Knowledge Base Creation, Enrichment and Repair
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- 作者：Sebastian Hellmann (18)
Volha Bryl (19)
Lorenz Bühmann (18)
Milan Dojchinovski (21)
Dimitris Kontokostas (18)
Jens Lehmann (18)
Uro? Milo?evi? (20)
Petar Petrovski (19)
Vojtěch Svátek (21)
Mladen Stanojevi? (20)
Ond?ej Zamazal (21) - 刊名：Lecture Notes in Computer Science
- 出版年：2014
- 出版时间：2014
- 年：2014
- 卷：1
- 期：1
- 页码：45-69
- 全文大小：8,671 KB
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Volha Bryl (19)
Lorenz Bühmann (18)
Milan Dojchinovski (21)
Dimitris Kontokostas (18)
Jens Lehmann (18)
Uro? Milo?evi? (20)
Petar Petrovski (19)
Vojtěch Svátek (21)
Mladen Stanojevi? (20)
Ond?ej Zamazal (21)
18. University of Leipzig, Leipzig, Germany
19. University of Mannheim, Mannheim, Germany
21. University of Economics Prague, Prague, Czech Republic
20. Institute Mihajlo Pupin, Belgrade, Serbia - ISSN：1611-3349
文摘
This chapter focuses on data transformation to RDF and Linked Data and furthermore on the improvement of existing or extracted data especially with respect to schema enrichment and ontology repair. Tasks concerning the triplification of data are mainly grounded on existing and well-proven techniques and were refined during the lifetime of the LOD2 project and integrated into the LOD2 Stack. Triplification of legacy data, i.e. data not yet in RDF, represents the entry point for legacy systems to participate in the LOD cloud. While existing systems are often very useful and successful, there are notable differences between the ways knowledge bases and Wikis or databases are created and used. One of the key differences in content is in the importance and use of schematic information in knowledge bases. This information is usually absent in the source system and therefore also in many LOD knowledge bases. However, schema information is needed for consistency checking and finding modelling problems. We will present a combination of enrichment and repair steps to tackle this problem based on previous research in machine learning and knowledge representation. Overall, the Chapter describes how to enable tool-supported creation and publishing of RDF as Linked Data (Sect.?1) and how to increase the quality and value of such large knowledge bases when published on the Web (Sect.?2).