CN110321460A - A kind of food safety association map construction method and system - Google Patents
A kind of food safety association map construction method and system Download PDFInfo
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- CN110321460A CN110321460A CN201910585147.4A CN201910585147A CN110321460A CN 110321460 A CN110321460 A CN 110321460A CN 201910585147 A CN201910585147 A CN 201910585147A CN 110321460 A CN110321460 A CN 110321460A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/901—Indexing; Data structures therefor; Storage structures
- G06F16/9024—Graphs; Linked lists
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/903—Querying
- G06F16/9032—Query formulation
- G06F16/90324—Query formulation using system suggestions
- G06F16/90328—Query formulation using system suggestions using search space presentation or visualization, e.g. category or range presentation and selection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/908—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
Abstract
The invention discloses a kind of food safety association map construction method and systems, including establishing a variety of incidence relations between food security standard；Establish a variety of incidence relations between food safety sampling observation data and food security standard；Chart database mapping, the key index of the metadata of food security standard and food safety sampling observation data is mapped as to the node of chart database, is the side of chart database by the relationship maps between association, food safety sampling observation data and the food security standard between food security standard；Based on chart database search result structuring food prods security association map；Food security standard data and sampling observation data are incorporated map by this method, construct food safety association map, realize the association analysis between complicated correlation inquiry, food safety sampling observation inspection data and the standard of food security standard, facilitate the inspection and analysis of the food-safe related data of related personnel, provides more preferable decision support for food safety Regulation.
Description
Technical field
The present invention relates to food safety big data fields, and in particular, to a kind of food safety association map construction method
And system.
Background technique
Field of food safety relevant criterion is not only many kinds of, but also relatively independent between standard.Query criteria is big at present
The table consulting relevant criterion file by hand or providing using the conventional relationship type database established based on normative document is be provided
Lattice are inquired.Manual accessed document mode is time-consuming and laborious, retrieves very slow；Conventional relationship data base querying can only pass through bivariate table
The external key of lattice establishes the simple connection between standard, cannot achieve the complicated correlation inquiry between standard and analysis.
Food Inspection is to be carried out according to food security standard, but good pass is not set up between inspection result data and standard
Connection, is not carried out association mining food safety data, better decision support can not be provided for food safety Regulation.
Summary of the invention
The present invention provides a kind of food safeties to be associated with map construction method and system, this method and system for food safety
Normal data and sampling observation data incorporate map, construct a kind of food safety association map, realize answering for food security standard
Miscellaneous correlation inquiry, food safety sampling observation inspection data and standard between association analysis, greatly instant food reviewer and
The inspection and analysis of the food-safe related data of food safety data analyst provide more preferable decision for food safety Regulation
It supports.
For achieving the above object, one aspect of the present invention provides a kind of food safety association map construction method, institute
The method of stating includes:
Step 1: acquisition field of food safety relevant criterion；
Step 2: extracting the metadata of food security standard, including entity metadata, classification metadata and relationship metadata；
Step 3: extracting the key index of food safety sampling observation inspection result；
Step 4: establishing a variety of incidence relations between food security standard；
Step 5: establishing a variety of incidence relations between food safety sampling observation data and food security standard；
Step 6: chart database mapping, by the key index of the metadata of food security standard and food safety sampling observation data
It is mapped as the node of chart database, by association, food safety sampling observation data and the food security standard between food security standard
Between relationship maps be chart database side；
Step 7: utilizing figure query language efficient retrieval chart database, search result is based on D3.JS Rendering and B/S frame
Structure structuring food prods security association map.
Further, step 7 further include: food-safe standard and food safety sampling observation data carry out labeling and complete
Text index, and the food safety of full-text index step 7 building is associated with map.
Further, food security standard includes: the food safety universal standard, food safety product standard, the method for inspection
Standard, limit standard, food additives and some areas and professional standard.
Further, entity metadata includes food standard, inspection project, limit standard, method standard；Classification metadata
Including disabling veterinary drug, residue of veterinary drug, banned pesticides, pesticide residue, banned substance and the micro- life of invasive organism, non-pathogenic
Object, mycotoxin, helminth index, metal pollutant, food additives, organoleptic indicator, physical and chemical index, nutrition fortifier, its
His pollutant.
Further, the key index of food safety sampling observation data includes: food name, inspection project, manufacturing enterprise, quilt
Sampling unit, sampling link, limit standard, inspection result.
Further, the association between food security standard includes: between the food safety universal standard and product standard
Being associated between association, product standard and limit standard, being associated between limit standard and test method standard.
Further, food safety sampling observation data pass through food name, inspection three key indexes of project and limit standard
It is associated with respectively with food safety product standard, Food Safety Analysis standard, the foundation of food safety limit standard.
