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Data Analysis and Knowledge Discovery  2017, Vol. 1 Issue (3): 54-61    DOI: 10.11925/infotech.2096-3467.2017.03.07
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Extracting Events of Food Safety Emergencies with Characteristics Knowledge
Dongbo Wang1,2(),Yi Wu1,Wenhao Ye1,Ruilun Liu1
1College of Information and Technology, Nanjing Agricultural University, Nanjing 210095, China
2Research Center for Correlation of Domain Knowledge, Nanjing Agricultural University, Nanjing 210095, China
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[Objective] This paper aims to extract the events of food safety emergencies from large food safety emergencies. [Methods] First, we built the food safety emergency corpus based on the past events, as well as the data acquisition, labeling, and organization methods of information science. Then, we extracted the corresponding events with the help of conditional random field model, and the distribution characteristics knowledge of the food safety emergencies. [Limitations] We might not be able to apply the feature template created by this research to other fields. [Results] We examined the proposed model with a food safety emergency corpus of 15 million Chinese words, and the F value of this model reached 91.94%. [Conclusions] It is feasible for us to extract the events from food safety emergency corpus with the help of conditional random field model.

Key wordsCharacteristics Knowledge      Conditional Random Fields      Event      Food Safety Emergency     
Received: 03 August 2016      Published: 20 April 2017

Cite this article:

Dongbo Wang,Yi Wu,Wenhao Ye,Ruilun Liu. Extracting Events of Food Safety Emergencies with Characteristics Knowledge. Data Analysis and Knowledge Discovery, 2017, 1(3): 54-61.

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