CN106709017A - Big data-based aid decision making method - Google Patents
Big data-based aid decision making method Download PDFInfo
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- CN106709017A CN106709017A CN201611226754.4A CN201611226754A CN106709017A CN 106709017 A CN106709017 A CN 106709017A CN 201611226754 A CN201611226754 A CN 201611226754A CN 106709017 A CN106709017 A CN 106709017A
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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- G06F16/248—Presentation of query results
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- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
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Abstract
The invention discloses a big data-based aid decision making method. The method comprises the following steps of: selecting a data dictionary according to a decision making demand; establishing a basic model library by utilizing a keyword mechanism; analyzing and displaying data in the basic model library according to the decision making demand; and carrying out data drilling according to the data analysis result so as to obtain decision making data. According to the method, a big data platform technology, the data dictionary and model construction are effectively grouped together, so that a data analysis system is rapidly and conveniently constructed, aid decision making is carried out, the time consuming expressed by information demand is effectively decreased, the correctness is ensured and the decision making efficiency is improved.
Description
Technical field
The present invention relates to a kind of aid decision-making method based on big data, belong to big data mining analysis technical field.
Background technology
With being continuously increased for personalized decision data service content, the busincess intelligence based on data warehouse is
Important means as big data industry future competition, more demands requirement is excavated to more valuable from big data platform
Content information, aids in more brilliant decision-making to provide data analysis and helps.Based on big data platform, information source and storage form
The features such as with diversity, multiple types, data representation isomery, quick-searching, Analysis of Policy Making in face of mass data, drill through step by step
Deng the dependency relation between data goes to the multisystem data correlation in big data environment from the system application of single fixation, logarithm
According to excavating requirement higher, the data service modes under big data environment, preferably for decision-making is provided are proposed with treatment efficiency
The demand that data are supported increasingly is highlighted.
The content of the invention
For above-mentioned deficiency, the invention provides a kind of aid decision-making method based on big data, it can make decision-making party
Method quickly, simply, is efficiently used.
The present invention solves its technical problem and adopts the technical scheme that：A kind of aid decision-making method based on big data, its
It is characterized in carry out selection data dictionary according to decision requirements, carries out setting up basic model storehouse using keyword mechanism, according to decision-making
Demand is analyzed to the data in basic model storehouse, shows, data results carried out with data mining and obtains decision data.
Further, the aid decision-making method that should be based on big data is comprised the following steps：
Step one：Propose decision requirements：User proposes the decision-making needs to be carried out data mining and displaying, the decision-making
Need at least to include involved service point and excavation purpose；
Step 2：Choose data dictionary：Carry out choosing corresponding data dictionary according to the decision requirements that user proposes；
Step 3：Set up keyword mechanism：In data retrieval, according to the keyword search key word library of retrieval, if
With the retrieval result that the keyword match in key word library then calls the keyword in key word library, if the keyword with it is crucial
Keyword in character library is mismatched, and is retrieved from the data dictionary chosen, and in the data that will be retrieved from data dictionary
Appearance is saved in key word library；
Step 4：Set up basic model storehouse：Keyword, decision requirements and data dictionary are associated according to retrieval result
Basic model is set up, and the basic model of foundation is saved in plinth model library；
Step 5：Carry out data analysis, displaying：Basic model storehouse is called according to decision requirements and relevant rudimentary model is entered
Data results are shown by row analysis with patterned form；
Step 6：Carry out data mining：Data mining is carried out to data results, data root is found, decision-making is formed
Data.
Further, the data dictionary includes knowledge base, policies and regulations storehouse, System Documents storehouse, job instruction, basis
Database, production business library, exchange SB, Analysis of Policy Making storehouse.
