Abstract
In this paper, we present a combinational approach to automatically supplying keyphrases for a Chinese news documen. In particular, we discuss some factors that have an effect on forming an initial set of keyphrase candidates and filtering unimportant candidates out from the initial set, as well as selecting the best items from the set of the remaining candidates. Experiments show that the approach reaches a satisfactory result.
This work is partially funded by National Natural Science Foundation of Chinese (grant No. 60173005).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Chien, L.F.: PAT-Tree-based keyword Extraction for Chinese Information Retrieval. In: Proceedings of the ACM SIGIR International Conference on Information Retrieval, pp. 50–59 (1997)
Frank, E., Paynter, G.W., Witten, I.H., Gutwin, C., Nevill-Manning, C.G.: Domainspecific keyphrase extraction. In: Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI 1999), pp. 668–673. Morgan Kaufmann, California (1999)
Ong, T., Chen, H.: Updateable PAT-Tree Approach to Chinese Key Phrase Extraction using Mutual Information: A Linguistic Foundation for Knowledge Management. In: Proceedings of 2nd Asian Digital Labrary Conference, Taipei, Taiwan, November 8-9, pp. 63–84 (1999)
Turney, P.D.: Learning algorithms for keyphrase extraction. Information Retrieval 2, 303–336 (2000)
Witten, I.H., Paynter, G.W., Frank, E., Gutwin, C., Nevill-Manning, C.G.: KEA: Practical automatic keyphrase extraction. In: Proceedings of Digital Libraries 1999 (DL 1999), pp. 254–256. ACM Press, New York (1999)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, H., Li, S., Yu, S., Kang, B.K. (2004). A Combining Approach to Automatic Keyphrases Indexing for Chinese News Documents. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2004. Lecture Notes in Computer Science, vol 2945. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24630-5_54
Download citation
DOI: https://doi.org/10.1007/978-3-540-24630-5_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21006-1
Online ISBN: 978-3-540-24630-5
eBook Packages: Springer Book Archive