On-demand Relational Concept Analysis - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2018

On-demand Relational Concept Analysis

Résumé

Formal Concept Analysis and its associated conceptual structures have been used to support exploratory search through conceptual navigation. Relational Concept Analysis (RCA) is an extension of Formal Concept Analysis to process relational datasets. RCA and its multiple interconnected structures represent good candidates to support exploratory search in relational datasets, as they are enabling navigation within a structure as well as between the connected structures. However, building the entire structures does not present an efficient solution to explore a small localised area of the dataset, for instance to retrieve the closest alternatives to a given query. In these cases, generating only a concept and its neighbour concepts at each navigation step appears as a less costly alternative. In this paper, we propose an algorithm to compute a concept and its neighbourhood in extended concept lattices. The concepts are generated directly from the relational context family, and possess both formal and relational attributes. The algorithm takes into account two RCA scaling operators. We illustrate it on an example.
Fichier principal
Vignette du fichier
cla2018rca.pdf (551.32 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-01735865 , version 1 (21-03-2018)

Identifiants

Citer

Alexandre Bazin, Jessie Carbonnel, Marianne Huchard, Giacomo Kahn. On-demand Relational Concept Analysis. 2018. ⟨hal-01735865⟩
294 Consultations
142 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More