Publications des scientifiques de l'IRD

Chahdi H., Grozavu N., Mougenot I., Berti-Equille Laure, Bennani Y. (2016). On the use of ontology as a priori knowledge into constrained clustering. In : Data science and advanced analytics. Montréal : IEEE, 9 p. multigr. DSAA 2016 : Data Science and Advanced Analytics : IEEE International Conference, 3., Montréal (CAN), 2016/10/17-19.

Titre du document
On the use of ontology as a priori knowledge into constrained clustering
Année de publication
2016
Type de document
Colloque
Auteurs
Chahdi H., Grozavu N., Mougenot I., Berti-Equille Laure, Bennani Y.
In
Data science and advanced analytics
Source
Montréal : IEEE, 2016, 9 p. multigr.
Colloque
DSAA 2016 : Data Science and Advanced Analytics : IEEE International Conference, 3., Montréal (CAN), 2016/10/17-19
Recent studies have shown that the use of a priori knowledge can significantly improve the results of unsupervised classification. However, capturing and formatting such knowledge as constraints is not only very expensive requiring the sustained involvement of an expert but it is also very difficult because some valuable information can be lost when it cannot be encoded as constraints. In this paper, we propose a new constraint-based clustering approach based on ontology reasoning for automatically generating constraints and bridging the semantic gap in satellite image labeling. The use of ontology as a priori knowledge has many advantages that we leverage in the context of satellite image interpretation. The experiments we conduct have shown that our proposed approach can deal with incomplete knowledge while completely exploiting the available one
Plan de classement
Traitement / Analyse numérique [126TELTRN]
Descripteurs
IMAGE SATELLITE ; TRAITEMENT D'IMAGE ; RECONNAISSANCE DE FORME ; SEMANTIQUE ; CLUSTERING ; ONTOLOGIE
Localisation
Fonds IRD [F B010067376]
Identifiant IRD
fdi:010067376
Contact