples of such projects are The European Library [1] and the Memory of the Netherlands [2]. A crucial point for the success of these is the availability to provide a unified access on top of the different collections, e.g. using one single vocabulary for querying or browsing the objects they contain. This is made difficult by the fact that the objects from different collections are often described using different vocabularies - thesauri, classification schemes - and are therefore not interoperable at the semantic level. To solve this problem, one can turn to semantic links - mappings - between the elements of the different vocabularies. If one knows that a concept C from a vocabulary V is semantically equivalent to a concept to a concept D from vocabulary W, then an appropriate search engine can return all the objects that were indexed against D for a query for objects described using C. We thus have an access to other collections, using a single one vocabulary. This is however an ideal situation, and hard alignment work is required to reach it. Several projects in the past have tried to implement such a solution, like MACS [3] and Renardus [4]. They have demonstrated very interesting results, but also highlighted the difficulty of aligning manually all the different vocabularies involved in practical cases, which sometimes contain hundreds of thousands of concepts. To alleviate this problem, a number of tools have been proposed in order to provide with candidate mappings between two input vocabularies, making alignment a (semi-) automatic task. Recently, the Semantic Web community has produced a lot of these alignment tools'. Several techniques are found, depending on the material they exploit: labels of concepts, structure of vocabularies, collection objects and external knowledge sources. Throughout our presentation, we will present a concrete heterogeneity case where alignment techniques have been applied to build a (pilot) browser, developed in the context of the STITCH project [5]. This browser enables a unified access to two collections of illuminated manuscripts, using the description vocabulary used in the first collection, Mandragore [6], or the one used by the second, Iconclass [7]. In our talk, we will also make the point for using unified representations the vocabulary semantic and lexical information. Additionally to ease the use of the alignment tools that have these vocabularies as input, turning to a standard representation format helps designing applications that are more generic, like the browser we demonstrate. We give pointers to SKOS [8], an open and web-enabled format currently developed by the Semantic Web community.
  20. Knitting the semantic Web (2007) 0.01
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    Content
    Enthält die Beiträge: Greenberg, J., E.M. Méndez Rodríguez: Introduction: toward a more library-like Web via semantic knitting (S.1-8). - Campbell, D.G.: The birth of the new Web: a Foucauldian reading (S.9-20). - McCathieNevile, C., E.M. Méndez Rodríguez: Library cards for the 21st century (S.21-45). - Harper, C.A., B.B. Tillett: Library of Congress controlled vocabularies and their application to the Semantic Web (S.47-68). - Miles, A., J.R. Pérez-Agüera: SKOS: Simple Knowledge Organisation for the Web (S.69-83). - Tennis, J.T.: Scheme versioning in the Semantic Web (S.85-104). - Rogers, G.P.: Roles for semantic technologies and tools in libraries (S.105-125). - Severiens, T., C. Thiemann: RDF database for PhysNet and similar portals (S.127-147). - Michon, J.: Biomedicine and the Semantic Web: a knowledge model for visual phenotype (S.149-160). - Liang, A., G. Salokhe u. M. Sini u.a.: Towards an infrastructure for semantic applications: methodologies for semantic integration of heterogeneous resources (S.161-189). - Graves, M., A. Constabaris u. D. Brickley: FOAF: connecting people on the Semantic Web (S.191-202). - Greenberg, J.: Advancing Semantic Web via library functions (S.203-225). - Weibel, S.L.: Social Bibliography: a personal perspective on libraries and the Semantic Web (S.227-236)

Languages

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Types

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  • el 19
  • m 12
  • s 6
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