CN104346698B - Based on the analysis of the food and drink member big data of cloud computing and data mining and checking system - Google Patents
Based on the analysis of the food and drink member big data of cloud computing and data mining and checking system Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The present invention relates to a kind of based on the analysis of the food and drink member big data of cloud computing and data mining and checking system,It includes realizing the operating service terminal system of two-way communication respectively,At least one merchant tenninal system,Member terminal system,High in the clouds data center and data digging system,Wherein operating service terminal system,Merchant tenninal system and member terminal system typing food and drink member run related initial data and interacted with high in the clouds data center information,Initial data is after high in the clouds data center pre-processes,It is sent to data digging system and carries out analysis calculating,Export rule model set and give high in the clouds data center,And the merchant tenninal system specified is sent to via high in the clouds data center,Rule model, which is integrated into be corrected by user in merchant tenninal system, forms the rule model with time attribute,And apply and formed using result data after correcting,Rule model and application result data with time attribute store data center beyond the clouds as knowledge base.
Description
Technical field
The present invention relates to food management system, more particularly to a kind of big number of food and drink member based on cloud computing and data mining
According to analysis and checking system.
Background technology
In recent years, the food and beverage enterprise of some scales has been commonly used CRM software (CRM) to realize meal
The informationization of Room member system management.It common are what the crm system, internet food and drink platform service business that POS carries provided
The CRM software products of crm system and stand-alone development.These crm systems generally include member management, membership promotion, member disappear
Take, several modules such as statistical report form, wherein, member management module is used for the increase of membership information, deletes modification and inquiry；Member
Marketing module is used to, to food and beverage enterprise member, differential marketing is carried out using different channels；Member is consumed for recording meeting
Shops's transaction data of member；Statistical report form is used for the related data statistical analysis of member, member's member card and membership promotion.CRM
System contributes to food and beverage enterprise to carry out the marketing of system to having member by oneself, improves member's loyalty and constantly receives new member；
Fed back by the data interaction of member terminal system and crm system to collect products ＆ services, so as to constantly improve product kimonos
Business.
But for above-described traditional CRM softwares, the statistical data analysis that can be provided is only limitted to member's system sheet
Body, and simply simple operation Jing Guo system draws the collecting of branch data, screened and simple comparative analysis.POS is certainly
Although member data and food and beverage enterprise's entirety operation data can be made simple contrast by the CRM softwares of band, it is soft to lack professional CRM
The analysis method of part.And in today of catering industry competition, food and beverage enterprise is more dependent on the operation by intelligence
Member data and become based on this intelligent data operation to obtain accurately Management plan, the implementation effect of high quality and development
The prediction of gesture, constantly consolidate and expand the market of oneself.Realize traditional data operation to intelligent data operation across mainly
Obstacle be：
1st, domestic catering industry membership promotion is still in primary developing stage at present, and the mutual existence information wall of enterprise
Build, either Dan Dian, single brand, single industry situation or the whole industry, can not all provide the weighing apparatus that member runs development and implementation effect
Amount standard, causing food and beverage enterprise to do membership promotion can only blindly be carried out, and even be caused so as to inevitably influence efficiency of operation
Loss；
2nd, lack intelligent, accurately member's operation data forecast model relatively, cause food and beverage enterprise to adjust in advance
Whole member's Management plan, the limited operation resource in allotment dining room；
3rd, due to the confidentiality and own operations system of food and beverage enterprise's entirety operation data and mutually dividing for professional crm system
From, the effect for causing trade company can not actually be played in food and beverage enterprise integrally runs by the clear and definite member's operation of data analysis, from
And it can not accurately weigh input-output ratio.
The content of the invention
Analyze and examine based on the food and drink member big data of cloud computing and data mining it is an object of the invention to provide a kind of
System, its can realize provide industry member's operation management criterion, efficiently and accurately provide analysis report and to provide trend pre-
Survey, help enterprise to pinpoint the problems, adjust Management plan and make important decision.
