Artículos

 

Single-Document Keyphrase Extraction for Multi-Document Keyphrase Extraction

 

Extracción de palabras clave de documentos individuales para extracción de palabras clave de documentos múltiples

 

Gábor Berend¹ and Richárd Farkas²

 

¹ University of Szeged, Department of Informatics, Árpád tér 2., 6720 Szeged, Hungary berendg@inf.u-szeged.hu

² University of Szeged, Department of Informatics, Árpád tér 2., 6720 Szeged, Hungary rfarkas@inf.u-szeged.hu

 

Article received on 07/12/2012
Accepted on 13/01/2013.

 

Abstract

Here, we address the task of assigning relevant terms to thematically and semantically related sub-corpora and achieve superior results compared to the baseline performance. Our results suggest that more reliable sets of keyphrases can be assigned to the semantically and thematically related subsets of some corpora if the automatically determined sets of keyphrases for the individual documents of an entire corpus are identified first. The sets of keyphrases assigned by our proposed method for the workshops present in the ACL Anthology Corpus over a 6-year period were considered better in more than 60% of the test cases compared to our baseline system when evaluated against an aggregation of different human judgements.

Keywords: Multi-document keyphrase extraction, knowledge management, information retrieval.

 

Resumen

En este artículo se considera el tema de asignación de términos relevantes a sub-corpus con temas y semántica relacionados y se logran resultados superiores a los del rendimiento de referencia. Los resultados obtenidos en este trabajo muestran que los conjuntos más confiables de palabras clave pueden ser asignados a subconjuntos con temas y semántica relacionados de un corpus si primero se identifican automáticamente los subconjuntos de palabras clave de documentos individuales en todo corpus. Los conjuntos de palabras clave asignados mediante el método propuesto para los talleres incluidos en ACL Anthology Corpus para el periodo de 6 años fueron considerados mejor en más de 60.

Palabras clave: Extracción de palabras clave de documentos múltiples, administración de conocimiento, recuperación de información.

 

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Acknowledgments

This work was in part supported by the European Union and the European Social Fund through the project FuturICT.hu (grant no.: TÁMOP-4.2.2.C-11/1/KONV-2012-0013).

 

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