Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining

Kata Gábor (1) , Haïfa Zargayouna (1) , Isabelle Tellier (2) , Davide Buscaldi (1) , Thierry Charnois (1)

1 LIPN - Laboratoire d'Informatique de Paris-Nord
2 Lattice - Lattice - Langues, Textes, Traitements informatiques, Cognition - UMR 8094

This paper deals with the extraction of semantic relations from scientific texts. Pattern-based representations are compared to word embeddings in unsupervised clustering experiments, according to their potential to discover new types of semantic relations and recognize their instances. The results indicate that sequential pattern mining can significantly improve pattern-based representations, even in a completely unsupervised setting.

Domaines: Informatique [cs]

Kata Gábor, Haïfa Zargayouna, Isabelle Tellier, Davide Buscaldi, Thierry Charnois. Unsupervised Relation Extraction in Specialized Corpora Using Sequence Mining. XVIth Symposium on Intelligent Data Analysis, Oct 2016, Stockholm, Sweden. pp.237 - 248, ⟨10.1007/978-3-319-46349-0_21⟩. ⟨hal-01405041⟩