Discovering linguistic patterns using sequence mining

Nicolas Béchet (1) , Peggy Cellier (2) , Thierry Charnois (1) , Bruno Crémilleux (1)

1 Equipe CODAG - Laboratoire GREYC - UMR6072
2 LIS - Logical Information Systems

In this paper, we present a method based on data mining techniques to automatically discover linguistic patterns matching appositive qualifying phrases. We develop an algorithm mining sequential patterns made of itemsets with gap and linguistic constraints. The itemsets allow several kinds of information to be associated with one term. The advantage is the extraction of linguistic patterns with more expressiveness than the usual sequential patterns. In addition, the constraints enable to automatically prune irrelevant patterns. In order to manage the set of generated patterns, we propose a solution based on a partial ordering. A human user can thus easily validate them as relevant linguistic patterns.We illustrate the efficiency of our approach over two corpora coming from a newspaper

Domaines: Intelligence artificielle [cs.AI]; Base de données [cs.DB]; Traitement du texte et du document

Nicolas Béchet, Peggy Cellier, Thierry Charnois, Bruno Crémilleux. Discovering linguistic patterns using sequence mining. 13th Int. Conf. on Intelligent Text Processing and Computational Linguistics (CICLing'12), Mar 2012, new delhi, India. pp.154-165. ⟨hal-01023109⟩