CN106202218A - A kind of data processing method and data handling system - Google Patents
A kind of data processing method and data handling system Download PDFInfo
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- CN106202218A CN106202218A CN201610490608.6A CN201610490608A CN106202218A CN 106202218 A CN106202218 A CN 106202218A CN 201610490608 A CN201610490608 A CN 201610490608A CN 106202218 A CN106202218 A CN 106202218A
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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
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
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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
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/285—Clustering or classification
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- G—PHYSICS
- 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
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
Abstract
The embodiment of the present invention provides a kind of data processing method and data handling system, for solving the technical problem that in prior art, the accuracy of the data analysis of pin intelligent home device user is relatively low.The method includes: described Data Integration processing subsystem obtains the customer data relevant with M client and product data from described internal database and to the external data base that described Data Integration subsystem connects, described customer data and described product data are carried out integrating classification by described Data Integration processing subsystem, obtaining at least four big class data, described at least four big class data include client's base attribute class data, consumer product interest class data, customer event class data and social network relationships data；Described user profile processing subsystem, based on described at least four big class data, determines at least one class client properties that described M client is corresponding.
Description
Technical field
The present invention relates to electronic technology field, particularly to a kind of data processing method and data handling system.
Background technology
Along with the development of science and technology, increasing intelligent home device has incorporated daily life, for
People provide comfortable life style easily.And intelligent home device manufacturer typically requires record product and is producing and selling and selling
The data in each stage such as rear, it is simple to user or research worker later stage can be by obtaining corresponding conclusion to the analysis of data.
At present, intelligent home device manufacturer, when understanding customer type, is generally only when user buys commodity, carries out letter
Single understanding, such as age bracket, sex, occupation etc., therefore the data obtained compared with based on, limited, but, in actual applications, example
As when planning product function, it is suitable for the factor needing emphasis to consider during user is still product programming, therefore,
Analysis to user-dependent data is particularly important.
Summary of the invention
The embodiment of the present invention provides a kind of data processing method and data handling system, is used for solving pin intelligence in prior art
Can the relatively low technical problem of the accuracy of data analysis of home equipment user.
On the one hand, the application provides a kind of data processing method, is applied in a data handling system, and described data process
System includes Data Integration processing subsystem, the internal database being connected with described Data Integration processing subsystem, and with described
The user profile processing subsystem that Data Integration processing subsystem connects, the method includes:
Described Data Integration processing subsystem is from described internal database and being connected with described Data Integration subsystem
Obtaining the customer data relevant to M client and product data in portion data base, M is positive integer；
Described customer data and described product data are carried out integrating classification by described Data Integration processing subsystem, it is thus achieved that extremely
Few four big class data, described at least four big class data include client's base attribute class data, consumer product interest class data, client
Event class data and social network relationships data；
Described user profile processing subsystem, based on described at least four big class data, determines that described M client is corresponding extremely
A few class client properties.
On the other hand, the application provides a kind of data handling system, including:
At least one data base, including internal database and external data base, for the client that storage is relevant to M client
Data and product data, M is positive integer；
Described Data Integration processing subsystem, obtains described client from described internal database and described external data base
Data and described product data, and carry out described customer data and described product data integrating classification, it is thus achieved that at least four big classes
Data；Wherein, described at least four big class data include client's base attribute class data, consumer product interest class data, client's thing
Part class data and social network relationships data；
Described user profile processing subsystem, based on described at least four big class data, determines that described M client is corresponding extremely
A few class client properties.
The one or more technical schemes provided in the embodiment of the present application, at least have the following technical effect that or advantage:
In the technical scheme of the application, by Data Integration processing subsystem from internal database and with Data Integration subsystem
The external data base that system connects obtains the customer data relevant to M client and product data, and based on customer data and product
Product data carry out integrating classification, it is thus achieved that include client's base attribute class data, consumer product interest class data, customer event class number
According at least four big class data, then by user profile processing subsystem, at least four big class data are processed, it may be determined that M
At least one class client properties that client is corresponding.Therefore may determine that intelligence by customer data and the product data that M client is correlated with
The user type of energy home equipment such that it is able to corresponding product design etc. is set according to each user type, to improve product
Practicality.
