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摘要:
With the development of public security information system, a large number of food safety cases are stored in the database. This study uses the HMM model and the Viterbi algorithm as text processing technologies. We downloaded 3555 food safety criminal judgments, Chinese word segmentation is an effective way to deal with them. We can find the high frequency words after processing the segmentation results, the key words of the case were extracted, such as the name and carrier of harmful food additives, the crime time and the crime place. The Apriori algorithm is used to analyze the internal rules of common food safety cases, which has certain reference significance for combating and preventing food safety crimes.
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来源 :
PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020)
ISSN: 1948-9439
年份: 2020
页码: 343-348
语种: 英文