A ranking approach to keyphrase extraction

Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009

Volumn , Issue , 2009, Pages 756-757

  Jiang, Xin ^a   Hu, Yunhua ^b   Li, Hang ^b  

^a PEKING UNIVERSITY   (China)

^b MICROSOFT RESEARCH ASIA   (China)

Author keywords

Keyphrase extraction; Learning to rank; Ranking SVM

Indexed keywords

BASELINE METHODS; DATA SETS; KEYPHRASE EXTRACTION; LEARNING METHODS; LEARNING TO RANK; NAIVE BAYES; RANKING APPROACH; RANKING SVM; STATE-OF-ART METHODS;

INFORMATION RETRIEVAL; INFORMATION SERVICES; SUPPORT VECTOR MACHINES;

EDUCATION;

EID: 72449211067     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1571941.1572113     Document Type: Conference Paper

References (4)

1. E. Frank, G. W. Paynter, I. H. Witten, C. Gutwin, and C. G. Nevill-Manning. Domain-specific keyphrase extraction. In IJCAI '99, pages 668-673, 1999.
2. R. Herbrich, T. Graepel, and K. Obermayer. Large margin rank boundaries for ordinal regression. In Advances in Large Margin Classifiers, pages 115-132. MIT Press, 2000.
3. P. D. Turney. Learning to extract keyphrases from text. Technical Report ERB-1057, National Research Council, Institute for Information Technology, 2000.
4. E. Xun, C. Huang, and M. Zhou. A unified statistical model for the identification of English baseNP. In ACL '00, pages 109-116.