Automatic keyphrase extraction from medical documents

Abstract

Keyphrases provide semantic metadata that summarizes the documents and enable the reader to quickly determine whether the given article is in the reader's fields of interest. This paper presents an automatic keyphrase extraction method based on the naive Bayesian learning that exploits a number of domain-specific features to boost up the keyphrase extraction performance in medical domain. The proposed method has been compared to a popular keyphrase extraction algorithm, called Kea. © 2009 Springer-Verlag Berlin Heidelberg.