The application the most also has the following technical effect that or advantage:
Further, in the embodiment of the present application, the Data Source of data handling system can be from the daily life of M client
In obtained by diversified source and channel, the data therefore gathered have variation, by integrate classification process
Make data be easy to management, improve the technique effect of data management effect.
Further, the technical scheme in the application can describe class data, client's consumption feature class based on client interests
Data and client, to product evaluation class data, analyze and obtain the acquisition of accurate beneficially manufacturer for the pass improving product
Key data, so that data handling system also has the technique effect improving analysis result accuracy.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of data handling system in the embodiment of the present invention；
Fig. 2 is the flow chart of data processing method in the embodiment of the present invention.
Detailed description of the invention
The embodiment of the present invention provides a kind of data processing method and data handling system, is used for solving pin intelligence in prior art
Can the relatively low technical problem of the accuracy of data analysis of home equipment user.
Technical scheme in the embodiment of the present application is for solving above-mentioned technical problem, and general thought is as follows:
In the technical scheme of the application, by Data Integration processing subsystem from internal database and with Data Integration subsystem
The external data base that system connects obtains the customer data relevant to M client and product data, and based on customer data and product
Product data carry out integrating classification, it is thus achieved that include client's base attribute class data, consumer product interest class data, customer event class number
According at least four big class data, then by user profile processing subsystem, at least four big class data are processed, it may be determined that M
At least one class client properties that client is corresponding.Therefore may determine that intelligence by customer data and the product data that M client is correlated with
The user type of energy home equipment such that it is able to corresponding product design etc. is set according to each user type, to improve product
Practicality.
In the embodiment of the present invention, data handling system can include that internal database, external data base, Data Integration process
Subsystem and user profile processing subsystem, its corresponding functional schematic is as shown in Figure 1.
In the embodiment of the present invention, internal database may refer to what intelligent home device production firm oneself bought or developed
Data base in server database, or the intelligent home device that produced of production firm.External data base may refer to and intelligence
Home equipment production firm can have cooperation character or other manufacturer service, all of server of agent or supplier
Or storage device data storehouse.
In actual mechanical process, can buy user, when keeping in repair intelligent home device, by computer, mobile terminal,
Image-text scanner etc. electronic equipment internally data base and/or external data base input corresponding data.Or, user
When using intelligent home device, it is also possible to the use Trace Data of user is transferred to distal internal Cloud Server number by network
According to storehouse, or it is directly stored in the storage device in intelligent home device, when these data transferred by needs, far-end can be passed through
Operation directly obtains.
Below by accompanying drawing and specific embodiment, technical scheme is described in detail, it should be understood that the application
Specific features in embodiment and embodiment is the detailed description to technical scheme rather than to present techniques
The restriction of scheme, in the case of not conflicting, the technical characteristic in the embodiment of the present application and embodiment can be mutually combined.
The terms "and/or", a kind of incidence relation describing affiliated partner, can there are three kinds of passes in expression
System, such as, A and/or B, can represent: individualism A, there is A and B, individualism B these three situation simultaneously.It addition, herein
Middle character "/", typicallys represent the forward-backward correlation relation to liking a kind of "or".
Below in conjunction with the accompanying drawings the preferred embodiment of the present invention is described in detail.
As in figure 2 it is shown, the embodiment of the present invention provides a kind of data processing method, it is applied in a data handling system, number
Including Data Integration processing subsystem according to processing system, the internal database being connected with Data Integration processing subsystem, with data
Integrating the user profile processing subsystem that processing subsystem connects, the method can be described as follows.
S11: Data Integration processing subsystem is from internal database and the external data base that is connected with Data Integration subsystem
Customer data that middle acquisition is relevant to M client and product data, M is positive integer.
In the embodiment of the present invention, product data can include Smart Home that user bought, used, that keeped in repair
Device name, model, specification, and the number relevant to intelligent home device that user is inputted by test paper mode during this period
According to, such as, the intelligent home device function liked, the intelligent home device profile of desired acquisition, the intelligent family that do not likes
Occupy equipment application；Even product data use Trace Data that can also include intelligent home device etc., wherein, uses vestige
Data may be used to characterize user and carried out which function setting, and corresponding function setting when operating intelligent home device
Parameter, and operation order, etc..As a rule, as long as all data relevant to intelligent home device can serve as
Product data, this is not specifically limited by the present invention.
