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| Research on Complex Time Information Extraction Based on CRF Model |
| Lu Wanhui1,2, Ma Jianxia1 |
1. Lanzhou Branch of National Science Library, Chinese Academy of Sciences, Lanzhou 730000, China;
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract Because of the characteristic of time-serial and polymorphism of the network information, this paper presents a model of extracting the complex time information based on Conditional Random Fields(CRF), and verifies the feasibility of this model through an experiment, compares the results through choosing the features of words (contexts) and word-POS. The experiment shows that the result will be much improved if adding the POS feature.
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Received: 12 August 2011
Published: 03 December 2011
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