Further, the knowledge base includes problem base, hidden danger storehouse and data bank, is asked for quick autonomous learning, lookup
Topic, solve problem；The basic database is used to deposit all kinds of basic dictionary datas and basic agricultural object data, agriculture industry
Business object mainly include cultivated land resource, fertilization compositions based on earth measurement, agricultural product price market, agricultural pest, agriculture feelings and production management,
Agriculture Internet of Things, confirmation of land right；The production business library is used to deposit the business that all kinds of operation system routine work operations are produced
Data；It is described exchange SB be used to realizing and agriculture the superior and the subordinate, between external unit and the Ministry of Agriculture data share exchange need
Ask, be provided with exchange sharing data area, the agriculture business datum for exchanging having shared demand is stored and managed, agricultural sector
Shared data bank with production business library logical separation, should exchange the data source of SB in production business library；The decision-making point
Analysis storehouse is used to deposit the related all kinds of operational datas of agriculture business.To realize agricultural data in-depth analysis and aid decision, with
Data are carried out based on production business library slightly to collect, form Analysis of Policy Making storehouse, and divide with decision-making the characteristics of combination agricultural data
Analysis needs to build subject analysis model.
Further, the basic model includes soil moisture content Early-warning Model, pestforecasting Early-warning Model, envirment factor
Model, agricultural extension model.
Further, in step 5, if not meeting decision requirements in basic model storehouse when calling basic model storehouse
Basic model, then set up new basic model and be saved in basic model storehouse.
Further, the patterned form being shown to data results includes pie chart, block diagram, curve map and row
Table.
The beneficial effects of the invention are as follows：
It is the efficiency of accurate retrieval decision-making effective information in lifting big data environment, fast and effectively finds closed in data
Connection and influence factor, allow data to maximize degree and support decision-making, present invention uses big data platform technology, data dictionary, mould
Type builds effectively tissue and, to together, quickly and easily builds data analysis system, carries out aid decision, and effectively reducing information needs
The time-consuming of expression is asked, the degree of accuracy is ensure that, the efficiency of decision-making is improve.
The invention has the characteristics that：
(1) proposition of decision requirements is the premise of data mining and displaying, and user needs the industry clearly involved by the decision-making
Business point and excavation purpose；
(2) application of data dictionary is according to existing information excavating analysis, for customizing data analysis, it is necessary to set up new
Data model and data dictionary meet demand；
(3) it is that, in order to improve recall precision in data retrieval, can quickly position, go out to sign an undertaking to set up keyword mechanism
Really；
(4) basic model storehouse is set up for business datum mining analysis, for decision requirements provide data mining service；
(5) drilling through for data is to look for data root according to data results, forms decision data.
Brief description of the drawings
With reference to Figure of description, the present invention will be described.
Fig. 1 is flow chart of the method for the present invention；
Fig. 2 is embodied flow chart for the present invention in agricultural application.
Specific embodiment
For the technical characterstic for illustrating this programme can be understood, below by specific embodiment, and its accompanying drawing is combined, to this hair
It is bright to be described in detail.Following disclosure provides many different embodiments or example is used for realizing different knots of the invention
Structure.In order to simplify disclosure of the invention, hereinafter the part and setting to specific examples are described.Additionally, the present invention can be with
Repeat reference numerals and/or letter in different examples.This repetition is that for purposes of simplicity and clarity, itself is not indicated
Relation between various embodiments being discussed and/or being set.It should be noted that part illustrated in the accompanying drawings is not necessarily to scale
Draw.Present invention omits the description to known assemblies and treatment technology and process avoiding being unnecessarily limiting the present invention.
A kind of aid decision-making method based on big data of the invention, it carries out selection data dictionary according to decision requirements,
Carry out setting up basic model storehouse using keyword mechanism, the data in basic model storehouse are analyzed according to decision requirements, are opened up
Show, data results are carried out with data mining and obtains decision data.
As shown in figure 1, the aid decision-making method that should be based on big data includes step in detail below：
Step one：Propose decision requirements：User proposes the decision-making needs to be carried out data mining and displaying, the decision-making
Need at least to include involved service point and excavation purpose.The proposition of decision requirements, is the premise of data mining and displaying, is used
Family needs clearly to do the involved service point of this calculating, clearly excavates purpose.
Step 2：Choose data dictionary：Carry out choosing corresponding data dictionary according to the decision requirements that user proposes.This hair
It is bright to carry out existing information excavating analysis, for customizing data analysis, it is necessary to set up new data model with data dictionary to expire
Sufficient demand.The built-in data dictionary of system, uses for quick-searching matched data.
