Inducing Classes of Terms from Text

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

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.
Original languageUnknown
Title of host publicationLecture Notes in Computer Science
Pages31-38
Publication statusPublished - 1 Jan 2007
EventText, Speech and Dialogue -
Duration: 1 Jan 2007 → …

Conference

ConferenceText, Speech and Dialogue
Period1/01/07 → …

Cite this

Lopes, J. G. P. (2007). Inducing Classes of Terms from Text. In Lecture Notes in Computer Science (pp. 31-38)