Automatic keyphrase extraction from scientific articles

Abstract

This paper describes the organization and results of the automatic keyphrase extraction task held at the Workshop on Semantic Evaluation 2010 (SemEval-2010). The keyphrase extraction task was specifically geared towards scientific articles. Systems were automatically evaluated by matching their extracted keyphrases against those assigned by the authors as well as the readers to the same documents. We outline the task, present the overall ranking of the submitted systems, and discuss the improvements to the state-of-the-art in keyphrase extraction.

Publication
Lang. Resour. Eval.
Min-Yen Kan
Min-Yen Kan
Associate Professor

WING lead; interests include Digital Libraries, Information Retrieval and Natural Language Processing.