-
Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014)
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- Date
- 23. 7.2017 13:49:22
-
Baião Salgado Silva, G.; Lima, G.Â. Borém de Oliveira: Using topic maps in establishing compatibility of semantically structured hypertext contents (2012)
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- Abstract
- Considering the characteristics of hypertext systems and problems such as cognitive overload and the disorientation of users, this project studies subject hypertext documents that have undergone conceptual structuring using facets for content representation and improvement of information retrieval during navigation. The main objective was to assess the possibility of the application of topic map technology for automating the compatibilization process of these structures. For this purpose, two dissertations from the UFMG Information Science Post-Graduation Program were adopted as samples. Both dissertations had been duly analyzed and structured on the MHTX (Hypertextual Map) prototype database. The faceted structures of both dissertations, which had been represented in conceptual maps, were then converted into topic maps. It was then possible to use the merge property of the topic maps to promote the semantic interrelationship between the maps and, consequently, between the hypertextual information resources proper. The merge results were then analyzed in the light of theories dealing with the compatibilization of languages developed within the realm of information technology and librarianship from the 1960s on. The main goals accomplished were: (a) the detailed conceptualization of the merge process of the topic maps, considering the possible compatibilization levels and the applicability of this technology in the integration of faceted structures; and (b) the production of a detailed sequence of steps that may be used in the implementation of topic maps based on faceted structures.
- Date
- 22. 2.2013 11:39:23
-
Koopman, B.; Zuccon, G.; Bruza, P.; Sitbon, L.; Lawley, M.: Information retrieval as semantic inference : a graph Inference model applied to medical search (2016)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Madalli, D.P.; Chatterjee, U.; Dutta, B.: ¬An analytical approach to building a core ontology for food (2017)
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-
Zhitomirsky-Geffet, M.; Bar-Ilan, J.: Towards maximal unification of semantically diverse ontologies for controversial domains (2014)
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- Date
- 20. 1.2015 18:30:22
-
Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014)
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- Date
- 20. 1.2015 18:30:22
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Weller, K.: Ontologien (2013)
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- Source
- Grundlagen der praktischen Information und Dokumentation. Handbuch zur Einführung in die Informationswissenschaft und -praxis. 6., völlig neu gefaßte Ausgabe. Hrsg. von R. Kuhlen, W. Semar u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried
-
El idrissi esserhrouchni, O. et al.; Frikh, B.; Ouhbi, B.: OntologyLine : a new framework for learning non-taxonomic relations of domain ontology (2016)
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-
Öttl, S.; Streiff, D.; Stettler, N.; Studer, M.: Aufbau einer Testumgebung zur Ermittlung signifikanter Parameter bei der Ontologieabfrage (2010)
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- Abstract
- Der Einsatz von semantischen Technologien ist mittlerweile ein etabliertes Mittel zur Optimierung von Information-Retrieval-Systemen. Obwohl der Einsatz von Ontologien für verschiedene Anwendungsbereiche wie beispielsweise zur Query-Expansion (Bhogal et al. 2007), zur Strukturierung von Benutzeroberflächen bzw. zur Dialoggestaltung (z. B. Garcia & Sicilia 2003; Liu et al. 2005; Lopez et al. 2006; Paulheim 2009; Paulheim & Probst 2010), in Recommendersystemen (z. B. Taehee et al. 2006; Cantador et al. 2008; Middleton et al. 2001; Middleton et al. 2009) usw. rege erforscht wird, gibt es noch kaum Bestrebungen, die einzelnen Abfragemethodiken für Ontologien systematisch zu untersuchen. Bei der Abfrage von Ontologien geht es in erster Linie darum, Zusammenhänge zwischen Begriffen zu ermitteln, indem hierarchische (Classes und Individuals), semantische (Object Properties) und ergänzende (Datatype Properties) Beziehungen abgefragt oder logische Verknüpfungen abgeleitet werden. Hierbei werden sogenannte Reasoner für die Ableitungen und als Abfragesprache SPARQL (seltener auch XPath) eingesetzt. Ein weiterer, weniger oft eingesetzter, vielversprechender Ansatz findet sich bei Hoser et al. (2006) und Weng & Chang (2008), die Techniken der Sozialen Netzwerkanalyse zur Auswertung von Ontologien miteinsetzen (Semantic Network Analysis). Um die Abfrage von Ontologien sowie Kombinationen der unterschiedlichen Abfragemöglichkeiten systematisch untersuchen zu können, wurde am SII eine entsprechende Testumgebung entwickelt, die in diesem Beitrag genauer vorgestellt werden soll.
-
Blobel, B.: Ontologies, knowledge representation, artificial intelligence : hype or prerequisite for international pHealth interoperability? (2011)
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-
Boer, V. de; Wielemaker, J.; Gent, J. van; Hildebrand, M.; Isaac, A.; Ossenbruggen, J. van; Schreiber, G.: Supporting linked data production for cultural heritage institutes : the Amsterdam Museum case study (2012)
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-
Hoppe, T.: Semantische Filterung : ein Werkzeug zur Steigerung der Effizienz im Wissensmanagement (2013)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Bold, N.; Kim, W.-J.; Yang, J.-D.: Converting object-based thesauri into XML Topic Maps (2010)
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-
Werrmann, J.: Modellierung im Kontext : Ontologie-basiertes Information Retrieval (2011)
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-
Boteram, F.; Gödert, W.; Hubrich, J.: Semantic interoperability and retrieval paradigms (2010)
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-
Finke, M.; Risch, J.: "Match Me If You Can" : Sammeln und semantisches Aufbereiten von Fußballdaten (2017)
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Girju, R.; Beamer, B.; Rozovskaya, A.; Fister, A.; Bhat, S.: ¬A knowledge-rich approach to identifying semantic relations between nominals (2010)
0.01
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-
Glimm, B.; Hogan, A.; Krötzsch, M.; Polleres, A.: OWL: Yet to arrive on the Web of Data? (2012)
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-
Xu, Y.; Li, G.; Mou, L.; Lu, Y.: Learning non-taxonomic relations on demand for ontology extension (2014)
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- Abstract
- Learning non-taxonomic relations becomes an important research topic in ontology extension. Most of the existing learning approaches are mainly based on expert crafted corpora. These approaches are normally domain-specific and the corpora acquisition is laborious and costly. On the other hand, based on the static corpora, it is not able to meet personalized needs of semantic relations discovery for various taxonomies. In this paper, we propose a novel approach for learning non-taxonomic relations on demand. For any supplied taxonomy, it can focus on the segment of the taxonomy and collect information dynamically about the taxonomic concepts by using Wikipedia as a learning source. Based on the newly generated corpus, non-taxonomic relations are acquired through three steps: a) semantic relatedness detection; b) relations extraction between concepts; and c) relations generalization within a hierarchy. The proposed approach is evaluated on three different predefined taxonomies and the experimental results show that it is effective in capturing non-taxonomic relations as needed and has good potential for the ontology extension on demand.
-
Green, R.: See-also relationships in the Dewey Decimal Classification (2011)
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- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