The present invention's is a kind of based on the analysis of the food and drink member big data of cloud computing and data mining and checking system, including fortune
Service terminal system, merchant tenninal system, member terminal system, high in the clouds data center and data digging system are sought, wherein described
Operating service terminal system, merchant tenninal system and member terminal system typing food and drink member run related initial data and with
High in the clouds data center information interaction, initial data are sent to the data mining system after the high in the clouds data center pre-processes
System carries out analysis calculating, exports rule model set and gives high in the clouds data center, and is sent to what is specified via high in the clouds data center
Merchant tenninal system, rule model, which is integrated into be corrected by user in the merchant tenninal system, forms the rule with time attribute
Model, and apply and formed using result data after correcting, rule model and application result data conduct with time attribute
Knowledge base stores data center beyond the clouds.
Further, the merchant tenninal system includes merchant store fronts POS terminal system, CRM merchant business processing subsystem
System, CRM Report Subsystems and CRM data forecasting terminal system, wherein the meeting of merchant store fronts POS terminal system processing shops
Member, member card and transaction related service, and caused initial data is sent to the high in the clouds data center；The CRM business
Family service process subsystem management member data and processing member, member card, transaction and financial related service, and by caused by
Initial data is sent to high in the clouds data center；The CRM Report Subsystems are used for the application of the rule model with time attribute
And formed using result data, and be sent to by the rule model with time attribute and using result data in the data of high in the clouds
The heart；The rule model and application result data of the CRM data forecasting terminal system timing belt having time attribute simultaneously predict trade company
Member's operation data.
Further, the member terminal system is used for presentation, member's online transaction and the evaluation of member's related data, and
Caused initial data is sent to high in the clouds data center.
Further, the rule model set includes nontransaction rule model and trading rules model, the high in the clouds number
Include CRM high in the clouds data center and high in the clouds trade data mart according to center, wherein CRM high in the clouds data center collection and synchronization
Operating service terminal system, merchant tenninal system, nontransaction data caused by member terminal system, and to the nontransaction data
After the related logical process of carry out business, there is provided carry out analysis calculating to the data digging system, return to nontransaction regular mould
Type is to CRM high in the clouds data center；The high in the clouds trade data mart collection and synchronous operating service terminal system, merchant tenninal system
System, the transaction data of member terminal system, and after the logical process related to transaction data progress business, it is sent to data digging
Pick system carries out analysis calculating, returns to trading rules model to CRM high in the clouds data center.
Further, the data digging system includes：1) it is used for the number for gathering the data resource used for data mining
According to warehouse；2) it is used for the data mining kernel for learning, analyzing and exporting rule model.
Further, the data mining kernel includes：1) automatic clustering is carried out to it according to trade company's attributive character to divide
Class device；2) it is used to learning and exporting the coefficient analysis module for influenceing coefficient rule model；3) it is used to learn and outgoing traffic index
The indicator analysis module of rule model.
Further, the grader uses following algorithm：
S1：The trade company's characteristic attribute set defined from data warehouse collection operating service terminal system；
S2：All characteristic attributes are done into permutation and combination, draw classification 1, classification 2 ... classification n, corresponding one group of spy per component class
Levy attribute set；
S3：When collecting a Ge Xin trade companies --- during trade company X information, the characteristic attribute set of all classification is traveled through, if
Meet condition：Trade company's X characteristic attributes set=classification n characteristic attribute set, then trade company X is referred to classification n；
S4：When meeting a calculating cycle, first three step is repeated.
Further, the algorithm of the influence coefficient of the coefficient analysis module is as follows：
S1：Defined from data warehouse acquisition terminal system, determine to influence the operational indicator item of coefficient and its examination cycle；
S2：Calculate the average value in each examination cycle；
S3：Calculate the influence coefficient in each cycle；
S4：When meeting a calculating cycle, first three step is repeated.
Further, the operational indicator rule-based algorithm of the indicator analysis module is as follows：
S1：Each trade company in upper 1 year each examination cycle is gathered from data warehouse actually accomplishes value；
S2：Calculate industry service guidance target goals value：The row of the classification in the corresponding examination cycle in this year of operational indicator
Industry instructs objectives of examination value；
S3：Calculate operational indicator objectives of examination value default value：
Value >=the industry that actually accomplishes such as trade company's upper examination cycle instructs desired value, then
Output trade company it is next examination the cycle objectives of examination value default value be：The reality in trade company's upper examination cycle is complete
Into the influence coefficient * 105% of the influence coefficient * this months of value ÷ last month；
The value ＜ industries that actually accomplish such as trade company's upper examination cycle instruct desired value, then
Output trade company it is next examination the cycle operational indicator objectives of examination value default value be：Trade company's upper examination cycle
The influence coefficient * this months for actually accomplishing value ÷ last month influence coefficient * 110%.