In actual mechanical process, can buy user, when keeping in repair intelligent home device, by computer, mobile terminal,
Image-text scanner etc. electronic equipment internally data base or external data base input the customer data of user；Can also with
When family uses intelligent home device, the use Trace Data of user is transferred to distal internal Cloud Server data by network
Storehouse, or be directly stored in the storage device in intelligent home device, when these data transferred by needs, can be grasped by far-end
Make directly to obtain corresponding customer data.
Optionally, the process of S11 may include that Data Integration processing subsystem customer data from internal database
Storehouse, CRM database and enterprise's metadatabase；And the forum's letter from the external data base being connected with Data Integration subsystem
In breath data base, trend information data base, daily behavior information database and social networks information database, it is thus achieved that with client
Relevant customer data and the product data relevant to product.
Wherein, CRM (Customer Relationship Management, customer relation management) data base can include
Relation data between relation data between client and client, and client and relatives and friends, job market friend etc..
Enterprise's metadatabase can include the title of intelligent home device product, function, basic technical indicator etc. and intelligence
The metadata that home equipment is corresponding.
Alternatively, the customer data relevant to M client obtained in data handling system and the process of product data,
May include that and obtain the client basic attribute data relevant to client, customer consuming behavior data, client's evaluation number to product
According to and client's internet relation data；And obtain the product attribute letter that the product data relevant to client, such as client are bought
Breath, purchase product price information and purpose purchase product information etc..As can be seen here, above-mentioned data cover user and product substantially
It is beneficial to manufacturer between product rely and analyze acquisition and be applicable to the every aspect information of this user.
Wherein, customer consuming behavior data may refer to client and use which kind of mode to buy intelligent home device, such as, and visitor
The shopping at network mode that family uses when buying intelligent home device, then customer consuming behavior data characterization is consumption on network；Visitor
Family uses the mode that solid shop/brick and mortar store is bought when buying intelligent home device, then customer consuming behavior data characterization is solid shop/brick and mortar store
Consumption；Client uses serial shopping way, then customer consuming behavior tables of data when buying intelligent home device
Levy as installment payment, etc., as long as the data relevant to consuming behavior can serve as customer consuming behavior data.
It is to say, in the technical scheme of the embodiment of the present application, the source of customer data and product data is the most permissible
Obtain from customer database, CRM database and the enterprise's metadatabase that the production firm of intelligent home device oneself is built
Take.Webpage forum that the outside firm of cooperation character built, OK can also be had from the production firm with intelligent home device
For recording equipment, questionnaire etc. facilities and equipment or operation, corresponding forum information data base, trend information data base,
Daily behavior information database and social networks information database obtain.
Visible, the product data source in the embodiment of the present application can be by diversified from the daily life of user
Source and channel obtain, the user data variation that therefore having to rely analyzes, and analyze the result accuracy obtained more
Height, the wider array of technique effect of the scope of application.
Customer data and product data are carried out integrating classification by S12: Data Integration processing subsystem, it is thus achieved that at least four big classes
Data, at least four big class data include client's base attribute class data, consumer product interest class data, customer event class data and
Social network relationships data.
In the embodiment of the present invention, client's base attribute class data can include the basic social property data of user and basic
Physiological attribute data etc..Basic social property data can include that the address of user, family relation data etc. are closed with basic society
The data that system is relevant；Basic physiological attribute data can include that the sex of user, age, height, body weight etc. belong to basic physiological
Property relevant data.
Such as, client's base attribute class data can include the name of user, address, father and mother's name of user, user's
Children's name, the name of the relative good friend of user, the occupation of user, position, the occupation of relative good friend, position, etc. society belong to
Property data；Client's base attribute class data can also include user and its society sex of related personnel, age, pressure value, blood
The physiological attribute data such as fat value, history of disease.
