A proposal for classifying the content of the web of data based on FCA and pattern structures

Justine Reynaud; Mehwish Alam; Yannick Toussaint; Amedeo Napoli

doi:10.1007/978-3-319-60438-1_67

A proposal for classifying the content of the web of data based on FCA and pattern structures

Justine Reynaud
, Mehwish Alam
, Yannick Toussaint
, Amedeo Napoli

Nancy Université
University Paris 13

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

Abstract

This paper focuses on a framework based on Formal Concept Analysis and the Pattern Structures for classifying sets of RDF triples. Firstly, this paper proposes a method to construct a pattern structure for the classification of RDF triples w.r.t. domain knowledge. More precisely, the poset of classes representing subjects and objects and the poset of predicates in RDF triples are taken into account. A similarity measure is also proposed based on these posets. Then, the paper discusses experimental details using a subset of DBpedia. It shows how the resulting pattern concept lattice is built and how it can be interpreted for discovering significant knowledge units from the obtained classes of RDF triples.

Original language	English
Title of host publication	Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings
Editors	Marzena Kryszkiewicz, Henryk Rybinski, Zbigniew W. Ras, Dominik Slezak, Andrzej Skowron, Annalisa Appice, Andrzej Skowron
Publisher	Springer Verlag
Pages	684-694
Number of pages	11
ISBN (Print)	9783319604374
DOIs	https://doi.org/10.1007/978-3-319-60438-1_67
Publication status	Published - 1 Jan 2017
Externally published	Yes
Event	23rd International Symposium on Methodologies for Intelligent Systems, ISMIS 2017 - Warsaw, Poland Duration: 26 Jun 2017 → 29 Jun 2017

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	10352 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	23rd International Symposium on Methodologies for Intelligent Systems, ISMIS 2017
Country/Territory	Poland
City	Warsaw
Period	26/06/17 → 29/06/17

Access to Document

10.1007/978-3-319-60438-1_67

Cite this

Reynaud, J., Alam, M., Toussaint, Y., & Napoli, A. (2017). A proposal for classifying the content of the web of data based on FCA and pattern structures. In M. Kryszkiewicz, H. Rybinski, Z. W. Ras, D. Slezak, A. Skowron, A. Appice, & A. Skowron (Eds.), Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings (pp. 684-694). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10352 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-60438-1_67

Reynaud, Justine ; Alam, Mehwish ; Toussaint, Yannick et al. / A proposal for classifying the content of the web of data based on FCA and pattern structures. Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings. editor / Marzena Kryszkiewicz ; Henryk Rybinski ; Zbigniew W. Ras ; Dominik Slezak ; Andrzej Skowron ; Annalisa Appice ; Andrzej Skowron. Springer Verlag, 2017. pp. 684-694 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A proposal for classifying the content of the web of data based on FCA and pattern structures",

abstract = "This paper focuses on a framework based on Formal Concept Analysis and the Pattern Structures for classifying sets of RDF triples. Firstly, this paper proposes a method to construct a pattern structure for the classification of RDF triples w.r.t. domain knowledge. More precisely, the poset of classes representing subjects and objects and the poset of predicates in RDF triples are taken into account. A similarity measure is also proposed based on these posets. Then, the paper discusses experimental details using a subset of DBpedia. It shows how the resulting pattern concept lattice is built and how it can be interpreted for discovering significant knowledge units from the obtained classes of RDF triples.",

author = "Justine Reynaud and Mehwish Alam and Yannick Toussaint and Amedeo Napoli",

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Reynaud, J, Alam, M, Toussaint, Y & Napoli, A 2017, A proposal for classifying the content of the web of data based on FCA and pattern structures. in M Kryszkiewicz, H Rybinski, ZW Ras, D Slezak, A Skowron, A Appice & A Skowron (eds), Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10352 LNAI, Springer Verlag, pp. 684-694, 23rd International Symposium on Methodologies for Intelligent Systems, ISMIS 2017, Warsaw, Poland, 26/06/17. https://doi.org/10.1007/978-3-319-60438-1_67

A proposal for classifying the content of the web of data based on FCA and pattern structures. / Reynaud, Justine; Alam, Mehwish; Toussaint, Yannick et al.
Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings. ed. / Marzena Kryszkiewicz; Henryk Rybinski; Zbigniew W. Ras; Dominik Slezak; Andrzej Skowron; Annalisa Appice; Andrzej Skowron. Springer Verlag, 2017. p. 684-694 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10352 LNAI).

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

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AU - Reynaud, Justine

AU - Alam, Mehwish

AU - Toussaint, Yannick

AU - Napoli, Amedeo

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017/1/1

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N2 - This paper focuses on a framework based on Formal Concept Analysis and the Pattern Structures for classifying sets of RDF triples. Firstly, this paper proposes a method to construct a pattern structure for the classification of RDF triples w.r.t. domain knowledge. More precisely, the poset of classes representing subjects and objects and the poset of predicates in RDF triples are taken into account. A similarity measure is also proposed based on these posets. Then, the paper discusses experimental details using a subset of DBpedia. It shows how the resulting pattern concept lattice is built and how it can be interpreted for discovering significant knowledge units from the obtained classes of RDF triples.

AB - This paper focuses on a framework based on Formal Concept Analysis and the Pattern Structures for classifying sets of RDF triples. Firstly, this paper proposes a method to construct a pattern structure for the classification of RDF triples w.r.t. domain knowledge. More precisely, the poset of classes representing subjects and objects and the poset of predicates in RDF triples are taken into account. A similarity measure is also proposed based on these posets. Then, the paper discusses experimental details using a subset of DBpedia. It shows how the resulting pattern concept lattice is built and how it can be interpreted for discovering significant knowledge units from the obtained classes of RDF triples.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings

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PB - Springer Verlag

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Reynaud J, Alam M, Toussaint Y, Napoli A. A proposal for classifying the content of the web of data based on FCA and pattern structures. In Kryszkiewicz M, Rybinski H, Ras ZW, Slezak D, Skowron A, Appice A, Skowron A, editors, Foundations of Intelligent Systems - 23rd International Symposium, ISMIS 2017, Proceedings. Springer Verlag. 2017. p. 684-694. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-60438-1_67

A proposal for classifying the content of the web of data based on FCA and pattern structures

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