-
Reimer, U.: Einführung in die Wissensrepräsentation : netzartige und schema-basierte Repräsentationsformate (1991)
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- Classification
- ST 304 Informatik / Monographien / Künstliche Intelligenz / Automatisches Programmieren, Deduction and theorem proving, Wissensrepräsentation
Mat T 1091 / Wissensverarbeitung
IFQ (FH K)
- GHBS
- IFQ (FH K)
- RVK
- ST 304 Informatik / Monographien / Künstliche Intelligenz / Automatisches Programmieren, Deduction and theorem proving, Wissensrepräsentation
- SBB
- Mat T 1091 / Wissensverarbeitung
-
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.
-
Xiong, C.: Knowledge based text representations for information retrieval (2016)
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- Content
- Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
-
Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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- Content
- Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
-
Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017)
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- Abstract
- Diese Publikation beschreibt die Zusammenhänge zwischen wissenshaltigen begriffsorientierten Terminologien, Ontologien, Big Data und künstliche Intelligenz.
- Date
- 13.12.2017 14:17:22
-
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.
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- 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
-
Handbook on ontologies (2004)
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- BK
- 54.72 / Künstliche Intelligenz
- Classification
- ST 300 Informatik / Monographien / Künstliche Intelligenz / Allgemeines
ST 302 Informatik / Monographien / Künstliche Intelligenz / Expertensysteme; Wissensbasierte Systeme
54.72 / Künstliche Intelligenz
TXV (FH K)
- GHBS
- TXV (FH K)
- RVK
- ST 300 Informatik / Monographien / Künstliche Intelligenz / Allgemeines
ST 302 Informatik / Monographien / Künstliche Intelligenz / Expertensysteme; Wissensbasierte Systeme
-
Stuart, D.: Practical ontologies for information professionals (2016)
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- BK
- 54.72 (Künstliche Intelligenz)
- Classification
- 54.72 (Künstliche Intelligenz)
- Content
- C H A P T E R 1 What is an ontology?; Introduction; The data deluge and information overload; Defining terms; Knowledge organization systems and ontologies; Ontologies, metadata and linked data; What can an ontology do?; Ontologies and information professionals; Alternatives to ontologies; The aims of this book; The structure of this book; C H A P T E R 2 Ontologies and the semantic web; Introduction; The semantic web and linked data; Resource Description Framework (RDF); Classes, subclasses and properties; The semantic web stack; Embedded RDF; Alternative semantic visionsLibraries and the semantic web; Other cultural heritage institutions and the semantic web; Other organizations and the semantic web; Conclusion; C H A P T E R 3 Existing ontologies; Introduction; Ontology documentation; Ontologies for representing ontologies; Ontologies for libraries; Upper ontologies; Cultural heritage data models; Ontologies for the web; Conclusion; C H A P T E R 4 Adopting ontologies; Introduction; Reusing ontologies: application profiles and data models; Identifying ontologies; The ideal ontology discovery tool; Selection criteria; Conclusion C H A P T E R 5 Building ontologiesIntroduction; Approaches to building an ontology; The twelve steps; Ontology development example: Bibliometric Metrics Ontology element set; Conclusion; C H A P T E R 6 Interrogating ontologies; Introduction; Interrogating ontologies for reuse; Interrogating a knowledge base; Understanding ontology use; Conclusion; C H A P T E R 7 The future of ontologies and the information professional; Introduction; The future of ontologies for knowledge discovery; The future role of library and information professionals; The practical development of ontologies
-
Stuckenschmidt, H.: Ontologien : Konzepte, Technologien und Anwendungen (2009)
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- BK
- 54.72 / Künstliche Intelligenz
- Classification
- 54.72 / Künstliche Intelligenz
TWX (FH K)
- GHBS
- TWX (FH K)
-
Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997)
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- Date
- 1.10.2018 14:13:22
-
Kottmann, N.; Studer, T.: Improving semantic query answering (2006)
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- Abstract
- The retrieval problem is one of the main reasoning tasks for knowledge base systems. Given a knowledge base K and a concept C, the retrieval problem consists of finding all individuals a for which K logically entails C(a). We present an approach to answer retrieval queries over (a restriction of) OWL ontologies. Our solution is based on reducing the retrieval problem to a problem of evaluating an SQL query over a database constructed from the original knowledge base. We provide complete answers to retrieval problems. Still, our system performs very well as is shown by a standard benchmark.
-
Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval
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- Date
- 12. 2.2011 17:35:22
-
Stuckenschmidt, H.; Harmelen, F. van: Information sharing on the semantic web (2005)
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- BK
- 54.72 / Künstliche Intelligenz
- Classification
- 54.72 / Künstliche Intelligenz
TWX (FH K)
- GHBS
- TWX (FH K)
-
Nagao, M.: Knowledge and inference (1990)
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- Classification
- TXX (FH K)
- GHBS
- TXX (FH K)
- RSWK
- Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
- Subject
- Inferenz <Künstliche Intelligenz> / Wissensrepräsentation
-
Bittner, T.; Donnelly, M.; Winter, S.: Ontology and semantic interoperability (2006)
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- Date
- 3.12.2016 18:39:22
-
Hermans, J.: Ontologiebasiertes Information Retrieval für das Wissensmanagement (2008)
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- BK
- 54.72 / Künstliche Intelligenz
- Classification
- 54.72 / Künstliche Intelligenz
BCAQ (FH K)
- GHBS
- BCAQ (FH K)
-
Semantische Technologien : Grundlagen - Konzepte - Anwendungen (2012)
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- Content
- Inhalt: 1. Einleitung (A. Dengel, A. Bernardi) 2. Wissensrepräsentation (A. Dengel, A. Bernardi, L. van Elst) 3. Semantische Netze, Thesauri und Topic Maps (O. Rostanin, G. Weber) 4. Das Ressource Description Framework (T. Roth-Berghofer) 5. Ontologien und Ontologie-Abgleich in verteilten Informationssystemen (L. van Elst) 6. Anfragesprachen und Reasoning (M. Sintek) 7. Linked Open Data, Semantic Web Datensätze (G.A. Grimnes, O. Hartig, M. Kiesel, M. Liwicki) 8. Semantik in der Informationsextraktion (B. Adrian, B. Endres-Niggemeyer) 9. Semantische Suche (K. Schumacher, B. Forcher, T. Tran) 10. Erklärungsfähigkeit semantischer Systeme (B. Forcher, T. Roth-Berghofer, S. Agne) 11. Semantische Webservices zur Steuerung von Prooduktionsprozessen (M. Loskyll, J. Schlick, S. Hodeck, L. Ollinger, C. Maxeiner) 12. Wissensarbeit am Desktop (S. Schwarz, H. Maus, M. Kiesel, L. Sauermann) 13. Semantische Suche für medizinische Bilder (MEDICO) (M. Möller, M. Sintek) 14. Semantische Musikempfehlungen (S. Baumann, A. Passant) 15. Optimierung von Instandhaltungsprozessen durch Semantische Technologien (P. Stephan, M. Loskyll, C. Stahl, J. Schlick)
-
Müller, T.: Wissensrepräsentation mit semantischen Netzen im Bereich Luftfahrt (2006)
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- Date
- 26. 9.2006 21:00:22
-
Kiren, T.; Shoaib, M.: ¬A novel ontology matching approach using key concepts (2016)
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- Date
- 20. 1.2015 18:30:22
