-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie (2005)
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- Abstract
- Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
- Date
- 11. 2.2011 18:22:58
- Object
- K-Infinity
- Source
- Information - Wissenschaft und Praxis. 56(2005) H.5/6, S.281-290
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- Pages
- S.235-243
- Source
- Proceedings of the 19th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (ACM SIGIR '96), Zürich, Switzerland, August 18-22, 1996. Eds.: H.P. Frei et al
-
Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005)
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- Abstract
- Ontologien werden eingesetzt, um durch semantische Fundierung insbesondere für das Dokumentenretrieval eine grundlegend bessere Basis zu haben, als dies gegenwärtiger Stand der Technik ist. Vorgestellt wird eine an der FH Darmstadt entwickelte und eingesetzte Ontologie, die den Gegenstandsbereich Hochschule sowohl breit abdecken und gleichzeitig differenziert semantisch beschreiben soll. Das Problem der semantischen Suche besteht nun darin, dass sie für Informationssuchende so einfach wie bei gängigen Suchmaschinen zu nutzen sein soll, und gleichzeitig auf der Grundlage des aufwendigen Informationsmodells hochwertige Ergebnisse liefern muss. Es wird beschrieben, welche Möglichkeiten die verwendete Software K-Infinity bereitstellt und mit welchem Konzept diese Möglichkeiten für eine semantische Suche nach Dokumenten und anderen Informationseinheiten (Personen, Veranstaltungen, Projekte etc.) eingesetzt werden.
- Date
- 11. 2.2011 18:22:25
- Object
- K-Infinity
-
Baofu, P.: ¬The future of information architecture : conceiving a better way to understand taxonomy, network, and intelligence (2008)
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- Classification
- BBV (FH K)
- GHBS
- BBV (FH K)
- Pages
- XX, 283 S
-
Nagao, M.: Knowledge and inference (1990)
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- Classification
- TXX (FH K)
- GHBS
- TXX (FH K)
- Pages
- XV, 304 S
-
Mäkelä, E.; Hyvönen, E.; Saarela, S.; Vilfanen, K.: Application of ontology techniques to view-based semantic serach and browsing (2012)
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- Abstract
- We scho how the beenfits of the view-based search method, developed within the information retrieval community, can be extended with ontology-based search, developed within the Semantic Web community, and with semantic recommendations. As a proof of the concept, we have implemented an ontology-and view-based search engine and recommendations system Ontogaotr for RDF(S) repositories. Ontogator is innovative in two ways. Firstly, the RDFS.based ontologies used for annotating metadata are used in the user interface to facilitate view-based information retrieval. The views provide the user with an overview of the repositorys contents and a vocabulary for expressing search queries. Secondlyy, a semantic browsing function is provided by a recommender system. This system enriches instance level metadata by ontologies and provides the user with links to semantically related relevant resources. The semantic linkage is specified in terms of logical rules. To illustrate and discuss the ideas, a deployed application of Ontogator to a photo repository of the Helsinki University Museum is presented.
-
Thenmalar, S.; Geetha, T.V.: Enhanced ontology-based indexing and searching (2014)
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- Date
- 20. 1.2015 18:30:22
- Source
- Aslib journal of information management. 66(2014) no.6, S.678-696
-
Wang, Y.-H.; Jhuo, P.-S.: ¬A semantic faceted search with rule-based inference (2009)
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- Pages
- S.1002-1008
-
Calegari, S.; Sanchez, E.: Object-fuzzy concept network : an enrichment of ontologies in semantic information retrieval (2008)
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- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.13, S.2171-2185
-
Green, R.: See-also relationships in the Dewey Decimal Classification (2011)
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- Source
- Knowledge organization. 38(2011) no.4, S.335-341
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Weiermann, S.L.: Semantische Netze und Begriffsdeskription in der Wissensrepräsentation (2000)
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- Pages
- III, 240 S
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Atanassova, I.; Bertin, M.: Semantic facets for scientific information retrieval (2014)
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- S.108-113
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Moreira, W.; Martínez-Ávila, D.: Concept relationships in knowledge organization systems : elements for analysis and common research among fields (2018)
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- Source
- Cataloging and classification quarterly. 56(2018) no.1, S.19-39
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Drexel, G.: Knowledge engineering for intelligent information retrieval (2001)
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- Pages
- S.495-504
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Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005)
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- S.455-470
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Arenas, M.; Cuenca Grau, B.; Kharlamov, E.; Marciuska, S.; Zheleznyakov, D.: Faceted search over ontology-enhanced RDF data (2014)
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Boteram, F.: Typisierung semantischer Relationen in integrierten Systemen der Wissensorganisation (2013)
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- Pages
- S.152-160
-
Cao, N.; Sun, J.; Lin, Y.-R.; Gotz, D.; Liu, S.; Qu, H.: FacetAtlas : Multifaceted visualization for rich text corpora (2010)
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Ma, N.; Zheng, H.T.; Xiao, X.: ¬An ontology-based latent semantic indexing approach using long short-term memory networks (2017)
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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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- Source
- Information Retrieval Journal. 19(2016) no.1, S.6-37
