ARViz: Interactive Visualization of Association Rules for RDF Data Exploration - Archive ouverte HAL Access content directly
Conference Papers Year : 2021

ARViz: Interactive Visualization of Association Rules for RDF Data Exploration

ARViz : La visualisation interactive des règles d'association pour l'exploration des données RDF


Association rule mining often leads the analyst into a rough rummaging process to identify rules that are relevant to understand specific problems. We propose a visualization interface to assist the rule selection process and evaluate it on an RDF knowledge graph derived from the COVID-19 Open Research Dataset. The user interface supports data exploration with focus on the overview of rules through a scatter plot, subsets of rules through a chord diagram chart, and itemsets through an association graph which is dynamically created by entering an item of interest (i.e. a named entity). Further, the analyst can interactively recover a list of publications containing the named entities involved in a particular rule. Among the original aspects of our approach, we highlight the representation of attributes describing measures of interest (i.e. confidence and interestingness), a visual indication of existence (or not) of symmetry in association rules, the exploration of subsets of rules according to clusters of publications and named entities, and an interactive prompting that aims at expanding the discovery of named entities within selected association rules. We assess our approach through a semi-structured interview involving experts in the domains of data mining and biomedicine, whose feedback could assist the refinement of the visual and interaction tools.
Fichier principal
Vignette du fichier
IV2021_CameraReady_126_eXpress_Validated.pdf (2.25 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-03292140 , version 1 (20-07-2021)



Aline Menin, Lucie Cadorel, Andrea G. B. Tettamanzi, Alain Giboin, Fabien Gandon, et al.. ARViz: Interactive Visualization of Association Rules for RDF Data Exploration. IV 2021 - 25th International Conference Information Visualisation, Jul 2021, Melbourne / Virtual, Australia. pp.13-20, ⟨10.1109/IV53921.2021.00013⟩. ⟨hal-03292140⟩
293 View
148 Download



Gmail Facebook Twitter LinkedIn More