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  • × theme_ss:"Semantic Web"
  • × type_ss:"a"
  1. Narock, T.; Zhou, L.; Yoon, V.: Semantic similarity of ontology instances using polarity mining (2013) 0.05 
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    Abstract
    Semantic similarity is vital to many areas, such as information retrieval. Various methods have been proposed with a focus on comparing unstructured text documents. Several of these have been enhanced with ontology; however, they have not been applied to ontology instances. With the growth in ontology instance data published online through, for example, Linked Open Data, there is an increasing need to apply semantic similarity to ontology instances. Drawing on ontology-supported polarity mining (OSPM), we propose an algorithm that enhances the computation of semantic similarity with polarity mining techniques. The algorithm is evaluated with online customer review data. The experimental results show that the proposed algorithm outperforms the baseline algorithm in multiple settings.
  2. Djioua, B.; Desclés, J.-P.; Alrahabi, M.: Searching and mining with semantic categories (2012) 0.04 
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    Abstract
    A new model is proposed to retrieve information by building automatically a semantic metatext structure for texts that allow searching and extracting discourse and semantic information according to certain linguistic categorizations. This paper presents approaches for searching and mining full text with semantic categories. The model is built up from two engines: The first one, called EXCOM (Djioua et al., 2006; Alrahabi, 2010), is an automatic system for text annotation, related to discourse and semantic maps, which are specification of general linguistic ontologies founded on the Applicative and Cognitive Grammar. The annotation layer uses a linguistic method called Contextual Exploration, which handles the polysemic values of a term in texts. Several 'semantic maps' underlying 'point of views' for text mining guide this automatic annotation process. The second engine uses semantic annotated texts, produced previously in order to create a semantic inverted index, which is able to retrieve relevant documents for queries associated with discourse and semantic categories such as definition, quotation, causality, relations between concepts, etc. (Djioua & Desclés, 2007). This semantic indexation process builds a metatext layer for textual contents. Some data and linguistic rules sets as well as the general architecture that extend third-party software are expressed as supplementary information.
  3. Finke, M.; Risch, J.: "Match Me If You Can" : Sammeln und semantisches Aufbereiten von Fußballdaten (2017) 0.04 
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    Abstract
    Interviews, Spielstatistiken oder Videoaufzeichnungen sind für Fußballfans zwar zahlreich im Internet verfügbar, aber auf viele verschiedene Websites verstreut. "Semantic Media Mining" verknüpft nun Fußballdaten aus unterschiedlichen Quellen, bereitet sie semantisch auf und führt sie auf einer einzigen Website zusammen. Dadurch dokumentieren und visualisieren wir mehr als 50 Jahre Fußballgeschichte mit über 500 Mannschaften und 40.000 Spielern der Champions League, sowie der 1. und 2. Bundesliga.
  4. Papadakis, I. et al.: Highlighting timely information in libraries through social and semantic Web technologies (2016) 0.02 
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    Source
    Metadata and semantics research: 10th International Conference, MTSR 2016, Göttingen, Germany, November 22-25, 2016, Proceedings. Eds.: E. Garoufallou
  5. 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
  6. Faaborg, A.; Lagoze, C.: Semantic browsing (2003) 0.01 
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    Source
    Research and advanced technology for digital libraries : 7th European Conference, proceedings / ECDL 2003, Trondheim, Norway, August 17-22, 2003
  7. Malmsten, M.: Making a library catalogue part of the Semantic Web (2008) 0.01 
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    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
  8. Schneider, R.: Web 3.0 ante portas? : Integration von Social Web und Semantic Web (2008) 0.01 
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    Date
    22. 1.2011 10:38:28
  9. Blumauer, A.; Pellegrini, T.: Semantic Web Revisited : Eine kurze Einführung in das Social Semantic Web (2009) 0.01 
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    Pages
    S.3-22
  10. Heflin, J.; Hendler, J.: Semantic interoperability on the Web (2000) 0.01 
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    Date
    11. 5.2013 19:22:18
  11. 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
  12. Franklin, R.A.: Re-inventing subject access for the semantic web (2003) 0.01 
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    Date
    30.12.2008 18:22:46
  13. Hooland, S. van; Verborgh, R.; Wilde, M. De; Hercher, J.; Mannens, E.; Wa, R.Van de: Evaluating the success of vocabulary reconciliation for cultural heritage collections (2013) 0.01 
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    Date
    22. 3.2013 19:29:20
  14. 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
  15. 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
  16. 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
  17. Subirats, I.; Prasad, A.R.D.; Keizer, J.; Bagdanov, A.: Implementation of rich metadata formats and demantic tools using DSpace (2008) 0.01 
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    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
  18. Shoffner, M.; Greenberg, J.; Kramer-Duffield, J.; Woodbury, D.: Web 2.0 semantic systems : collaborative learning in science (2008) 0.01 
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    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
  19. Brunetti, J.M.; Roberto García, R.: User-centered design and evaluation of overview components for semantic data exploration (2014) 0.01 
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    Date
    20. 1.2015 18:30:22
  20. Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014) 0.01 
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    Date
    20. 1.2015 18:30:22

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