Data patterns explained with linked data

Ilaria Tiddi*, Mathieu d’Aquin, Enrico Motta

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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.

Original languageEnglish
Title of host publicationMachine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings
EditorsBianca Zadrozny, Francesco Bonchi, Bianca Zadrozny, Jaime Cardoso, Francesco Bonchi, Ricard Gavalda, Francesco Bonchi, Myra Spiliopoulou, Ricard Gavalda, Dino Pedreschi, Jaime Cardoso, Myra Spiliopoulou, Jaime Cardoso, Dino Pedreschi, Francesco Bonchi, Albert Bifet, Dino Pedreschi, Albert Bifet, Bianca Zadrozny, Myra Spiliopoulou, Dino Pedreschi, Myra Spiliopoulou, Michael May, Michael May, Albert Bifet, Ricard Gavalda, Albert Bifet, Michael May, Bianca Zadrozny, Michael May, Jaime Cardoso, Ricard Gavalda
PublisherSpringer Verlag
Pages271-275
Number of pages5
ISBN (Print)9783319234601, 9783319234601, 9783319234601, 9783319234601
DOIs
Publication statusPublished - 1 Jan 2015
Externally publishedYes
EventEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015 - Porto, Portugal
Duration: 7 Sep 201511 Sep 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9286
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015
CountryPortugal
CityPorto
Period7/09/1511/09/15

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