Joint European Conference on Machine Learning and Knowledge Discovery in Databases

ECML PKDD 2015: Machine Learning and Knowledge Discovery in Databases pp 271-275

Data Patterns Explained with Linked Data

Conference paper

DOI: 10.1007/978-3-319-23461-8_28

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)
Cite this paper as:
Tiddi I., d’Aquin M., Motta E. (2015) Data Patterns Explained with Linked Data. In: Bifet A. et al. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2015. Lecture Notes in Computer Science, vol 9286. Springer, Cham

Abstract

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.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Knowledge Media InstituteThe Open UniversityMilton KeynesUK

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