Consumer product interest class data could be for characterizing user's data to the preference of intelligent home device.Such as,
It can include the application of the preferred intelligent home device type of user, function, profile etc., naturally it is also possible to includes user institute
The intelligent home device kind that do not likes, application, outward appearance etc..As long as with user for intelligent home device happiness dislike interest phase
The data closed can serve as consumer product interest class data.
Customer event class data could be for characterizing user buying, use, keep in repair intelligent home device during
Institute's event.Such as, if the user while there occurs because of intelligent home device selling at exorbitant prices when buying intelligent home device
When abandoning the event bought, then this event can be carried out record as customer event class data.
Client's social network relationships data can be to be obtained by the network social intercourse account of user, and it can include user
Social Identity, network social intercourse account, doings, social connections people etc..
Certainly, in practical implementation, above-mentioned four big class data can be obtained respectively by the input of corresponding, or
Person, it is also possible to automatically carried out above-mentioned four big class data by the analysis identification of word content extracting or the most voluntarily
Arrange.
Optionally, during the customer data being correlated with M client and product data are classified, may include that
Determine the data attribute that in customer data and product data, each data are characterized, based on data attribute, by customer data and product
Product data are divided at least four big class data.
Wherein, data attribute may refer to the attribute that data are characterized.Such as, if obtaining data is purchasing in customer data
Buy product review information, then its data attribute can be customer comment generic attribute etc..
Optionally, based on data attribute, customer data and product data are divided at least four big class data, can wrap
Include:
Determine that in customer data and product data, data attribute shows the data of the log-on message that data are client, will determine
Data be divided into client's base attribute class data；And/or
Determine that in customer data and product data, data attribute shows that data are the data that client buys product, by determine
Data are divided into consumer product interest class data；And/or
Determine that in customer data and product data, data attribute shows that data are social data, is divided into society by social data
Hand over cyberrelationship data；And/or
Determine that in customer data and product data, data attribute shows that data are product evaluation data, by product evaluation data
It is divided into customer evaluation class data.
S13: user profile processing subsystem, based at least four big class data, determines at least one class visitor that M client is corresponding
Family attribute.
In the embodiment of the present invention, based at least four big class data, determine at least one class client properties corresponding to M client
Process may include that and processes at least four big class data, it is thus achieved that the user profile data set corresponding with M client, user
Descriptor data set at least includes: client's social characteristic data, client interests describe class data, client's consumption feature class data and
Client is to product evaluation class data；
Determine customer data and the product data proportion in user profile data set, determine M client's number according to proportion
According at least one corresponding class client properties.
Optionally, determine N number of customer data proportion in user profile data set, determine M client's number according to proportion
According at least one corresponding class client properties, may include that
Determine that at least one data that in M client, each client is correlated with are retouched at client's social characteristic data, client interests
State class data, client's consumption feature class data and client's ratio to taking respectively in product evaluation class data；
Determine, higher than at least one class descriptor data set of preset ratio, the client that respective client is corresponding according to the ratio taken
Attribute.
Please again referring to Fig. 1, based on same inventive concept, the embodiment of the present invention is also disclosed a kind of data handling system, this number
At least one data base, Data Integration processing subsystem and user profile processing subsystem is included according to processing system.
Optionally, at least one data base can include internal database and external data base, for storage and M client
Relevant customer data and product data, M is positive integer；
Described Data Integration processing subsystem, obtains described client from described internal database and described external data base
Data and described product data, and carry out described customer data and described product data integrating classification, it is thus achieved that at least four big classes
Data；Wherein, described at least four big class data include client's base attribute class data, consumer product interest class data, client's thing
Part class data and social network relationships data；
Described user profile processing subsystem, based on described at least four big class data, determines that described M client is corresponding extremely
A few class client properties.
Optionally, described Data Integration processing subsystem is used for:
Described Data Integration processing subsystem customer database from internal database, CRM database and unit of enterprise
Data base；And forum information data base from the external data base being connected with described Data Integration subsystem, trend information
In data base, daily behavior information database and social networks information database, it is thus achieved that the client relevant to described M client
Data.
