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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.
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Shen, M.; Liu, D.-R.; Huang, Y.-S.: Extracting semantic relations to enrich domain ontologies (2012)
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-
Drewer, P.; Massion, F; Pulitano, D: Was haben Wissensmodellierung, Wissensstrukturierung, künstliche Intelligenz und Terminologie miteinander zu tun? (2017)
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- Date
- 13.12.2017 14:17:22
- Type
- r
-
Studer, R.; Studer, H.-P.; Studer, A.: Semantisches Knowledge Retrieval (2001)
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- Source
- http://www.b-y-a.de/wordpress/wp-content/uploads/2006/08/ontoprise_whitepaper_knowledge_retrieval.pdf
- Type
- r
-
Sure, Y.; Studer, R.: ¬A methodology for ontology-based knowledge management (2004)
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Wei, W.; Liu, Y.-P.; Wei, L-R.: Feature-level sentiment analysis based on rules and fine-grained domain ontology (2020)
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Bringsjord, S.; Clark, M.; Taylor, J.: Sophisticated knowledge representation and reasoning requires philosophy (2014)
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- Abstract
- What is knowledge representation and reasoning (KR&R)? Alas, a thorough account would require a book, or at least a dedicated, full-length paper, but here we shall have to make do with something simpler. Since most readers are likely to have an intuitive grasp of the essence of KR&R, our simple account should suffice. The interesting thing is that this simple account itself makes reference to some of the foundational distinctions in the field of philosophy. These distinctions also play a central role in artificial intelligence (AI) and computer science. To begin with, the first distinction in KR&R is that we identify knowledge with knowledge that such-and-such holds (possibly to a degree), rather than knowing how. If you ask an expert tennis player how he manages to serve a ball at 130 miles per hour on his first serve, and then serve a safer, topspin serve on his second should the first be out, you may well receive a confession that, if truth be told, this athlete can't really tell you. He just does it; he does something he has been doing since his youth. Yet, there is no denying that he knows how to serve. In contrast, the knowledge in KR&R must be expressible in declarative statements. For example, our tennis player knows that if his first serve lands outside the service box, it's not in play. He thus knows a proposition, conditional in form.
- Date
- 9. 2.2017 19:22:14
- Source
- Philosophy, computing and information science. Eds.: R. Hagengruber u. U.V. Riss
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Jorge-Botana, G.; León, J.A.; Olmos, R.; Hassan-Montero, Y.: Visualizing polysemy using LSA and the predication algorithm (2010)
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Yu, L.-C.; Wu, C.-H.; Chang, R.-Y.; Liu, C.-H.; Hovy, E.H.: Annotation and verification of sense pools in OntoNotes (2010)
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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.
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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.
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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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Eito-Brun, R.: Ontologies and the exchange of technical information : building a knowledge repository based on ECSS standards (2014)
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