Further, the chart database in this method uses Neo4j chart database, and figure query language uses Cypher.
Further, this method is according to food security standard classification and title, in conjunction with Lucene full-text index food safety
It is associated with map.
Further, this method is associated with map using D3.JS rendering food safety, and providing the map based on B/S framework is in
Existing mode.
On the other hand, the present invention also provides a kind of food safeties to be associated with map construction system, the system comprises:
Standard acquisition unit, for acquiring field of food safety relevant criterion；
Metadata extraction unit, for extracting the metadata of food security standard, including entity metadata, classification metadata
And relationship metadata；
Key index extracting unit, for extracting the key index of food safety sampling observation inspection result；
Unit is established in first association, for establishing the association between food security standard；
Unit is established in second association, for establishing being associated between food safety sampling observation data and food security standard；
Map unit is mapped for chart database, inspects the metadata of food security standard and food safety by random samples data
Key index is mapped as the node of chart database, by association, food safety sampling observation data and the food between food security standard
Relationship maps between safety standard are the side of chart database；
Food safety is associated with map construction unit, for retrieving chart database using figure query language, is based on search result
Structuring food prods security association map.
One or more technical solution provided by the invention, has at least the following technical effects or advantages:
A kind of food safety association map construction method and system, pass through the first number for extracting food security standard in the present invention
According to the key index with extraction food safety sampling observation data, establish between food security standard, food security standard and extraction are eaten
Product inspect safely a variety of associations between data by random samples, and are mapped by chart database, and figure query language efficient retrieval figure is utilized
Database provides food peace according to search result structuring food prods security association map for the personnel of food safety and related fields
The complete relevant efficient retrieval of standard and analysis.
Present method solves inefficiency problems and traditional relational that field of food safety browses food security standard by hand
Database cannot achieve the problem of retrieval and analysis based on figure, and this method provides for food safety correlation analysis with supervisor
Based on the Food Safety Analysis and digging tool of association map, the recall precision and food safety of food security standard are improved
Analysis and the level excavated, provide better decision support for food safety Regulation.
Detailed description of the invention
Attached drawing described herein is used to provide to further understand the embodiment of the present invention, constitutes of the invention one
Point, do not constitute the restriction to the embodiment of the present invention；
Fig. 1 is a kind of flow diagram of food safety association map construction method in the present invention；
Fig. 2 is a kind of composition schematic diagram of food safety association map construction system in the present invention.
Specific embodiment
To better understand the objects, features and advantages of the present invention, with reference to the accompanying drawing and specific real
Applying mode, the present invention is further described in detail.It should be noted that in the case where not conflicting mutually, it is of the invention
Feature in embodiment and embodiment can be combined with each other.
In the following description, numerous specific details are set forth in order to facilitate a full understanding of the present invention, still, the present invention may be used also
Implemented with being different from the other modes being described herein in range using other, therefore, protection scope of the present invention is not by under
The limitation of specific embodiment disclosed in face.
The present invention provides the invention proposes a kind of food safeties to be associated with map construction method, comprising: 1) acquires food
The relevant standard in security fields；2) metadata of food security standard is extracted；3) key index of Food Inspection data is extracted；4)
Establish a variety of incidence relations between food security standard；5) it establishes between food safety sampling observation data and food security standard
A variety of incidence relations；6) chart database maps, and the key of the metadata of food security standard and food safety sampling observation data is referred to
Mark is mapped as the node of chart database, by association, food safety sampling observation data and the food safety mark between food security standard
Relationship maps between standard are the side of chart database, are stored using Neo4j chart database；7) figure query language Cypher high is utilized
Effect retrieval chart database, search result are based on D3.JS Rendering and B/S framework structuring food prods security association map.
Referring to FIG. 1, one of present invention food safety is associated with map construction method, comprising steps of
Step 1, the relevant standard of acquisition field of food safety, including the food safety universal standard, food safety product mark
Standard, test method standard, limit standard, food additives and some areas and professional standard.
Step 2, the metadata of food security standard, including entity metadata, classification metadata and relationship metadata are extracted,
Wherein entity metadata includes food standard, limit standard, inspection project, method standard；Classification metadata include disabling veterinary drug,
Residue of veterinary drug, banned pesticides, pesticide residue, banned substance and invasive organism, mycotoxin, are posted non-pathogenic microorganisms
Infested index, metal pollutant, food additives, organoleptic indicator, physical and chemical index, nutrition fortifier, other pollutants；This step
Data will be used for step 4 and step 5, for establishing between food security standard and food security standard and food safety are taken out
Examine the association between data.
Step 3, extract Food Inspection data key index, mainly include food name, examine project, manufacturing enterprise,
It is sampled unit, sampling link, limit standard, inspection result etc.；The purpose of extraction is to establish to extract Food Inspection number for step 5
According to key index between a variety of associations provide basis.
