Single-label hep-ex Clustering Corpus

Autores:
URL:
Contacto:

David Eduardo Pinto Avendaño <dpintocs.buap.mx>

Descripción

This corpus is a pre-processed version of the collection of scientific abstracts compiled by the University of Jaén, Spain named hep-ex [1].

Funcionalidad

The aim of the pre-processed version of this corpus is to support experiments of supervised and unsupervised classifiers with narrow domain short texts.

Tecnología

The corpus (raw text) and the gold standard are provided.

Requisitos técnicos

No special requirements are needed in order to use the corpus.

Módulos

-

Innovación

A relatively big pre-processed collection which may be used to experiment with different clustering methods on the narrow domain short-text clustering task.

Desarrollo

Developed as part of David Pinto Ph.D. and the MiDES CICYT TIN2006-15265-C06-04 research project.

Publicaciones

  • Arturo Montejo-Ráez, Luis Alfonso Ureña-López, Ralf Steinberger; Text Categorization using bibliographic records: beyond document content. Procesamiento del Lenguaje Natural, nº 35, Septiembre 2005.
  • David Pinto, Alfons Juan, Paolo Rosso: A Comparative Study of Clustering Algorithms on Narrow-Domain Abstracts. Procesamiento del Lenguaje Natural 37(1): 43-49, 2006.
  • Héctor Jiménez-Salazar, David Pinto, Paolo Rosso: Uso del Punto de Transición en la Selección de Términos Índice para Agrupamiento de Textos Cortos, Procesamiento del Lenguaje Natural 35(1): 114-118, 2005.
  • David Pinto, José-Miguel Benedí, Paolo Rosso: Clustering Narrow-Domain Short Texts by Using the Kullback-Leibler Distance. CICLing 2007. Lecture Notes in Computer Science 4394, Springer-Verlag: 611-622, 2007.
  • David Pinto, Héctor Jiménez-Salazar, Paolo Rosso: Clustering Abstracts of Scientific Texts Using the Transition Point Technique. CICLing 2006. Lecture Notes in Computer Science 3878, Springer-Verlag:536-546, 2006.