A Proposal for Classifying the Content of the Web of Data Based on FCA and Pattern Structures - Archive ouverte HAL Access content directly
Conference Papers Year :

A Proposal for Classifying the Content of the Web of Data Based on FCA and Pattern Structures

(1) , (2) , (1) , (1)
1
2
Justine Reynaud
Mehwish Alam
  • Function : Author
  • PersonId : 996824
Yannick Toussaint
  • Function : Author
  • PersonId : 832664
Amedeo Napoli

Abstract

This paper focuses on a framework based on Formal Concept Analysis and the Pattern Structures for classifying sets of RDF triples. The first step proposes how the pattern structures allowing the classification of RDF triples w.r.t. domain knowledge can be constructed. 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.
Fichier principal
Vignette du fichier
ISMIS_2017_paper_85.pdf (537.54 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01667437 , version 1 (04-04-2019)

Identifiers

  • HAL Id : hal-01667437 , version 1

Cite

Justine Reynaud, Mehwish Alam, Yannick Toussaint, Amedeo Napoli. A Proposal for Classifying the Content of the Web of Data Based on FCA and Pattern Structures. ISMIS 2017 - 23rd International Symposium on Methodologies for Intelligent Systems, Jun 2017, Warsaw, Poland. ⟨hal-01667437⟩
88 View
110 Download

Share

Gmail Facebook Twitter LinkedIn More