Further, the rule model includes：1) coefficient is influenceed；2) industry service guidance operation index desired value；3)
Operational indicator objectives of examination value default value, the knowledge base include：1) whole industry with time attribute and each Merchant Category
Influence coefficient；2) whole industry with time attribute and the service guidance operation index desired value of each Merchant Category；3) band is sometimes
Between the whole industry of attribute and the revised operational indicator objectives of examination value of each Merchant Category；4) whole industry of time attribute is carried
With each Merchant Category using result data.
By such scheme, the present invention at least has advantages below：Being realized by data digging system carries out lasting, follows
The analyzing and processing of ring, output rule model set, and band having time category is formed by high in the clouds data center and merchant tenninal system
The rule model of property and using result data, so as to provide industry member's operation management criterion, efficiently and accurately provides point
Analysis report and offer trend prediction, help enterprise to pinpoint the problems, and adjust Management plan and make important decision.
Described above is only the general introduction of technical solutions of the utility model, in order to better understand the technology hand of the present invention
Section, and can be practiced according to the content of specification, with presently preferred embodiments of the present invention and coordinate accompanying drawing to describe in detail such as below
Afterwards.
Brief description of the drawings
Fig. 1 is that structure of the present invention based on the analysis of the food and drink member big data of cloud computing and data mining and checking system is shown
It is intended to；
Fig. 2 is the fundamental diagram of the present invention.
Embodiment
With reference to the accompanying drawings and examples, the embodiment of the present invention is described in further detail.Implement below
Example is used to illustrate the present invention, but is not limited to the scope of the present invention.
With Internet technology, cloud computing and the continuous development of data storage service, data analysis technique also develops more
Add accurate and comprehensive, it is possible to achieve instead of the increasing experience and rule summarized by manpower.Data mining (Data
Mining) it is a kind of method in knowledge discovery in database, generally refers to be hidden in by algorithm search from substantial amounts of data
The wherein process of information.Data analysis is generally relevant with computer science, and by statistics, Data Environments, information retrieval,
All multi-methods such as machine learning, expert system (rely on the past rule of thumb) and pattern-recognition realize above-mentioned target.Data
Analysis is also used as a kind of decision support processes, and it is based primarily upon artificial intelligence, machine learning, pattern-recognition, statistics, number
According to storehouse, visualization technique etc., the data of enterprise are analyzed increasingly automatedly, make the reasoning of inductive, are therefrom excavated potential
Pattern, aid decision making person adjust market strategy, reduce risks, make correct decision-making.
Data analysis is to find the technology of its rule from mass data by analyzing each data, mainly has data accurate
Standby, rule is found and rule represents 3 steps.Data prepare to be to choose required data from the data source of correlation and be integrated into
Data set for data analysis；It is to be created the rule contained by data set with some way that rule, which is found,；Rule represents
The rule found out is showed (as visualized) in a manner of user understands as far as possible.
Referring to Fig. 1 and Fig. 2, the food and drink member based on cloud computing and data mining described in a preferred embodiment of the present invention is big
Data analysis and checking system, including operating service terminal system 1, merchant tenninal system, member terminal system 2, high in the clouds data
Center 3 and data digging system 4.The operating service terminal system 1, merchant tenninal system and the typing of member terminal system 2 meal
Drink member run related initial data and with the information exchange of high in the clouds data center 3, initial data is through the high in the clouds data center 3
Cleaned, computing, the pretreatment such as screen, collect after, be sent to the data digging system 4 and carry out analysis calculating, output rule
Then model set is to high in the clouds data center 3, and the merchant tenninal system specified, regular mould are sent to via high in the clouds data center 3
Type, which is integrated into be corrected by user in the merchant tenninal system, forms the rule model with time attribute, and is applied simultaneously after correcting
Result data is applied in formation, and rule model and application result data with time attribute store data beyond the clouds as knowledge base
Center 3, by the knowledge base so as to being further used for the excavation of big data.The rule model set includes nontransaction regular mould
Type and trading rules model.The application of the rule model, it is to be combined it with catering industry professional knowledge, output has enough
Food and beverage enterprise's member's traffic-operating period visualization data analysis report of breadth and depth, is intuitively presented on merchant tenninal system circle
On face, food and beverage enterprise and whole catering industry is helped to carry out member's operation.The application of the rule model comprising but be not limited only to：
1) the catering industry whole industry, different industry situations, different enterprises, the member of different members operation developing stage run development
Situation analysis and prediction；
2) group of food and beverage enterprise and each branch company, the member of shops run wire examination method and instructed, performance assessment criteria desired value
Intelligence setting and artificial correction；
3) food and beverage enterprise member runs the visualization presentation of monthly magazine；
4) food and beverage enterprise member runs the informationization of quantizing examination, intelligent solution.
