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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
Wang Dongbo1,2(), Wu Yi1, Ye Wenhao1, Liu Ruilun1
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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Abstract  

[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
ZTFLH:  G350  

Cite this article:

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

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2017.03.07     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2017/V1/I3/54

实体长度 数量(个) 实体长度 数量(个)
2 48 036 13 13
3 23 499 9 9
4 6 878 10 7
1 6 594 12 5
5 1 383 14 2
6 394 11 1
7 182 15 1
8 37 20 1
实体 数量(个) 实体 数量(个)
添加剂 2 243 大米 899
奶粉 1 661 牛奶 810
地沟油 1 178 药袋 733
酱油 1 078 菌落总数 377
1 006 亚硝酸盐 352
猪肉 943 反式脂肪酸 95
甲醛 904 过氧化苯甲酰 90
词语 词性 词长度 是否
实体词
是否
左边界
是否右边界 标记
有关 p 2 N N N S
反式 b 2 Y N N B
脂肪酸 n 3 Y N N E
问题 n 1 N N N S
, wd 1 N N N S
浙江省 ns 3 N N N S
金华市 ns 3 N N N S
公安局 n 3 N N N S
江南 ns 2 N N N S
分局 n 2 N N N S
接到 v 2 N N N S
群众 n 2 N N N S
举报 vn 2 N N N S
v 1 N N N S
测试编号 准确率 召回率 F值
1 89.95% 90.17% 90.06%
2 90.46% 91.01% 90.73%
3 91.89% 90.68% 91.28%
4 88.35% 91.88% 90.08%
5 90.37% 91.06% 90.71%
6 91.01% 90.07% 90.54%
7 91.43% 91.74% 91.58%
8 90.48% 91.01% 90.74%
9 92.12% 91.77% 91.94%
10 90.54% 91.65% 91.09%
均值 90.66% 91.10% 90.88%
测试编号 准确率 召回率 F值
1 72.55% 62.50% 67.15%
2 73.72% 61.89% 67.29%
3 81.90% 65.19% 72.60%
4 84.10% 59.97% 70.01%
5 81.67% 62.49% 70.80%
6 86.52% 63.70% 73.38%
7 81.66% 65.74% 72.84%
8 72.71% 67.10% 69.79%
9 74.72% 63.37% 68.58%
10 80.88% 65.40% 72.32%
均值 79.04% 63.74% 70.48%
编号 条件随机场模型 最大熵模型
训练耗时
(秒)
测试耗时
(毫秒)
训练耗时
(秒)
测试耗时
(毫秒)
1 43 837.09 810 78.01 4
2 41 660.11 1 045 67.01 5
3 43 267.72 980 89.06 78
4 42 078.04 124 67.35 9
5 41 863.00 450 56.43 45
6 43 287.12 160 67.50 7
7 45 677.87 678 57.49 67
8 48 814.89 410 67 56
9 47 691.62 431 78.50 30
10 43 827.01 910 67.59 9
均值 44 200.45 599.8 69.59 31
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