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.


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.



Weitere Links