Publication
DFKI KeyWE: Ranking keyphrases extracted from scientific articles
Kathrin Eichler; Günter Neumann
In: Proceedings of the Fifth International Workshop on Semantic Evaluations. International Workshop on Semantic Evaluation (SemEval-2010), located at ACL, June 15-16, Uppsala, Sweden, ACL, 2010.
Abstract
A central issue for making the content
of a scientific document quickly accessible
to a potential reader is the extraction
of keyphrases, which capture the main
topic of the document. Keyphrases can
be extracted automatically by generating a
list of keyphrase candidates, ranking these
candidates, and selecting the top-ranked
candidates as keyphrases. We present the
KeyWE system, which uses an adapted
nominal group chunker for candidate extraction
and a supervised ranking algorithm
based on support vector machines
for ranking the extracted candidates. The
system was evaluated on data provided
for the SemEval 2010 Shared Task on
Keyphrase Extraction.