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Veterinary drug residue knowledge graph construction method based on weighted LDA

A technology for veterinary drug residues and knowledge graphs, applied in semantic tool creation, structured data retrieval, character and pattern recognition, etc., can solve problems such as excessive veterinary drug residues and poisoning

Pending Publication Date: 2020-12-18
CHINA AGRI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the phenomenon of non-standard, illegal use and abuse of veterinary drugs leads to excessive residues of veterinary drugs, which leads to poisoning incidents

Method used

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  • Veterinary drug residue knowledge graph construction method based on weighted LDA
  • Veterinary drug residue knowledge graph construction method based on weighted LDA
  • Veterinary drug residue knowledge graph construction method based on weighted LDA

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Embodiment Construction

[0069] In order to further explain the technical means and effects that the present invention adopts to achieve the intended purpose of the invention, below in conjunction with the accompanying drawings and preferred embodiments, the specific implementation, structure, features and effects of the present invention will be described in detail as follows: back.

[0070] A method for constructing a weighted LDA-based knowledge map of veterinary drug residues, comprising the following steps:

[0071] (1) Construct the knowledge framework of veterinary medicine: use AHP and rule-based methods to extract knowledge from veterinary pharmacology and veterinary toxicology books. Toxicology-related knowledge of veterinary drugs obtained from Pubchem web sites using a wrapper-based approach. Use the jieba word segmentation tool to remove stop words, word segmentation, and part-of-speech tagging on the corpus to form a dictionary and form a hierarchical veterinary drug knowledge framework...

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Abstract

The invention discloses a veterinary drug residue knowledge graph construction method based on weighted LDA (Latent Dirichlet Allocation). The method comprises the following steps: firstly, constructing a veterinary drug knowledge framework, and performing deep search and downloading literature by using a web crawler in combination with the knowledge framework; and aiming at topic noise existing in the LDA topic model and a feature word bias problem, performing topic mining by using a weighted LDA method, and downloading veterinary drug related literatures again; completing named entity identification and relationship extraction by using a dictionary-based model; and finally, utilizing the Neo4j graph database to construct a veterinary drug knowledge graph. The veterinary drug residue knowledge graph can be constructed, veterinary drug residue characteristic rules and causes of damage of veterinary drug residues to human bodies can be found out, the quality safety of meat, eggs and milk is guaranteed, and therefore the body health and life safety of people are protected.

Description

technical field [0001] The invention relates to the field of natural language processing, in particular to a weighted LDA-based method for constructing a knowledge map of veterinary drug residues. Background technique [0002] Food safety issues are attracting more and more attention, among which meat, eggs, and dairy food safety issues are the most important. Veterinary drugs play an important role in the prevention and treatment of animal diseases and the promotion of animal growth. The breeding process of livestock products is inseparable from veterinary drugs. However, the non-standard, illegal use and abuse of veterinary drugs lead to excessive veterinary drug residues, which lead to poisoning incidents. By building a knowledge map of veterinary drug residues, find out the characteristics and rules of veterinary drug residues and the reasons why veterinary drug residues cause harm to the human body, so as to ensure the quality and safety of meat, egg and milk products,...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/28G06F40/216G06F40/242G06F40/289G06F16/35G06K9/62
CPCG06F16/367G06F16/288G06F40/216G06F40/242G06F40/289G06F16/35G06F18/2411
Inventor 郑丽敏杨璐张恬
Owner CHINA AGRI UNIV
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