TermITH-Eval: a French Standard-Based Resource for Keyphrase Extraction Evaluation
| Autor: | Bougouin, Adrien, Barreaux, Sabine, Romary, Laurent, Boudin, Florian, Daille, Béatrice |
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| Přispěvatelé: | Laboratoire d'Informatique de Nantes Atlantique (LINA), Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-Université de Nantes (UN), Institut de l'information scientifique et technique (INIST), Centre National de la Recherche Scientifique (CNRS), Analyse Linguistique Profonde à Grande Echelle, Large-scale deep linguistic processing (ALPAGE), Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Paris Diderot - Paris 7 (UPD7), Boudin, Florian, Mines Nantes (Mines Nantes)-Université de Nantes (UN)-Centre National de la Recherche Scientifique (CNRS), Humboldt University Of Berlin |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
[INFO.INFO-TT]Computer Science [cs]/Document and Text Processing
automatic evaluation [INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR] InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL [INFO.INFO-TT] Computer Science [cs]/Document and Text Processing TermITH-Eval [INFO]Computer Science [cs] [INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR] structured resource [INFO] Computer Science [cs] keyphrase extraction |
| Zdroj: | LREC-Language Resources and Evaluation Conference LREC-Language Resources and Evaluation Conference, May 2016, Potoroz, Slovenia LREC-Language Resources and Evaluation Conference, May 2016, Potoroz, Slovenia. pp.1924-1927 |
| Popis: | International audience; Keyphrase extraction is the task of finding phrases that represent the important content of a document. The main aim of keyphrase extraction is to propose textual units that represent the most important topics developed in a document. The output keyphrases of automatic keyphrase extraction methods for test documents are typically evaluated by comparing them to manually assigned reference keyphrases. Each output keyphrase is considered correct if it matches one of the reference keyphrases. However, the choice of the appropriate textual unit (keyphrase) for a topic is sometimes subjective and evaluating by exact matching underestimates the performance. This paper presents a dataset of evaluation scores assigned to automatically extracted keyphrases by human evaluators. Along with the reference keyphrases, the manual evaluations can be used to validate new evaluation measures. Indeed, an evaluation measure that is highly correlated to the manual evaluation is appropriate for the evaluation of automatic keyphrase extraction methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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