The rule model includes：1) coefficient is influenceed；2) industry service guidance operation index desired value；3) operational indicator is examined
Core desired value default value.
The knowledge base includes：1) the influence coefficient of the whole industry with time attribute and each Merchant Category；2) band is sometimes
Between the whole industry of attribute and the service guidance operation index desired value of each Merchant Category；3) whole industry with time attribute and each
The revised operational indicator objectives of examination value of Merchant Category；4) application of the whole industry with time attribute and each Merchant Category
Result data.
The operating service terminal management system is used for the management of trade company's Back ground Information, the setting of business rule and operation clothes
The trade company at business end authorizes business processing, and caused initial data is sent into high in the clouds data center 3.The merchant tenninal system
System includes merchant store fronts POS terminal system 51, CRM merchant business processing subsystem 52, CRM Report Subsystems 53 and CRM data
Forecasting terminal system 54.The merchant store fronts POS terminal system 51 handles shops member, member card and transaction related service, and
Caused initial data is sent to the high in the clouds data center 3.The CRM merchant business processing subsystem 52 manages member
Data and processing member, member card, transaction and financial related service, and caused initial data is sent in the data of high in the clouds
The heart 3.The CRM Report Subsystems 53 are used for the application of the rule model with time attribute and formed using result data, and
High in the clouds data center 3 is sent to by the rule model with time attribute and using result data.The CRM data predicts terminal
The rule model and application result data of the timing belt having time attribute of system 54 simultaneously predict trade company's member's operation data.The member
Terminal system 2 is used for presentation, member's online transaction and the evaluation of member's related data, and caused initial data is sent to
High in the clouds data center 3.
The data mining kernel will be sent out through analyzing the operational indicator default value being calculated via CRM high in the clouds data center
CRM Report Subsystems 53 are given, is modified and applied according to itself member operation current situation by trade company.The amendment is
Refer to, trade company can be carried out according to itself specific traffic-operating period to objectives of examination value and operation data (begining a theatrical performance number and turnover etc.)
Artificial correction, more to meet the actual examination needs of trade company.
The high in the clouds data center 3 includes CRM high in the clouds data center 31 and high in the clouds trade data mart 32, wherein described
CRM high in the clouds data center 31 gather and synchronous operating service terminal system 1, merchant tenninal system, member terminal system 2 produced by
Nontransaction data, and after carrying out the related logical process of business to the nontransaction data, there is provided to the data digging system 4
Analysis calculating is carried out, returns to nontransaction rule model to CRM high in the clouds data center 31.It is the high in the clouds CRM data central data, same
The data for walking and doing the processing of business interrelated logic include：1) trade company's essential information, including trade company's standard feature attribute can be described
Information；2) trade company CRM related services processing rule, including for statistical analysis and the variable parameter of anticipation trend；3) trade company,
Member, member card, finance and transaction business processing initial data and the member's mouth that operating service and member terminal system 2 are sent
Landmark data；4) the overall operation data inputted from third party's synchronization or merchant tenninal system；5) data digging system 4 is by study
With the rule model set for calculating return.The high in the clouds trade data mart 32 gathers and synchronous operating service terminal system, business
The transaction data of family terminal system, member terminal system 2, and after the logical process related to transaction data progress business, hair
Give data digging system 4 and carry out analysis calculating, return to trading rules model to CRM high in the clouds data center 31.
The data digging system 4 includes：1) it is used for the data warehouse 41 for gathering the data resource used for data mining；
2) it is used for the data mining kernel 42 for learning, analyzing and exporting rule model.Initial data is located in advance through the high in the clouds data center
The data warehouse 41 of the data digging system is sent to after reason, is available in the data mining of the data digging system 4
Core 42, analysis calculating is carried out by certain mining algorithm, export rule model set to data warehouse 41.Data warehouse 41 will
Rule model set is sent to the merchant tenninal system specified via high in the clouds data center 3.The data mining kernel 42 includes：
1) grader of automatic clustering is carried out to it according to trade company's attributive character；2) it is used to learn and export to influence coefficient rule model
Coefficient analysis module；3) it is used to learn the indicator analysis module with outgoing traffic indicator rule model.
