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A method and application of automatic term extraction using conditional random fields

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2 Author(s)
Weijun Fu ; CISTR, Beijing University of Posts and Telecommunications, P.R.C., 100876 ; Lei Li

A conditional random fields (CRF) based method and application of automatic term extraction was proposed in this paper according to the theory of ldquoInformation -Knowledge - Intelligencerdquo transformation. A CRF model was created by training the different fields of the corpus segmented and tagged. Using the model trained by CRF, the documents in a given field were automatically tagged and the terms in the field was automatically extracted with a certain way. On this basis, this method was used in automatic text summarization system to enhance the rate of the excellent summary. The experimental results showed that this method had a relatively high recall rate and accuracy, could effectively increase the performance of automatic summarization system.

Published in:

Natural Language Processing and Knowledge Engineering, 2009. NLP-KE 2009. International Conference on

Date of Conference:

24-27 Sept. 2009