Step 4, a variety of incidence relations between food security standard are established, mainly include the food safety universal standard and production
Being associated between the association, product standard and limit standard between product standard, the pass between limit standard and test method standard
Connection etc.；This step provides basis for the mapping of step 6 chart database.
Step 5, a variety of incidence relations between food safety sampling observation data and food security standard, tainted food number are established
It is examined respectively with food safety product standard, food safety according to by three food name, inspection project, limit standard key indexes
Standard inspection is quasi-, food safety limit standard establishes association.This step provides basis for the mapping of step 6 chart database.
Step 6, chart database maps, by the key index of the metadata of food security standard and food safety sampling observation data
It is mapped as the node of chart database, by association, food safety sampling observation data and the food security standard between food security standard
Between relationship maps be chart database side, using Neo4j chart database store.Node expression object, such as specific standard,
Some examines project or manufacturing enterprise etc., and side indicates the relationship between node.The characteristics of object, is abstracted as label and node
Attribute, according to label to node-classification.Also there are classification and weight in side, and wherein weight embodies the tightness degree of incidence relation.
Step 7, using figure query language Cypher inquire and analyze food security standard between and food security standard with
Inspect the association between data by random samples.
Step 8, using labeling and full-text index, abstract data, provide different perspectives, different dimensions inquiry and point
Analysis；It both can provide in conjunction with the entire map of Lucene full-text index based on chart database according to food security standard classification and title
Correlation inquiry, and can provide the full-text search of any keyword.
Step 9, map is associated with using D3.JS rendering food safety, the map presentation mode based on B/S framework is provided.
Referring to FIG. 2, the present invention also provides a kind of food safeties to be associated with map construction system, the system comprises:
Standard acquisition unit, for acquiring field of food safety relevant criterion；
Metadata extraction unit, for extracting the metadata of food security standard, including entity metadata, classification metadata
And relationship metadata；
Key index extracting unit, for extracting the key index of food safety sampling observation inspection result；
Unit is established in first association, for establishing the association between food security standard；
Unit is established in second association, for establishing being associated between food safety sampling observation data and food security standard；
Map unit is mapped for chart database, inspects the metadata of food security standard and food safety by random samples data
Key index is mapped as the node of chart database, by association, food safety sampling observation data and the food between food security standard
Relationship maps between safety standard are the side of chart database；
Food safety is associated with map construction unit, for retrieving chart database using figure query language, is based on search result
Structuring food prods security association map.
Above-mentioned food safety association map construction method and system, the data for describing food safety association chart system are come
Source, data are extracted, and the analysis and foundation of data correlation relation are realized using Neo4j chart database and Lucene full-text search
This method and system.It is associated with map using the food safety that the above method and system construct, food security standard and food are examined
It tests data and incorporates association map, provide knowledge retrieval, excavation and presentation mode based on figure.
Although preferred embodiments of the present invention have been described, it is created once a person skilled in the art knows basic
Property concept, then additional changes and modifications may be made to these embodiments.So it includes excellent that the following claims are intended to be interpreted as
It selects embodiment and falls into all change and modification of the scope of the invention.
Obviously, various changes and modifications can be made to the invention without departing from essence of the invention by those skilled in the art
Mind and range.In this way, if these modifications and changes of the present invention belongs to the range of the claims in the present invention and its equivalent technologies
Within, then the present invention is also intended to include these modifications and variations.
Claims (10)
1. a kind of food safety is associated with map construction method, which is characterized in that the described method includes:
Step 1: acquisition field of food safety relevant criterion；
Step 2: extracting the metadata of food security standard, including entity metadata, classification metadata and relationship metadata；
Step 3: extracting the key index of food safety sampling observation inspection result；
Step 4: establishing the association between food security standard；
Step 5: establishing being associated between food safety sampling observation data and food security standard；
Step 6: chart database mapping maps the key index of the metadata of food security standard and food safety sampling observation data
It, will be between association, food safety sampling observation data and the food security standard between food security standard for the node of chart database
Relationship maps be chart database side；
Step 7: retrieving chart database using figure query language, be based on search result structuring food prods security association map.
2. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that step 7 further include:
Food-safe standard and food safety sampling observation data carry out labeling and full-text index, and construct in full-text index step 7
Food safety be associated with map.
3. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that food security standard
It include: the food safety universal standard, food safety product standard, test method standard, limit standard, food additives and portion
Region-by-region and professional standard.
4. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that entity metadata packet
Include food standard, inspection project, limit standard, method standard；Classification metadata includes disabling veterinary drug, residue of veterinary drug, disabling agriculture
Medicine, pesticide residue, banned substance and invasive organism, non-pathogenic microorganisms, mycotoxin, helminth index, metal are dirty
Contaminate object, food additives, organoleptic indicator, physical and chemical index, nutrition fortifier, other pollutants.
5. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that food safety sampling observation
The key index of data includes: food name, inspection project, manufacturing enterprise, is sampled unit, sampling link, limit standard, inspection
Test result.
6. a kind of food safety according to claim 3 is associated with map construction method, which is characterized in that food security standard
Between association include: being associated with, between product standard and limit standard between the food safety universal standard and product standard
Being associated between association, limit standard and test method standard.
7. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that food safety sampling observation
Data are pacified with food safety product standard, food respectively by food name, inspection three key indexes of project and limit standard
Full test stone, food safety limit standard establish association.
8. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that the figure in this method
Database uses Neo4j chart database, and figure query language uses Cypher.
9. a kind of food safety according to claim 1 is associated with map construction method, which is characterized in that this method is according to food
The classification of product safety standard and title are associated with map in conjunction with Lucene full-text index food safety.
10. a kind of food safety is associated with map construction system, which is characterized in that the system comprises:
Standard acquisition unit, for acquiring field of food safety relevant criterion；
Metadata extraction unit, for extracting the metadata of food security standard, including entity metadata, classification metadata and pass
It is metadata；
Key index extracting unit, for extracting the key index of food safety sampling observation inspection result；
Unit is established in first association, for establishing the association between food security standard；
Unit is established in second association, for establishing being associated between food safety sampling observation data and food security standard；
Map unit is mapped for chart database, by the key of the metadata of food security standard and food safety sampling observation data
Index is mapped as the node of chart database, by association, food safety sampling observation data and the food safety between food security standard
Relationship maps between standard are the side of chart database；
Food safety is associated with map construction unit, for retrieving chart database using figure query language, is constructed based on search result
Food safety is associated with map.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110781315A (en) * | 2019-10-16 | 2020-02-11 | 华中农业大学 | Food safety knowledge map and construction method of related intelligent question-answering system |
| CN111598408A (en) * | 2020-04-23 | 2020-08-28 | 成都数之联科技有限公司 | Construction method and application of trade information risk early warning model |
| CN113590837A (en) * | 2021-07-29 | 2021-11-02 | 华中农业大学 | Deep learning-based food and health knowledge map construction method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106326422A (en) * | 2016-08-24 | 2017-01-11 | 北京大学 | Method and system for retrieving food security data information based on knowledge ontology |
| BR102015026814A2 (en) * | 2015-10-22 | 2017-07-11 | Universidade Federal Do Paraná | PROCESS OF PH ESTIMATION IN PALMITO |
| CN109447530A (en) * | 2018-12-25 | 2019-03-08 | 北京食安链科技有限公司 | A kind of foodsafety automatically analyzes and Warning System and method |
| CN109816405A (en) * | 2019-02-14 | 2019-05-28 | 江门出入境检验检疫局检验检疫技术中心 | A kind of two dimensional code food safety detection method |
-
2019
- 2019-07-01 CN CN201910585147.4A patent/CN110321460A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| BR102015026814A2 (en) * | 2015-10-22 | 2017-07-11 | Universidade Federal Do Paraná | PROCESS OF PH ESTIMATION IN PALMITO |
| CN106326422A (en) * | 2016-08-24 | 2017-01-11 | 北京大学 | Method and system for retrieving food security data information based on knowledge ontology |
| CN109447530A (en) * | 2018-12-25 | 2019-03-08 | 北京食安链科技有限公司 | A kind of foodsafety automatically analyzes and Warning System and method |
| CN109816405A (en) * | 2019-02-14 | 2019-05-28 | 江门出入境检验检疫局检验检疫技术中心 | A kind of two dimensional code food safety detection method |
Non-Patent Citations (1)
| Title |
|---|
| 叶金珠等: "基于知识图谱的国内食品安全研究可视化分析", 《安徽农业科学》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110781315A (en) * | 2019-10-16 | 2020-02-11 | 华中农业大学 | Food safety knowledge map and construction method of related intelligent question-answering system |
| CN110781315B (en) * | 2019-10-16 | 2022-11-08 | 华中农业大学 | Food safety knowledge graph and construction method of related intelligent question-answering system |
| CN111598408A (en) * | 2020-04-23 | 2020-08-28 | 成都数之联科技有限公司 | Construction method and application of trade information risk early warning model |
| CN111598408B (en) * | 2020-04-23 | 2023-04-18 | 成都数之联科技股份有限公司 | Construction method and application of trade information risk early warning model |
| CN113590837A (en) * | 2021-07-29 | 2021-11-02 | 华中农业大学 | Deep learning-based food and health knowledge map construction method |
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Application publication date: 20191011 |