Inducing Classes of Terms from Text

This paper describes a clustering method for organizing in semantic classes a list of terms. The experiments were made using a POS annotated corpus, the ACL Antology, which consists of technical articles in the field of Computational Linguistics. The method, mainly based on some assumptions of Formal Concept Analysis, consists in building bi-dimentional clusters of both terms and their lexico-sintactic contexts. Each generated cluster is defined as a semantic class with a set of terms describing the extension of the class and a set of contexts perceived as the intentional attributes (or properties) valid for all terms in the extension. The clustering process relies on two restrictive operations: abstraction and specification. The result is a concept lattice that describes a domain-specific ontology of terms.