Decomposition of terminology graphs for domain knowledge acquisition.

Fidelia Ibekwe-Sanjuan (1) , Eric Sanjuan (2) , Michael Vogeley (3)

1 ELICO - Equipe de recherche de Lyon en sciences de l'information et de la communication
2 LIA - Laboratoire Informatique d'Avignon
3 Department of Physics - Drexel University

We propose a graph decomposition algorithm for analyzing the structure of complex graph networks. After multi-word term extraction, we apply techniques from text mining and visual analytics in a novel way by integrating symbolic and numeric information to build clusters of domain topics. Terms are clustered based on surface linguistic variations and clusters are inserted in an association network based on their intersection with documents. The graph is then decomposed based on atom graph structure into central (non-decomposable) atom and peripheral atoms. The whole process is applied to publications from the Sloan Digital Sky Survey (SDSS) project in the Astronomy field. The mapping obtained was evaluated by a domain expert and appeared to have captured interesting conceptual relations between different domain topics.

Mots clés: graph decomposition algorithm; multi-word term extraction; term variation; terminology engineering.; terminology engineering

Domaines: Sciences de l'information et de la communication; Traitement du texte et du document

Fidelia Ibekwe-Sanjuan, Eric Sanjuan, Michael Vogeley. Decomposition of terminology graphs for domain knowledge acquisition.. 17th ACM conference on Information and knowledge management (CIKM '08), Oct 2008, Napa Valley, California, United States. pp.1463-1464, ⟨10.1145/1458082.1458334⟩. ⟨hal-00636039⟩