Abstract
Keyphrases are very useful for saving time on browsing through the news web pages. A new keyphrase extraction method from Chinese news web pages based on semantic relations is presented in this paper. Semantic relations between phrases are analyzed, and a lexical chain is used to construct a semantic relation graph. Keyphrases are extracted and a semantic link graph is built on the lexical chains. News web pages with core hints are selected from www.163.com to test our method. The experimental results show that the proposed method substantially outperforms the method based on term frequency, especially when the number of keyphrases extracted is 3 - the precision is improved by 26.97 percent, and the recall is improved by 20.93 percent. © 2008 Springer-Verlag Berlin Heidelberg.
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Xie, F., Wu, X., Hu, X. G., & Wang, F. Y. (2008). Keyphrase extraction from chinese news web pages based on semantic relations. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5075 LNCS, pp. 490–495). https://doi.org/10.1007/978-3-540-69304-8_51
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