The grader uses following algorithm：
S1：Trade company's characteristic attribute set of the definition of operating service terminal system 1 is gathered from data warehouse 41；
S2：All characteristic attributes are done into permutation and combination, draw classification 1, classification 2 ... classification n, corresponding one group of spy per component class
Levy attribute set --- set 1, set 2 ... set n；
S3：When collecting a Ge Xin trade companies --- during trade company X information, the characteristic attribute set of all classification is traveled through, if
Meet condition：Trade company's X characteristic attributes set=classification n characteristic attribute set, then trade company X is referred to classification n；
S4：When meeting a calculating cycle, first three step is repeated.
Example：Trade company's attribute has：Begin a theatrical performance industry situation, the moon number, per capita, permutation and combination produce 9 Merchant Categories.
Because the business circumstance of catering industry can be influenceed by time factors such as dull and rush season, festivals or holidays, thus calculate or
Predict during operational indicator, it is necessary to introduce the influence coefficient in different examination cycles.The calculation of the influence coefficient of the coefficient analysis module
Method is as follows：
S1：Defined from the acquisition terminal system of data warehouse 41, determine to influence the operational indicator item of coefficient and its examination cycle,
It is assumed that operational indicator item is A, B, the value that actually accomplishes in each examination cycle of certain each operational indicator item of classifying is：
| Operational indicator item | Examine the cycle 1 | Examine the cycle 2 | … | Examine cycle n |
| A | A1X | A2X | … | AnX |
| B | B1X | B2X | … | BnX |
S2：Calculate the average value in each examination cycle<AX>With<BX>:
<AX>=(A1X+A2X+ ...+AnX) ÷ n,
<BX>=(B1X+B2X+ ...+BnX) ÷ n；
S3：Calculate the influence coefficient A fn and Bfn in each cycle：
Afn=ANX ÷<AX>,
Bfn=BNX ÷<BX>；
S4：When meeting a calculating cycle, first three step is repeated.
Example：Determine influence coefficient operational indicator item for the turnover (A) and begin a theatrical performance number (B), examine the cycle be
One month, i.e. January to December.
The monthly average turnover of upper one year is<AX>=200,000 yuan,
The monthly average of upper one year begins a theatrical performance number：3,000,
The turnover on January, upper 1 is A1X=180,000 yuan,
The number of begining a theatrical performance on January, upper 1 is B1X=2,500 yuan,
Then：
The turnover influence coefficient A f1=180,000 ÷ 200,000=0.9 in January
The number of begining a theatrical performance in January influences coefficient B f1=2,500 ÷ 3,000=0.83
The operational indicator rule-based algorithm of the indicator analysis module is as follows：
S1：Each trade company in upper one year in each examination cycle was gathered from data warehouse 41 actually accomplishes value, it is assumed that business
Index item is：C, D, calculate the described each operational indicator of each Merchant Category actually accomplishes average value：
S2：Calculate industry service guidance target goals value CY, DY：
The classification n in the corresponding examination cycle in operational indicator C this year industry instructs objectives of examination value：
CY=<Classify nCX>,
The classification n in the corresponding examination cycle in operational indicator D this year industry instructs objectives of examination value：
DY=<Classify nDX>；
S3：Calculate objectives of examination value default value：
It is assumed that next examination cycle is cycle N, the operational indicator project that need to be examined is C, and operational indicator C receives influence
Coefficient Af influence,
1) value >=industry that actually accomplishes such as trade company's upper examination cycle instructs desired value, then
Output trade company it is next examination cycle C objectives of examination value default value be：The reality in trade company's upper examination cycle C
The influence coefficient A fN*105% of influence coefficient A f (N-1) the * this months of completion value ÷ last month；
2) the value ＜ industries that actually accomplish such as trade company's upper examination cycle C instruct desired value CY, then
Output trade company it is next examination the cycle operational indicator objectives of examination value default value be：Trade company's upper examination cycle
The influence coefficient A fN*110% of C influence coefficient A f (N-1) the * this months for actually accomplishing value ÷ last month.
