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Data Patterns Explained with Linked Data

Tiddi, Ilaria; d'Aquin, Mathieu and Motta, Enrico (2015). Data Patterns Explained with Linked Data. In: Machine Learning and Knowledge Discovery in Databases. Pt.3, Springer International Publishing, pp. 271–275.

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In this paper we present the system Dedalo, whose aim is to generate explanations for data patterns using background knowledge retrieved from Linked Data. In many real-world scenarios, patterns are generally manually interpreted by the experts that have to use their own background knowledge to explain and refine them, while their workload could be relieved by exploiting the open and machine-readable knowledge existing on the Web nowadays. In the light of this, we devised an automatic system that, given some patterns and some background knowledge extracted from Linked Data, reasons upon those and creates well-structured candidate explanations for their grouping. In our demo, we show how the system provides a step towards automatising the interpretation process in KDD, by presenting scenarios in different domains, data and patterns.

Item Type: Conference or Workshop Item
Copyright Holders: 2015 Springer International Publishing Switzerland
ISBN: 3-319-23460-9, 978-3-319-23460-1
ISSN: 0302-9743
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Item ID: 44302
Depositing User: Kay Dave
Date Deposited: 10 Sep 2015 08:28
Last Modified: 09 May 2019 11:39
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