Graph Mining under Linguistic Constraints to Explore Large Texts

Solen Quiniou (1) , Peggy Cellier (2) , Thierry Charnois (3, 4) , Dominique Legallois (5)

1 LINA - Laboratoire d'Informatique de Nantes Atlantique
2 LIS - Logical Information Systems
3 MoDyCo - Modèles, Dynamiques, Corpus
4 Equipe CODAG - Laboratoire GREYC - UMR6072
5 CRISCO - Centre de recherche inter-langues sur la signification en contexte

In this paper, we propose an approach to explore large texts by highlighting coherent sub-parts. The exploration method relies on a graph representation of the text according to Hoey's linguistic model which allows the selection and the binding of adjacent and non-adjacent sentences. The main contribution of our work consists in proposing a method based on both Hoey's linguistic model and a special graph mining technique, called CoHoP mining, to extract coherent sub-parts of the graph representation of the text. We have conducted some experiments on several English texts showing the interest of the proposed approach.

Keywords: Graph minig; Text exploration; Hoey's linguistic model; Sentence networks

Domains: Document and Text Processing; Machine Learning [cs.LG]; Artificial Intelligence [cs.AI]

Solen Quiniou, Peggy Cellier, Thierry Charnois, Dominique Legallois. Graph Mining under Linguistic Constraints to Explore Large Texts. 14th international conference on Computational Linguistics and Intelligent Text Processing (CICLing'13), Mar 2013, Samos, Greece. pp.239-250. ⟨hal-00817068⟩