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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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- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
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Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005)
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Xiong, C.: Knowledge based text representations for information retrieval (2016)
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- 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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Gayathri, R.; Uma, V.: Ontology based knowledge representation technique, domain modeling languages and planners for robotic path planning : a survey (2018)
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- Abstract
- Knowledge Representation and Reasoning (KR & R) has become one of the promising fields of Artificial Intelligence. KR is dedicated towards representing information about the domain that can be utilized in path planning. Ontology based knowledge representation and reasoning techniques provide sophisticated knowledge about the environment for processing tasks or methods. Ontology helps in representing the knowledge about environment, events and actions that help in path planning and making robots more autonomous. Knowledge reasoning techniques can infer new conclusion and thus aids planning dynamically in a non-deterministic environment. In the initial sections, the representation of knowledge using ontology and the techniques for reasoning that could contribute in path planning are discussed in detail. In the following section, we also provide comparison of various planning domain modeling languages, ontology editors, planners and robot simulation tools.
- Language
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Schmitz-Esser, W.: Language of general communication and concept compatibility (1996)
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Tudhope, D.; Hodge, G.: Terminology registries (2007)
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Börner, K.: Atlas of knowledge : anyone can map (2015)
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- JZN (E)
TVV (E)
- Date
- 22. 1.2017 16:54:03
22. 1.2017 17:10:56
- GHBS
- JZN (E)
TVV (E)
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Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009)
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Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997)
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Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010)
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- Content
- What Is an Ontology? - Kinds of Ontologies and the Role of Taxonomies - Principles of Best Practice 1: Domain Ontology Design - Principles of Best Practice II: Terms, Definitions, and Classification - Introduction to Basic Formal Ontology I: Continuants - Introduction to Basic Formal Ontology II: Occurrents - The Ontology of Relations - Basic Formal Ontology at Work - Appendix on Implementation: Languages, Editors, Reasoners, Browsers, Tools for Reuse - Glossary - Web Links Mentioned in the Text Including Ontologies, Research Groups, Software, and Reasoning Tools
- Language
- e
-
Prud'hommeaux, E.; Gayo, E.: RDF ventures to boldly meet your most pedestrian needs (2015)
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- Language
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- Source
- Bulletin of the Association for Information Science and Technology. 41(2015) no.4, S.18-22
-
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
- Language
- e
-
Järvelin, K.; Kristensen, J.; Niemi, T.; Sormunen, E.; Keskustalo, H.: ¬A deductive data model for query expansion (1996)
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- Language
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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
-
Fischer, D.H.: Converting a thesaurus to OWL : Notes on the paper "The National Cancer Institute's Thesaurus and Ontology" (2004)
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- Abstract
- The paper analysed here is a kind of position paper. In order to get a better under-standing of the reported work I used the retrieval interface of the thesaurus, the so-called NCI DTS Browser accessible via the Web3, and I perused the cited OWL file4 with numerous "Find" and "Find next" string searches. In addition the file was im-ported into Protégé 2000, Release 2.0, with OWL Plugin 1.0 and Racer Plugin 1.7.14. At the end of the paper's introduction the authors say: "In the following sections, this paper will describe the terminology development process at NCI, and the issues associated with converting a description logic based nomenclature to a semantically rich OWL ontology." While I will not deal with the first part, i.e. the terminology development process at NCI, I do not see the thesaurus as a description logic based nomenclature, or its cur-rent state and conversion already result in a "rich" OWL ontology. What does "rich" mean here? According to my view there is a great quantity of concepts and links but a very poor description logic structure which enables inferences. And what does the fol-lowing really mean, which is said a few lines previously: "Although editors have defined a number of named ontologic relations to support the description-logic based structure of the Thesaurus, additional relation-ships are considered for inclusion as required to support dependent applications."
- Language
- e
