Fresh food supply chain knowledge graph construction method based on semi-structured data

A semi-structured data and structured data technology, applied in the field of knowledge map construction, can solve the problems of large data volume, fast update speed, and low data value density, and achieve low data density, fast update speed, and easy understanding and use Effect

Pending Publication Date: 2020-09-22
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
View PDF3 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Through the collection and processing of semi-structured data, the quality of the constructed knowledge map is improved; the Neo4j graph database is used to store the data to solve the problems of low value density, large data volume and fast update speed in the fresh food supply chain

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Fresh food supply chain knowledge graph construction method based on semi-structured data
  • Fresh food supply chain knowledge graph construction method based on semi-structured data
  • Fresh food supply chain knowledge graph construction method based on semi-structured data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] In order to make the technical problems, technical solutions and beneficial effects to be solved by the present invention clearer, the present invention will be described in detail below in conjunction with the accompanying drawings. It should be noted that the specific embodiments described here are only used to explain the present invention, and are not intended to limit the present invention. Products that can achieve the same function are equivalent replacements and improvements, and are included in the protection scope of the present invention.

[0054] According to an embodiment of the present invention, see Figure 1-2 , a fresh food supply chain knowledge map construction method based on semi-structured data, specifically including the following steps:

[0055] Step 1: Since the fresh food supply chain data existing in the webpage is semi-structured and has a large amount of data, the use of crawler technology can greatly improve the efficiency of data acquisiti...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention provides a fresh food supply chain knowledge graph construction method based on semi-structured data, which is used for collecting and processing the semi-structured data to achieve thepurposes of effectively integrating the existing data resources and exploring the intrinsic data value of massive information, so that a high-quality knowledge graph with a rigorous structure and a complete system is constructed. Semi-structured data in a webpage where a target is located are crawled by utilizing a webpage crawler technology, so that the data acquisition efficiency is improved; aplurality of pieces of structured data containing entity names and entity attributes are obtained by means of a regular expression, so that the constructed knowledge graph is more scientific and accurate; the structuralization is converted into an RDF triple form by using a structuralization data mapping tool D2RML which is convenient for a user to use and understand; mapping from RDF triple datato a graph data structure is achieved, fresh food supply chain data are stored in a Neo4j graph database, and the problems that the fresh food supply chain data size is large, the data value density is low, and the updating speed is high are solved.

Description

technical field [0001] The invention relates to the technical field of knowledge graph construction, in particular to a method for constructing a fresh food supply chain knowledge graph based on semi-structured data. Background technique [0002] With the rapid development of China's economy, people's living standards and quality of life have been improved. At the same time, more and more attention has been paid to the quality and safety of food. As the main source of food in people's daily life, fresh food has also received more and more attention. Successively, some fresh food brands have also launched the traceability function, which puts the supply chain information of the production, storage, transportation, sales and other links of fresh food on the traceability platform for consumers to query and use. However, most of this information is unstructured or semi-structured data existing in web pages, making it difficult for consumers to quickly and accurately find the in...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/36G06F16/951G06F16/84G06F16/28G06F16/31
CPCG06F16/367G06F16/951G06F16/84G06F16/313G06F16/288
Inventor 刘新亮谷情张梦琪高圣乔张腾
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products