Step 3：Set up keyword mechanism：In data retrieval, according to the keyword search key word library of retrieval, if
With the retrieval result that the keyword match in key word library then calls the keyword in key word library, if the keyword with it is crucial
Keyword in character library is mismatched, and is retrieved from the data dictionary chosen, and in the data that will be retrieved from data dictionary
Appearance is saved in key word library.In data retrieval, the key search for repeating can cause the process task of machine constantly to repeat,
Be to improve recall precision, set up keyword mechanism, the keyword message of systematic collection retrieval input, incidence relation, data model,
The range of information such as result output, when there is duplicate key word to be input into, can quickly position, provide result.
Step 4：Set up basic model storehouse：Keyword, decision requirements and data dictionary are associated according to retrieval result
Basic model is set up, and the basic model of foundation is saved in plinth model library.Basic model storehouse is used for business datum excavation point
Analysis, the durability in basic model storehouse is strong and precision is as the application of Result is continued to optimize.Basic model storehouse is set up, by institute
There is the content modeled the need for covering in business, it is unified to model library, preferably for decision requirements provide data mining service.
Step 5：Carry out data analysis, displaying：Basic model storehouse is called according to decision requirements and relevant rudimentary model is entered
Data results are shown by row analysis with patterned form.Decision-making level draws data result by the system.
Step 6：Carry out data mining：Data mining is carried out to data results, data root is found, decision-making is formed
Data.Data results content is drilled through step by step, data root is looked for, is accomplished that any decision data has according to can
According to.
Fig. 2 is embodied flow chart for the present invention in agricultural application.As shown in Fig. 2 when the present invention is applied in agricultural
Specific implementation process it is as follows：
First, decision requirements are proposed
The data dictionary that decision requirements can be used with auto-associating, the applicable basic model storehouse of association.Data dictionary is included
Knowledge base, policies and regulations storehouse, job instruction, basic database, production business library, exchange SB, Analysis of Policy Making storehouse etc..
Knowledge base：The basic database such as including problem base, hidden danger storehouse, data bank.Asked for quick autonomous learning, lookup
Topic, solve problem.
Basic database：Base library is mainly used in depositing all kinds of basic dictionary datas and basic agricultural object data.Respectively
Class agricultural business object mainly include cultivated land resource, fertilization compositions based on earth measurement, agricultural product price market, agricultural pest, agriculture feelings and
Production management.The basic datas such as agriculture Internet of Things, confirmation of land right.Each application system of the future of agriculture integrated service all should follow basis
The basic dictionary standard in storehouse, it is unified to use basic agricultural object data.
Production business library：For depositing the business datum that all kinds of operation system routine work operations are produced.Business datum
Storage is arranged and divided according to business scope, and strictly controls access rights, it is ensured that the storage safety of all kinds of operation systems
Property.
Exchange SB：For realize and agriculture the superior and the subordinate, between external unit and the Ministry of Agriculture data share exchange need
Ask, special exchange sharing data area is set, the agriculture business datum for exchanging having shared demand is stored and managed, agricultural
Department's shared data bank should be with production business library logical separation, and its data source is in production business library.
Analysis of Policy Making storehouse：Production business library storage is the related all kinds of operational datas of agriculture business.To realize agricultural
Data in-depth is analyzed and aid decision, and carrying out data based on producing business library slightly collects, and forms Analysis of Policy Making storehouse, and tie
The characteristics of closing agricultural data and Analysis of Policy Making need to build subject analysis model.
2nd, the data dictionary needed for selecting
Data dictionary is various under big data platform, such as knowledge base, policies and regulations storehouse, System Documents storehouse, job instruction,
Decision requirements need to screen related content, for rapid data retrieval provides basic data input.When user proposes decision requirements,
Influence if desired for analysis policies and regulations to the price trend of agricultural product, click data dictionary, system automatic screening matching is current
The dictionary list (price storehouse, policies and regulations storehouse, knowledge base etc.) most agreed with demand, user can also self-defined retrieval data word
Allusion quotation, chooses the several data dictionaries used in demand as data input.
