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Food quality management safety risk pre-screening model

A safety risk and food quality technology, which is applied in the field of food quality management safety risk pre-screening model, can solve the problems of long food safety inspection cycle and cumbersome inspection types, and achieve the effect of reducing inspection costs and improving efficiency

Pending Publication Date: 2021-11-02
XINJIANG UNIVERSITY +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, current surveillance technologies expose companies and consumers to significant risks
[0006] 3) The current food safety inspection cycle is long and the inspection types are cumbersome

Method used

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  • Food quality management safety risk pre-screening model
  • Food quality management safety risk pre-screening model
  • Food quality management safety risk pre-screening model

Examples

Experimental program
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Embodiment 1

[0057] 1. Related work

[0058] (1) Text data mining

[0059] Text mining refers to the process of parsing the input text to obtain valuable information. Text classification is a common form of text mining that distinguishes text into the correct category based on corresponding attributes[-]. For example, in this embodiment, it is desired to distinguish between texts with potential food safety hazards and texts without food safety hazards. Supervised deep learning is a popular approach to text classification, a technique that requires each text in a dataset to be pre-labeled with the desired category. The text is then divided into a training set, which is used to build a high-performance predictive model, a validation set, which is used to verify that the model fits the data perfectly, and a test set, which is initially not seen by the model and is then It is used to verify the performance of the model's prediction on unknown data.

[0060] Sentiment analysis is a hot issu...

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Abstract

The invention relates to a food quality management safety risk pre-screening model. The food quality management safety risk pre-screening model comprises the following steps: (1) carrying out text data acquisition and preprocessing; (2) carrying out code vectorization on the preprocessed text data; and (3) judging the food safety hazard degree through an attention scoring mechanism in supervised deep learning. The food quality management safety risk pre-screening model is a novel food text mining technology based on an association attention mechanism, the association score of each word and the food safety hazard is calculated by utilizing mutual information of each word and a unsafety label in consumer comments, and potential interaction between consumers and dangerous food is further mined in combination with attention scores in supervised deep learning, so that potential food safety problems can be quickly screened.

Description

technical field [0001] The invention specifically relates to a food quality management safety risk pre-screening model. Background technique [0002] With the vigorous development of the Internet economy, China's food business model has undergone earth-shaking changes. As of March 2020, the number of online food delivery users in China has reached 397.8 million, the utilization rate of food delivery users has reached 44.0%, and the market penetration rate of food delivery industry has reached 13.0%. Consumers click on their favorite food on the mobile APP, and these food can be delivered to the designated area on time and accurately. While the rise of this takeaway market has brought convenience to consumers, it has also brought huge food safety hazards. According to the 2020 China Health Statistical Yearbook report, there were 38,797 foodborne disease cases in China in 2019, and the proportion of foodborne disease cases in catering service units reached 50%. Among them, ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06N3/04G06N3/08G06F16/35
CPCG06Q10/06395G06Q10/0635G06N3/08G06F16/35G06N3/045Y02P90/30
Inventor 左恩光陈晨吕小毅陈程严紫薇吴伟李敏
Owner XINJIANG UNIVERSITY
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