Example：To sell card amount (C) and Stored Value is supplemented with money (D), the shops for n last Januaries of classifying is averaged the operational indicator for needing to examine
Card amount is sold as 600, the average Stored Value of shops is supplemented with money as 50,000 yuan, then：
The industry that classification n sells card amount January in this year instructs the desired value to be：CY=<Classify nCX>=600
The classification n industries that Stored Value is supplemented with money January in this year instruct the desired value to be：DY=<Classify NnDX>=50,000 yuan
1) belong to classification n shops's first January sells card amount as 800, instructs desired value 600 to open more than industry, sells card amount
Influenceed by number is begined a theatrical performance, the classification n1 months begin a theatrical performance number influence coefficients be 0.83,2 months be 0.9, then shops's first 2 months sells card amount mesh
Scale value default value is：
800 ÷ 0.83*0.9*105%=826
2) Stored Value for belonging to classification n shops's first January is supplemented with money as 40,000 yuan, and desired value 50,000 is instructed less than industry
Member, Stored Value is supplemented with money to be influenceed by the turnover, the turnovers of the classification n1 months influence coefficient be 0.9,2 months be 1.2, then shops's first 2 months
Stored Value supplement desired value default value with money and be：
40,000 ÷ 0.9*1.2*110%=58,667 members
In summary, it is of the invention to be led to based on the analysis of the food and drink member big data of cloud computing and data mining and checking system
Cross the realization of data digging system 4 and carry out lasting, the analyzing and processing of circulation, output rule model set, and pass through high in the clouds data
Center 3 and the formation of merchant tenninal system carry the rule model of time attribute and using result data, so as to provide industry member
Operation management criterion, efficiently and accurately provide analysis report and provide trend prediction, help enterprise pinpoint the problems, adjustment fortune
Battalion's scheme and make important decision.
Described above is only the preferred embodiment of the present invention, is not intended to limit the invention, it is noted that for this skill
For the those of ordinary skill in art field, without departing from the technical principles of the invention, can also make it is some improvement and
Modification, these improvement and modification also should be regarded as protection scope of the present invention.
Claims (1)
- It is 1. a kind of based on the analysis of the food and drink member big data of cloud computing and data mining and checking system, it is characterised in that：Including Operating service terminal system, merchant tenninal system, member terminal system, high in the clouds data center and data digging system, wherein institute State operating service terminal system, merchant tenninal the system initial data related to member terminal system typing food and drink member's operation and Interacted with high in the clouds data center information, initial data is sent to the data mining after the high in the clouds data center pre-processes System carries out analysis calculating, exports rule model set and gives high in the clouds data center, and is sent to via high in the clouds data center specified Merchant tenninal system, rule model, which is integrated into be corrected by user in the merchant tenninal system, forms the rule with time attribute Then model, and apply and formed using result data after correcting, rule model and application result data with time attribute are made Data center beyond the clouds is stored for knowledge base；The merchant tenninal system includes merchant store fronts POS terminal system, CRM merchant business processing subsystem, CRM form subsystems System and CRM data forecasting terminal system, wherein merchant store fronts POS terminal system processing shops member, member card and transaction Related service, and caused initial data is sent to the high in the clouds data center；The CRM merchant business processing subsystem Member data and processing member, member card, transaction and financial related service are managed, and caused initial data is sent to cloud End data center；The CRM Report Subsystems are used for the application of the rule model with time attribute and formed using number of results According to, and it is sent to high in the clouds data center by the rule model with time attribute and using result data；The CRM data prediction The rule model and application result data of terminal system timing belt having time attribute simultaneously predict trade company's member's operation data；The member terminal system is used for presentation, member's online transaction and the evaluation of member's related data, and by caused original Beginning data are sent to high in the clouds data center；The rule model set includes nontransaction rule model and trading rules model, and the high in the clouds data center includes CRM High in the clouds data center and high in the clouds trade data mart, wherein CRM high in the clouds data center collection and synchronous operating service terminal System, merchant tenninal system, nontransaction data caused by member terminal system, and it is related to carry out business to the nontransaction data Logical process after, there is provided carry out