-
Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019)
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- Content
- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
- Pages
- S.140-150
-
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
-
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
-
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
-
Mahesh, K.: Highly expressive tagging for knowledge organization in the 21st century (2014)
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- Abstract
- Knowledge organization of large-scale content on the Web requires substantial amounts of semantic metadata that is expensive to generate manually. Recent developments in Web technologies have enabled any user to tag documents and other forms of content thereby generating metadata that could help organize knowledge. However, merely adding one or more tags to a document is highly inadequate to capture the aboutness of the document and thereby to support powerful semantic functions such as automatic classification, question answering or true semantic search and retrieval. This is true even when the tags used are labels from a well-designed classification system such as a thesaurus or taxonomy. There is a strong need to develop a semantic tagging mechanism with sufficient expressive power to capture the aboutness of each part of a document or dataset or multimedia content in order to enable applications that can benefit from knowledge organization on the Web. This article proposes a highly expressive mechanism of using ontology snippets as semantic tags that map portions of a document or a part of a dataset or a segment of a multimedia content to concepts and relations in an ontology of the domain(s) of interest.
- Pages
- S.274-280
- Source
- Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
-
Weller, K.: Kooperativer Ontologieaufbau (2006)
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- Pages
- S.227-234
-
Smolnik, S.; Nastansky, L.: K-Discovery : Identifikation von verteilten Wissensstrukturen in einer prozessorientierten Groupware-Umgebung (2004)
0.02
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- Abstract
- Verschiedene Szenarien in Groupware-basierten Umgebungen verdeutlichen die Probleme, Wissensstrukturen im Allgemeinen und organisationale Wissensstrukturen im Speziellen zu identifizieren. Durch den Einsatz von Topic Maps, definiert im ISOStandard "ISO/IEC 13250 Topic Maps", in Groupware-basierten organisationalen Wissensbasen wird es möglich, die Lücke zwischen Wissen und Information zu schließen. In diesem Beitrag werden die Ziele des Forschungsprojektes K-Discovery - der Einsatz von Topic Maps in Groupware-basierten Umgebungen - vorgestellt. Aufbauend auf diesen Zielen wird ein Architekturmodell sowie zwei Implementationsansätze präsentiert, in dem durch den Einsatz von Topic Maps in einer prozessorientierten GroupwareUmgebung Wissensstrukturen generiert werden. Der Beitrag schließt mit einigen abschließenden Ausführungen.
- Object
- K-Discovery
- Pages
- S.171-184
-
Nielsen, M.: Neuronale Netze : Alpha Go - Computer lernen Intuition (2018)
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- Content
- Vgl. auch den Beitrag: Sokol, J.: Spielend lernen. In: Spektrum der Wissenschaft. 2018, H.11, S.72-76.
- Source
- Spektrum der Wissenschaft. 2018, H.1, S.22-27
-
Weller, K.: Ontologien (2013)
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- Pages
- S.207-218
-
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
- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
-
Schmitz-Esser, W.: Language of general communication and concept compatibility (1996)
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- Pages
- S.11-22
-
Meng, K.; Ba, Z.; Ma, Y.; Li, G.: ¬A network coupling approach to detecting hierarchical linkages between science and technology (2024)
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- Abstract
- Detecting science-technology hierarchical linkages is beneficial for understanding deep interactions between science and technology (S&T). Previous studies have mainly focused on linear linkages between S&T but ignored their structural linkages. In this paper, we propose a network coupling approach to inspect hierarchical interactions of S&T by integrating their knowledge linkages and structural linkages. S&T knowledge networks are first enhanced with bidirectional encoder representation from transformers (BERT) knowledge alignment, and then their hierarchical structures are identified based on K-core decomposition. Hierarchical coupling preferences and strengths of the S&T networks over time are further calculated based on similarities of coupling nodes' degree distribution and similarities of coupling edges' weight distribution. Extensive experimental results indicate that our approach is feasible and robust in identifying the coupling hierarchy with superior performance compared to other isomorphism and dissimilarity algorithms. Our research extends the mindset of S&T linkage measurement by identifying patterns and paths of the interaction of S&T hierarchical knowledge.
- Source
- Journal of the Association for Information Science and Technology. 75(2023) no.2, S.167-187
-
Lee, J.; Min, J.-K.; Oh, A.; Chung, C.-W.: Effective ranking and search techniques for Web resources considering semantic relationships (2014)
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- Abstract
- On the Semantic Web, the types of resources and the semantic relationships between resources are defined in an ontology. By using that information, the accuracy of information retrieval can be improved. In this paper, we present effective ranking and search techniques considering the semantic relationships in an ontology. Our technique retrieves top-k resources which are the most relevant to query keywords through the semantic relationships. To do this, we propose a weighting measure for the semantic relationship. Based on this measure, we propose a novel ranking method which considers the number of meaningful semantic relationships between a resource and keywords as well as the coverage and discriminating power of keywords. In order to improve the efficiency of the search, we prune the unnecessary search space using the length and weight thresholds of the semantic relationship path. In addition, we exploit Threshold Algorithm based on an extended inverted index to answer top-k results efficiently. The experimental results using real data sets demonstrate that our retrieval method using the semantic information generates accurate results efficiently compared to the traditional methods.
- Source
- Information processing and management. 50(2014) no.1, S.132-155
-
Nguyen, P.H.P.; Kaneiwa, K.; Nguyen, M.-Q.: Ontology inferencing rules and operations in conceptual structure theory (2010)
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- Pages
- S.61-70
- Source
- Advances in ontologies: Proceedings of the Sixth Australasian Ontology Workshop Adelaide, Australia, 7 December 2010. Eds.: K. Taylor, T.Meyer u. M.Orgun [http://krr.meraka.org.za/~aow2010/AOW2010-preproceedings.pdf]
-
Baumer, C.; Reichenberger, K.: Business Semantics - Praxis und Perspektiven (2006)
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- Source
- Information - Wissenschaft und Praxis. 57(2006) H.6/7, S.359-366
-
Thellefsen, M.: ¬The dynamics of information representation and knowledge mediation (2006)
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- Pages
- S.279-286
- Source
- Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
-
Mainz, I.; Weller, K.; Paulsen, I.; Mainz, D.; Kohl, J.; Haeseler, A. von: Ontoverse : collaborative ontology engineering for the life sciences (2008)
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- Source
- Information - Wissenschaft und Praxis. 59(2008) H.2, S.91-99
-
Weller, K.; Peters, I.: Reconsidering relationships for knowledge representation (2007)
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- Pages
- S.501-504
-
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
-
Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997)
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- Date
- 1.10.2018 14:13:22
- Source
- AI communications. 10(1997) nos.3/4, S.167-176