Optionally, described Data Integration processing subsystem is used for:
Determine the data attribute that in described M customer data, each customer data is characterized；
Based on described data attribute, described M customer data is divided into described at least four big class data.
Optionally, described Data Integration processing subsystem is used for:
Determine that in described customer data and described product data, data attribute shows the number of the log-on message that data are client
According to, the data determined are divided into described client's base attribute class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are the data that client buys product,
The data determined are divided into described consumer product interest class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are social data, by described social activity
Data are divided into described social network relationships data；And/or
Determine that in described customer data and described product data, data attribute shows that data are product evaluation data, by described
Product evaluation data are divided into described customer evaluation class data.
Optionally, described user profile processing subsystem is used for:
Described at least four big class data are processed, it is thus achieved that the user profile data set corresponding with described M client, institute
State in user profile data set and at least include: client's social characteristic data, client interests describe class data, client's consumption feature class
Data, client is to product evaluation class data；
Determine described customer data and the described product data proportion in described user profile data set, according to described ratio
Heavily determine at least one class client properties that described M customer data is corresponding.
Optionally, described user profile processing subsystem is used for:
Determine that at least one data that in described M client, each client is correlated with are in described client's social characteristic data, institute
State client interests to describe class data, described client's consumption feature class data and described client and account for respectively in product evaluation class data
Ratio；
Determine that respective client is corresponding according to the described ratio taken higher than at least one class descriptor data set of preset ratio
Client properties.
Obviously, those skilled in the art can carry out various change and the modification essence without deviating from the present invention to the present invention
God and scope.So, if these amendments of the present invention and modification belong to the scope of the claims in the present invention and equivalent technologies thereof
Within, then the present invention is also intended to comprise these change and modification.
Claims (12)
1. a data processing method, is applied in a data handling system, and described data handling system includes at Data Integration
Reason subsystem, the internal database being connected with described Data Integration processing subsystem, and with described Data Integration processing subsystem
The user profile processing subsystem connected, it is characterised in that described method includes:
Described Data Integration processing subsystem is from described internal database and the external number that is connected with described Data Integration subsystem
According to obtaining the customer data relevant to M client and product data in storehouse, M is positive integer；
Described customer data and described product data are carried out integrating classification by described Data Integration processing subsystem, it is thus achieved that at least four
Big class data, described at least four big class data include client's base attribute class data, consumer product interest class data, customer event
Class data and social network relationships data；
Described user profile processing subsystem based on described at least four big class data, determine that described M client is corresponding at least one
Class client properties.
2. the method for claim 1, it is characterised in that described Data Integration processing subsystem is from described internal number
The customer data relevant with M client is obtained according to storehouse and to the external data base of described Data Integration subsystem connection, including:
Described Data Integration processing subsystem customer database from internal database, CRM database and enterprise's metadata
Storehouse；And forum information data base from the external data base being connected with described Data Integration subsystem, trend information data
In storehouse, daily behavior information database and social networks information database, it is thus achieved that the client number relevant to described M client
According to.
3. the method for claim 1, it is characterised in that described Data Integration processing subsystem is to described client's number
According to and described product data carry out integrate classification, it is thus achieved that at least four big class data, including:
Determine the data attribute that in described M customer data, each customer data is characterized；
Based on described data attribute, described M customer data is divided into described at least four big class data.
4. method as claimed in claim 3, it is characterised in that described based on described data attribute, by described customer data and
Described product data be divided into described at least four big class data, including:
Determine that in described customer data and described product data, data attribute shows the data of the log-on message that data are client, will
The data determined are divided into described client's base attribute class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are the data that client buys product, will be really
Fixed data are divided into described consumer product interest class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are social data, by described social data
It is divided into described social network relationships data；And/or
Determine that in described customer data and described product data, data attribute shows that data are product evaluation data, by described product
Evaluating data is divided into described customer evaluation class data.
5. method as claimed in claim 4, it is characterised in that described user profile processing subsystem based on described at least
Four big class data, determine at least one class client properties that described M client is corresponding, including:
Described at least four big class data are processed, it is thus achieved that the user profile data set corresponding with described M client, described use
Family descriptor data set at least includes: client's social characteristic data, client interests describe class data, client's consumption feature class number
According to, client is to product evaluation class data；
Determine described customer data and the described product data proportion in described user profile data set, true according to described proportion
At least one class client properties that fixed described M customer data is corresponding.
