Knowledge Discovery is traditionally used for analysis of large amounts of data and enables addressing a number of tasks that arise in Semantic Web and require scalable solutions. Additionally, Knowledge Discovery techniques have been successfully applied not only to structured data i.e. databases but also to semi-structured and unstructured data including text, graphs, images and video. Semantic Web technologies often call for dealing with text and sometimes also graphs or social networks. This chapter describes research approaches that are adopting knowledge discovery techniques to address semantic Web and presents several publicly available tools that are implementing some of the described approaches. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Mladenić, D., Grobelnik, M., Fortuna, B., & Grćar, M. (2009). Knowledge discovery for semantic web. In Semantic Knowledge Management: Integrating Ontology Management, Knowledge Discovery, and Human Language Technologies (pp. 21–36). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-540-88845-1_3
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