3rd, auto-associating search key
Data retrieval business under big data platform is more, and the retrieval tasks of repeatability are also more, set up keyword association mechanism,
Data retrieval tasks are efficiently completed, the key search result that will occur before takes out, newly-increased key search
Content is added in keyword association storehouse, is that later Data duplication retrieval is used.User input needs the keyword of retrieval, is
System search key storehouse automatic first, if repeatability inquiry, the content results that system was retrieved before finding, directly export
To displaying interface；If keyword does not exist, it is considered as keyword and increases newly, the data content and incidence relation covered in retrieving
Will exist in key word library, convenient repeated retrieval in the future is used.
4th, application foundation model library
After data content prepares completely, data analysis and data mining are realized in calling model storehouse.In basic model storehouse
Model cannot such as meet existing demand, can set up new model to basic model storehouse, system preservation model by mode input
Algorithm realizes content, there is provided used to later data.Under big data platform, the storage form of data has various, HDFS points
Cloth file is stored, HBase distributed data library storages, Hive data warehouse storages etc., and behind calling model storehouse, system is by model
The data for using retrieval analysis from HBase or Hive out, can also build Spark according to data scale and demand scene
Memory database improves data-handling efficiency.By using big data platform and technology, mass data passes through distributed type assemblies reality
Now analysis displaying.Basic model includes soil moisture content Early-warning Model, pestforecasting Early-warning Model, envirment factor model, agricultural
Rate Based On The Extended Creep Model etc..The implementation process of big data, is by data input, model calculating, result application, the degree of accuracy that model is calculated
Result to exporting has a direct impact.Soil moisture content Early-warning Model, pestforecasting Early-warning Model, envirment factor model, agriculture
The various basic models such as industry Rate Based On The Extended Creep Model can use existing model and carry out adaptation to it, it is preferably applied
In the present invention.
5th, data results are provided
By using Dictionary Database, basic model storehouse, data are shown in the page with patterned form, are in the page
Existing content, such as agricultural product (apple) upward price trend analysis graph, is carried out at data by Hive in big data Hadoop
Shown after reason, displayed page realizes data display by calling JSON.
6th, data mining
The result of data analysis can be drilled through step by step, find data source.The purpose of data mining, is by data mining point
Analysis result, finds data root, accomplishes that data are evidence-based, makes the result of decision authentic and valid.User can click data analysis page
The data of any position such as pie chart, block diagram, curve map, the list in face, under get into two grades, the three-level page, each page has
Data analysis content, is shown from different aspect.
7th, result application.Show and drill through by data analysis, determine reliability, the availability of result of calculation, be decision-making
There is provided and support, result is applied in decision-making.The standardization standard content that result application words art is provided according to system, enhancement information
The efficiency of requirement express.
The present invention can realize the flexible linkage of data dictionary, dynamic increase and decrease and Rapid matching, there is provided basic data mould
The implementation of type, for general utility functions rapid modeling, allows decision-making technique quickly, simply, efficiently to be used in every field.
The above is the preferred embodiment of the present invention, for those skilled in the art,
Without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications are also regarded as this hair
Bright protection domain.
Claims (7)
1. a kind of aid decision-making method based on big data, it is characterized in that, selection data dictionary is carried out according to decision requirements, utilize
Keyword mechanism carries out setting up basic model storehouse, the data in basic model storehouse is analyzed according to decision requirements, is shown, right
Data results carry out data mining and obtain decision data.
