Explaining data patterns using background knowledge from Linked Data

Tiddi, Ilaria (2013). Explaining data patterns using background knowledge from Linked Data. In: Proceedings of the Doctoral Consortium co-located with 12th International Semantic Web Conference (ISWC 2013), Sydney, Australia, October 20, 2013, pp. 56–63.

URL: http://iswc2013.semanticweb.org/

Abstract

When using data mining to find regularities in data, the obtained results (or patterns) need to be interpreted. The explanation of such patterns is achieved using the background knowledge which might be scattered among different sources. This intensive process is usually committed to the experts in the domain. With the rise of Linked Data and the increasing number of connected datasets, we assume that the access to this knowledge can be easier, faster and more automated. This PhD research aims to demonstrate whether Linked Data can be used to provide the background knowledge for pattern interpretation and how.

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About

• Item ORO ID
• 41693
• Item Type
• Conference or Workshop Item
• ISSN
• 1613-0073
• Keywords
• Linked Data; data mining; knowledge discovery; data interpretation
• Academic Unit or School
• Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
  Faculty of Science, Technology, Engineering and Mathematics (STEM)
• Copyright Holders
• © 2013 The Author
• Related URLs
• • http://ceur-ws.org/Vol-1045/(Other)
• Depositing User
• Kay Dave