Data patterns explained with linked data

Ilaria Tiddi; Mathieu d’Aquin; Enrico Motta

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

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 proceeding › Conference contribution › Academic › peer-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 language	English
Title of host publication	Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings
Editors	Bianca 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
Publisher	Springer Verlag
Pages	271-275
Number of pages	5
ISBN (Print)	9783319234601, 9783319234601, 9783319234601, 9783319234601
DOIs	https://doi.org/10.1007/978-3-319-23461-8_28
Publication status	Published - 1 Jan 2015
Externally published	Yes
Event	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015 - Porto, Portugal Duration: 7 Sept 2015 → 11 Sept 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9286
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015
Country/Territory	Portugal
City	Porto
Period	7/09/15 → 11/09/15

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

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Tiddi, I., d’Aquin, M., & Motta, E. (2015). Data patterns explained with linked data. In B. Zadrozny, F. Bonchi, B. Zadrozny, J. Cardoso, F. Bonchi, R. Gavalda, F. Bonchi, M. Spiliopoulou, R. Gavalda, D. Pedreschi, J. Cardoso, M. Spiliopoulou, J. Cardoso, D. Pedreschi, F. Bonchi, A. Bifet, D. Pedreschi, A. Bifet, B. Zadrozny, M. Spiliopoulou, D. Pedreschi, M. Spiliopoulou, M. May, M. May, A. Bifet, R. Gavalda, A. Bifet, M. May, B. Zadrozny, M. May, J. Cardoso, ... R. Gavalda (Eds.), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings (pp. 271-275). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9286). Springer Verlag. https://doi.org/10.1007/978-3-319-23461-8_28

Tiddi, Ilaria ; d’Aquin, Mathieu ; Motta, Enrico. / Data patterns explained with linked data. Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings. editor / Bianca 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. Springer Verlag, 2015. pp. 271-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Data patterns explained with linked data",

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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Tiddi, I, d’Aquin, M & Motta, E 2015, Data patterns explained with linked data. in B Zadrozny, F Bonchi, B Zadrozny, J Cardoso, F Bonchi, R Gavalda, F Bonchi, M Spiliopoulou, R Gavalda, D Pedreschi, J Cardoso, M Spiliopoulou, J Cardoso, D Pedreschi, F Bonchi, A Bifet, D Pedreschi, A Bifet, B Zadrozny, M Spiliopoulou, D Pedreschi, M Spiliopoulou, M May, M May, A Bifet, R Gavalda, A Bifet, M May, B Zadrozny, M May, J Cardoso & R Gavalda (eds), Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9286, Springer Verlag, pp. 271-275, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015, Porto, Portugal, 7/09/15. https://doi.org/10.1007/978-3-319-23461-8_28

Data patterns explained with linked data. / Tiddi, Ilaria; d’Aquin, Mathieu; Motta, Enrico.
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings. ed. / Bianca 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. Springer Verlag, 2015. p. 271-275 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9286).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - d’Aquin, Mathieu

AU - Motta, Enrico

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N2 - 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.

AB - 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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Tiddi I, d’Aquin M, Motta E. Data patterns explained with linked data. In Zadrozny B, Bonchi F, Zadrozny B, Cardoso J, Bonchi F, Gavalda R, Bonchi F, Spiliopoulou M, Gavalda R, Pedreschi D, Cardoso J, Spiliopoulou M, Cardoso J, Pedreschi D, Bonchi F, Bifet A, Pedreschi D, Bifet A, Zadrozny B, Spiliopoulou M, Pedreschi D, Spiliopoulou M, May M, May M, Bifet A, Gavalda R, Bifet A, May M, Zadrozny B, May M, Cardoso J, Gavalda R, editors, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2015, Proceedings. Springer Verlag. 2015. p. 271-275. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-23461-8_28

Data patterns explained with linked data

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