6. method as claimed in claim 5, it is characterised in that described determine that described N number of customer data is at described user profile
Proportion in data set, determines, according to described proportion, at least one class client properties that described M customer data is corresponding, including:
Determine that at least one data that in described M client, each client is correlated with are described client's social characteristic data, described visitor
Family interesting measure class data, described client's consumption feature class data and described client are to taking respectively in product evaluation class data
Ratio；
Determine, higher than at least one class descriptor data set of preset ratio, the client that respective client is corresponding according to the described ratio taken
Attribute.
7. a data handling system, it is characterised in that described data handling system includes:
At least one data base, including internal database and external data base, for the customer data that storage is relevant to M client
And product data, M is positive integer；
Described Data Integration processing subsystem, obtains described customer data from described internal database and described external data base
And described product data, and carry out described customer data and described product data integrating classification, it is thus achieved that at least four big class data；
Wherein, described at least four big class data include client's base attribute class data, consumer product interest class data, customer event class number
According to and social network relationships data；
Described user profile processing subsystem based on described at least four big class data, determine that described M client is corresponding at least one
Class client properties.
8. system as claimed in claim 7, it is characterised in that described Data Integration processing subsystem is used for:
Described Data Integration processing subsystem customer database from internal database, CRM database and enterprise's metadata
Storehouse；And forum information data base from the external data base being connected with described Data Integration subsystem, trend information data
In storehouse, daily behavior information database and social networks information database, it is thus achieved that the client number relevant to described M client
According to.
9. system as claimed in claim 7, it is characterised in that described Data Integration processing subsystem is used for:
Determine the data attribute that in described M customer data, each customer data is characterized；
Based on described data attribute, described M customer data is divided into described at least four big class data.
10. system as claimed in claim 9, it is characterised in that described Data Integration processing subsystem is used for:
Determine that in described customer data and described product data, data attribute shows the data of the log-on message that data are client, will
The data determined are divided into described client's base attribute class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are the data that client buys product, will be really
Fixed data are divided into described consumer product interest class data；And/or
Determine that in described customer data and described product data, data attribute shows that data are social data, by described social data
It is divided into described social network relationships data；And/or
Determine that in described customer data and described product data, data attribute shows that data are product evaluation data, by described product
Evaluating data is divided into described customer evaluation class data.
11. systems as claimed in claim 10, it is characterised in that described user profile processing subsystem is used for:
Described at least four big class data are processed, it is thus achieved that the user profile data set corresponding with described M client, described use
Family descriptor data set at least includes: client's social characteristic data, client interests describe class data, client's consumption feature class number
According to, client is to product evaluation class data；
Determine described customer data and the described product data proportion in described user profile data set, true according to described proportion
At least one class client properties that fixed described M customer data is corresponding.
12. systems as claimed in claim 11, it is characterised in that described user profile processing subsystem is used for:
Determine that at least one data that in described M client, each client is correlated with are described client's social characteristic data, described visitor
Family interesting measure class data, described client's consumption feature class data and described client are to taking respectively in product evaluation class data
Ratio；
Determine, higher than at least one class descriptor data set of preset ratio, the client that respective client is corresponding according to the described ratio taken
Attribute.
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| CN201610170241X | 2016-03-23 | ||
| CN201610170241 | 2016-03-23 |
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| CN106202218A true CN106202218A (en) | 2016-12-07 |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109359998A (en) * | 2018-08-15 | 2019-02-19 | 中国平安人寿保险股份有限公司 | Customer data processing method, device, computer installation and storage medium |
| WO2019165704A1 (en) * | 2018-03-01 | 2019-09-06 | 广东瑞德智能科技股份有限公司 | Data processing method and apparatus for smart appliance gateway device, and smart appliance gateway |
| CN111651454A (en) * | 2020-05-18 | 2020-09-11 | 珠海格力电器股份有限公司 | Data processing method and device and computer equipment |
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