analysis calculating to the data digging system, return to nontransaction rule model to CRM high in the clouds number According to center；The high in the clouds trade data mart collection and synchronous operating service terminal system, merchant tenninal system, member terminal system The transaction data of system, and after the logical process related to transaction data progress business, be sent to data digging system and divided Analysis calculates, and returns to trading rules model to CRM high in the clouds data center；The data digging system includes：1) it is used for the data warehouse for gathering the data resource used for data mining；2) it is used for The data mining kernel of study, analysis and output rule model；The data mining kernel includes：1) grader of automatic clustering is carried out to it according to trade company's attributive character；2) it is used to learn Practise and export the coefficient analysis module for influenceing coefficient rule model；3) it is used to learn the index with outgoing traffic indicator rule model Analysis module；The grader uses following algorithm：S1：The trade company's characteristic attribute set defined from data warehouse collection operating service terminal system；S2：All characteristic attributes are done into permutation and combination, draw classification 1, classification 2 ... classification n, corresponding one group of feature category per component class Property set；S3：When collecting a Ge Xin trade companies --- during trade company X information, the characteristic attribute set of all classification is traveled through, if meeting Condition：Trade company's X characteristic attributes set=classification n characteristic attribute set, then trade company X is referred to classification n；S4：When meeting a calculating cycle, first three step is repeated；The algorithm of the influence coefficient of the coefficient analysis module is as follows：S1：Defined from data warehouse acquisition terminal system, determine to influence the operational indicator item of coefficient and its examination cycle；S2：Calculate the average value in each examination cycle；S3：Calculate the influence coefficient in each cycle；S4：When meeting a calculating cycle, first three step is repeated；The operational indicator rule-based algorithm of the indicator analysis module is as follows：S1：Each trade company in upper 1 year each examination cycle is gathered from data warehouse actually accomplishes value；S2：Calculate industry service guidance target goals value：The industry of the classification in the corresponding examination cycle in this year of operational indicator refers to Lead objectives of examination value；S3：Calculate operational indicator objectives of examination value default value：Value >=the industry that actually accomplishes such as trade company's upper examination cycle instructs desired value, thenOutput trade company it is next examination the cycle objectives of examination value default value be：Trade company's upper examination cycle actually accomplishes value The influence coefficient * 105% of the influence coefficient * this months of ÷ last months；The value ＜ industries that actually accomplish such as trade company's upper examination cycle instruct desired value, thenOutput trade company it is next examination the cycle operational indicator objectives of examination value default value be：The reality in trade company's upper examination cycle The influence coefficient * 110% of the influence coefficient * this months of border completion value ÷ last month；The rule model includes：1) coefficient is influenceed；2) industry service guidance operation index desired value；3) operational indicator examination mesh Scale value default value, the knowledge base include：1) the influence coefficient of the whole industry with time attribute and each Merchant Category；2) carry The service guidance operation index desired value of the whole industry of time attribute and each Merchant Category；3) with time attribute the whole industry and The revised operational indicator objectives of examination value of each Merchant Category；4) whole industry of time attribute and answering for each Merchant Category are carried Use result data.
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| CN105931055A (en) * | 2016-04-05 | 2016-09-07 | 扬州大学 | Service provider feature modeling method for crowdsourcing platform |
| CN105897925B (en) * | 2016-05-31 | 2018-11-23 | 湖南一二三智能科技有限公司 | A kind of mobile remote power monitoring system and monitoring method based on 4G network |
| CN107357872A (en) * | 2017-07-04 | 2017-11-17 | 深圳齐心集团股份有限公司 | A kind of stationery sale big data based on cloud computing is excavated and analysis system |
| WO2019006638A1 (en) * | 2017-07-04 | 2019-01-10 | 深圳齐心集团股份有限公司 | Cloud computing-based stationery sales big data mining and analysis system |
| CN107481119A (en) * | 2017-08-21 | 2017-12-15 | 贵州西部生态链电子商务有限公司 | A kind of cloud food and drink platform and analysis method based on big data signature analysis |
| CN109544246A (en) * | 2018-11-29 | 2019-03-29 | 成都油管家科技有限公司 | A kind of system analyzed for gas station's member management and member data |
| CN111882226B (en) * | 2020-07-31 | 2024-01-05 | 贵州东冠科技有限公司 | Scoring and checking system based on specific place management |
| CN116431616B (en) * | 2023-06-13 | 2023-09-01 | 深圳市诚识科技有限公司 | Big data model management system and method based on cloud computing |
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