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 Anthology, 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-dimensional clusters of both terms and their lexico-syntactic 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 intensional attributes (or properties) valid for all the terms in the n. 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.

• Type: Conference
• Year: 2007
• Where: TSD
• Authors: Pablo Gamallo, Gabriel Pereira Lopes, Alexandre Agustini
• Keywords: Clustering Method, Formal Concept Analysis, POS Annotated Corpus, Signal Processing, TSD 2007