2. a kind of aid decision-making method based on big data according to claim 1, it is characterized in that, big data should be based on
Aid decision-making method is comprised the following steps：
Step one：Propose decision requirements：User proposes the decision-making needs to be carried out data mining and displaying, and the decision-making needs
At least include involved service point and excavation purpose；
Step 2：Choose data dictionary：Carry out choosing corresponding data dictionary according to the decision requirements that user proposes；
Step 3：Set up keyword mechanism：In data retrieval, according to retrieval keyword search key word library, if with pass
Keyword match in key character library then calls the retrieval result of the keyword in key word library, if the keyword and key word library
In keyword mismatch, from choose data dictionary in retrieved, and will from data dictionary retrieve data content protect
It is stored in key word library；
Step 4：Set up basic model storehouse：Keyword, decision requirements and data dictionary are associated by foundation according to retrieval result
Basic model, and the basic model of foundation is saved in plinth model library；
Step 5：Carry out data analysis, displaying：Basic model storehouse is called according to decision requirements and relevant rudimentary model is divided
Data results are shown by analysis with patterned form；
Step 6：Carry out data mining：Data mining is carried out to data results, data root is found, decision data is formed.
3. a kind of aid decision-making method based on big data according to claim 1 and 2, it is characterized in that, the data word
Allusion quotation includes that knowledge base, policies and regulations storehouse, System Documents storehouse, job instruction, basic database, production business library, exchange are shared
Storehouse, Analysis of Policy Making storehouse.
4. a kind of aid decision-making method based on big data according to claim 3, it is characterized in that,
The knowledge base include problem base, hidden danger storehouse and data bank, for quick autonomous learning, search problem, solve problem；
The basic database is used to deposit all kinds of basic dictionary datas and basic agricultural object data, agriculture business object master
To include cultivated land resource, fertilization compositions based on earth measurement, agricultural product price market, agricultural pest, agriculture feelings and production management, agriculture Internet of Things
Net, confirmation of land right；
The production business library is used to deposit the business datum that all kinds of operation system routine work operations are produced；
It is described exchange SB be used to realizing and agriculture the superior and the subordinate, between external unit and the Ministry of Agriculture data share exchange need
Ask, be provided with exchange sharing data area, the agriculture business datum for exchanging having shared demand is stored and managed, agricultural sector
Shared data bank with production business library logical separation, should exchange the data source of SB in production business library；
The Analysis of Policy Making storehouse is used to deposit the related all kinds of operational datas of agriculture business.To realize agricultural data in-depth analysis
And aid decision, based on producing business library carrying out data slightly collects, and forms Analysis of Policy Making storehouse, and combine agricultural data
Feature and Analysis of Policy Making need to build subject analysis model.
5. a kind of aid decision-making method based on big data according to claim 4, it is characterized in that, the basic model bag
Early-warning Model containing soil moisture content, pestforecasting Early-warning Model, envirment factor model, agricultural extension model.
6. a kind of aid decision-making method based on big data according to claim 2, it is characterized in that, in step 5, adjust
If not meeting the basic model of decision requirements during with basic model storehouse in basic model storehouse, new basic model is set up simultaneously
It is saved in basic model storehouse.
7. a kind of aid decision-making method based on big data according to claim 2, it is characterized in that, to data results
The patterned form being shown includes pie chart, block diagram, curve map and list.
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| CN110458383A (en) * | 2019-06-24 | 2019-11-15 | 平安国际智慧城市科技股份有限公司 | Demand handles implementation method, device and the computer equipment of serviceization, storage medium |
| CN110458383B (en) * | 2019-06-24 | 2020-08-18 | 平安国际智慧城市科技股份有限公司 | Method and device for realizing demand processing servitization, computer equipment and storage medium |
| CN110458442A (en) * | 2019-08-07 | 2019-11-15 | 成都九鼎瑞信科技股份有限公司 | Water utilities system cost analysis method |
| CN110502553A (en) * | 2019-08-22 | 2019-11-26 | 武汉东湖大数据交易中心股份有限公司 | A kind of aid decision-making method based on big data |
| CN111460217A (en) * | 2020-03-31 | 2020-07-28 | 苏州科达科技股份有限公司 | Video retrieval system and method for operating a video retrieval system |
| CN112380251A (en) * | 2020-11-17 | 2021-02-19 | 北京航空航天大学 | Multi-decision and data retrieval method based on data space |
| CN113297196A (en) * | 2021-07-28 | 2021-08-24 | 深圳市爱云信息科技有限公司 | Intelligent agricultural AIOT distributed big data storage platform |
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