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) befindet sich 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.


dilia_acl2010_FINAL.pdf (pdf, 86 KB)

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence