Exploratory Knowledge Discovery over Web of Data - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles Discrete Applied Mathematics Year : 2018

Exploratory Knowledge Discovery over Web of Data


With an increased interest in machine processable data and with the progress of semantic technologies, many datasets are now published in the form of RDF triples for constituting the so-called Web of Data. Data can be queried using SPARQL but there are still needs for integrating, classifying and exploring the data for data analysis and knowledge discovery purposes. This research work proposes a new approach based on Formal Concept Analysis and Pattern Structures for building a pattern concept lattice from a set of RDF triples. This lattice can be used for data exploration and in particular visualized thanks to an adapted tool. The specific pattern structure introduced for RDF data allows to make a bridge with other studies on the use of structured attribute sets when building concept lattices. Our approach is experimentally validated on the classification of RDF data showing the efficiency of the underlying algorithms.
Fichier principal
Vignette du fichier
ma+ab+an-dam-170722.pdf (1.16 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01673439 , version 1 (29-12-2017)



Mehwish Alam, Aleksey Buzmakov, Amedeo Napoli. Exploratory Knowledge Discovery over Web of Data. Discrete Applied Mathematics, 2018, 249, pp.2-17. ⟨10.1016/j.dam.2018.03.041⟩. ⟨hal-01673439⟩
240 View
231 Download



Gmail Facebook X LinkedIn More