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Hollink, L.; Assem, M. van: Estimating the relevance of search results in the Culture-Web : a study of semantic distance measures (2010)
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- Date
- 26.12.2011 13:40:22
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OWL Web Ontology Language Test Cases (2004)
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- Date
- 14. 8.2011 13:33:22
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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
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Zhang, L.; Liu, Q.L.; Zhang, J.; Wang, H.F.; Pan, Y.; Yu, Y.: Semplore: an IR approach to scalable hybrid query of Semantic Web data (2007)
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-
Scheir, P.; Pammer, V.; Lindstaedt, S.N.: Information retrieval on the Semantic Web : does it exist? (2007)
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- Abstract
- Plenty of contemporary attempts to search exist that are associated with the area of Semantic Web. But which of them qualify as information retrieval for the Semantic Web? Do such approaches exist? To answer these questions we take a look at the nature of the Semantic Web and Semantic Desktop and at definitions for information and data retrieval. We survey current approaches referred to by their authors as information retrieval for the Semantic Web or that use Semantic Web technology for search.
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Schmitz-Esser, W.; Sigel, A.: Introducing terminology-based ontologies : Papers and Materials presented by the authors at the workshop "Introducing Terminology-based Ontologies" (Poli/Schmitz-Esser/Sigel) at the 9th International Conference of the International Society for Knowledge Organization (ISKO), Vienna, Austria, July 6th, 2006 (2006)
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Monireh, E.; Sarker, M.K.; Bianchi, F.; Hitzler, P.; Doran, D.; Xie, N.: Reasoning over RDF knowledge bases using deep learning (2018)
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- Date
- 16.11.2018 14:22:01
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Gómez-Pérez, A.; Corcho, O.: Ontology languages for the Semantic Web (2015)
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- Abstract
- Ontologies have proven to be an essential element in many applications. They are used in agent systems, knowledge management systems, and e-commerce platforms. They can also generate natural language, integrate intelligent information, provide semantic-based access to the Internet, and extract information from texts in addition to being used in many other applications to explicitly declare the knowledge embedded in them. However, not only are ontologies useful for applications in which knowledge plays a key role, but they can also trigger a major change in current Web contents. This change is leading to the third generation of the Web-known as the Semantic Web-which has been defined as "the conceptual structuring of the Web in an explicit machine-readable way."1 This definition does not differ too much from the one used for defining an ontology: "An ontology is an explicit, machinereadable specification of a shared conceptualization."2 In fact, new ontology-based applications and knowledge architectures are developing for this new Web. A common claim for all of these approaches is the need for languages to represent the semantic information that this Web requires-solving the heterogeneous data exchange in this heterogeneous environment. Here, we don't decide which language is best of the Semantic Web. Rather, our goal is to help developers find the most suitable language for their representation needs. The authors analyze the most representative ontology languages created for the Web and compare them using a common framework.
