Modelling on Chinese subject-term extracting algorithm
by Kai Gao, Yangjie Li
International Journal of Modelling, Identification and Control (IJMIC), Vol. 13, No. 3, 2011

Abstract: With the rapid development of computer science and technology, information is increasing dramatically. How to analyse and extract useful knowledge effectively from the huge data is becoming more and more important. As the weighted subject-terms can be considered as the condensed versions of documents, on the basis of the statistics and computational linguistics, this paper presents a novel Chinese subject-term extraction algorithm based on paragraph analysing, Chinese segmentation, synonymous and unlisted-term processing. The proposed algorithm can remedy the shortage of pure statistics method and avoid the lower efficiency on semantic analysing. The experimental results and the analysis show the feasible of the approach, and the existing problems and further works are also present in the end.

Online publication date: Sat, 21-Mar-2015

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