CN110135901A - A kind of enterprise customer draws a portrait construction method, system, medium and electronic equipment - Google Patents
A kind of enterprise customer draws a portrait construction method, system, medium and electronic equipment Download PDFInfo
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- CN110135901A CN110135901A CN201910389932.2A CN201910389932A CN110135901A CN 110135901 A CN110135901 A CN 110135901A CN 201910389932 A CN201910389932 A CN 201910389932A CN 110135901 A CN110135901 A CN 110135901A
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Abstract
The present invention provides a kind of enterprise customer and draws a portrait construction method, system, medium and electronic equipment, the described method includes: obtaining enterprise customer in the history feature data of internet platform, wherein, the history feature data include basic attribute data, behavior property data and service attribute data；Clean the abnormal data in the history feature data；The history feature data of different enterprise customers are analyzed, decision tree training pattern is constructed；According to the decision tree training pattern, label to enterprise customer, building enterprise customer's portrait.
Description
Technical field
The present invention relates to user's Portrait brand technology fields, in particular to a kind of enterprise customer portrait construction method, are
System, medium and electronic equipment.
Background technique
After internet gradually steps into big data era, all behaviors of consumer all will be visualization in face of enterprise
's.Enterprise also start absorbed point day benefit focus on how using big data come accurately to provide services to the user；Then, it uses
Family portrait also just comes into being.
User's portrait, i.e. user information labeling are exactly by collecting and analysis user's social property, living habit, row
After data for equal main informations, the overall picture of a user is ideally taken out.User's portrait is actually that excavation is wherein hidden
The value information of hiding, analysis and the characteristic behavior for summarizing user；At present in fields such as B2C, telecommunications with more.
In addition, network video has become people and obtains video information and entertainment information with the rapid development of internet
One of main source.And number of videos improves the body of user in rapid growth, major video website or client
Effect is tested, corresponding video recommendations are often carried out to user according to the favorable rating of video user.Video is recommended to believe to user
The key technology used when breath is drawn a portrait first is that establishing user, and user's portrait is also known as user role, is delineated target as one kind and is used
Family, the effective tool for contacting user's demand and design direction, user's portrait are widely used in each field.We are in reality
The attribute of user, behavior and expectation have often been coupled with the most plain and closeness to life language by border during operating
Come.
Currently, user's portrait is mainly completed by Data Integration and model training.In terms of Data Integration, mainly pass through
User stays in some behaviors, transaction data on internet platform, and structural data and unstructured data are integrated；Mould
In terms of type training, mainly learn the behavioural habits of user by machine learning algorithm, then labels to user.But in B2B
Field need to fully consider the variation of business scenario and the characteristic of enterprise itself to realize the accurate portrait of platform enterprise user.
However, the behavior of enterprise customer can also change correspondingly with the variation of operation flow, portrait can also change；Enterprise's rule simultaneously
The difference of mould, affiliated industry, the result of enterprise customer's portrait also can be different.
Therefore, in long-term research and development, inventor has carried out a large amount of research to user's portrait, proposes a kind of enterprise
One of user's portrait construction method, to solve the above technical problems.
Summary of the invention
The purpose of the present invention is to provide a kind of enterprise customer portrait construction method, system, medium and electronic equipments, can
Solve at least one technical problem mentioned above.Concrete scheme is as follows:
A kind of enterprise customer's portrait construction method, this method are drawn a portrait for enterprise customer in building system, the portrait structure
System is built including obtaining module, cleaning module, model construction module, portrait building module, this method comprises:
Step 1, it obtains module and obtains enterprise customer in the history feature data of internet platform, wherein the history is special
Levying data includes basic attribute data, behavior property data and service attribute data；
Step 2, cleaning module cleans the abnormal data in the history feature data；
Step 3, model construction module analyzes the history feature data of different enterprise customers, building decision tree training mould
Type；
Step 4, portrait building module labels to enterprise customer according to the decision tree training pattern, and building enterprise uses
Family portrait.
Further, the basic attribute data includes enterprise ID, scope of the enterprise, enterprise when internet platform is registered
Between, the affiliated industry of enterprise.
Further, the behavior property data include whether browsing shop after enterprise customer enters internet platform website
Paving, internet platform website residence time, whether had consulting behavior.
Further, the service attribute data include submit the order time, submit order number, order sources,
The conclusion of the business order time, conclusion of the business order number, whether cancel, the affiliated classification of order, trade mode, nearly 1 year submission order number,
Conclusion of the business order number.
Further, the abnormal data include: empty data in history feature data, repeated data, be not inconsistent it is logical
Data.
Further, it according to the decision tree training pattern, labels to enterprise customer, comprising:
Since root node, the corresponding characteristic of enterprise customer to be sorted is tested；
The characteristic is assigned to its child node according to the test result, each child node corresponds to the spy at this time
One value of sign；
Continue to carry out the characteristic recurrence test and distribute, until reaching leaf node, by the class of leaf node storage
It Zuo Wei not enterprise customer's label.
Further, further comprise: enterprise customer portrait being analyzed, the institute of internet platform client is obtained
Belong to classification.
A kind of enterprise customer's portrait building system, the system is for realizing the portrait construction method, comprising:
Module is obtained, for obtaining enterprise customer in the history feature data of internet platform, wherein the history feature
Data include basic attribute data, behavior property data and service attribute data；
Cleaning module, the abnormal data for cleaning in the history feature data；
Model construction module, for analyzing the history feature data of different enterprise customers, building decision tree training mould
Type；
Portrait building module constructs enterprise customer for being labelled to enterprise customer according to the decision tree training pattern
Portrait.
A kind of computer readable storage medium is stored thereon with computer program, real when described program is executed by processor
The existing portrait construction method.
A kind of electronic equipment, comprising:
One or more processors；
Storage device, for storing one or more programs, when one or more of programs are one or more of
When processor executes, so that one or more of processors realize the portrait construction method.
Compared with prior art, the embodiment of the present invention is basic according to medium and small micro- enterprise for the above scheme of the embodiment of the present invention
The data such as attribute, behavior, transaction, the characteristics of portraying different scales enterprises service demand, compared to artificial marketing have more specific aim and
Actual effect, is retained simultaneously for client and customer value excavation provides a solution.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows and meets implementation of the invention
Example, and be used to explain the principle of the present invention together with specification.It should be evident that the accompanying drawings in the following description is only the present invention
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.In the accompanying drawings:
Fig. 1 shows a kind of flow chart of enterprise customer's portrait construction method according to an embodiment of the present invention；
Fig. 2 shows the sides according to an embodiment of the present invention to be labelled according to the decision tree training pattern to enterprise customer
Method flow chart；
Fig. 3 shows a kind of structural schematic diagram of enterprise customer's portrait building system according to an embodiment of the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into
It is described in detail to one step, it is clear that described embodiments are only a part of the embodiments of the present invention, rather than whole implementation
Example.Based on the embodiments of the present invention, obtained by those of ordinary skill in the art without making creative efforts
All other embodiment, shall fall within the protection scope of the present invention.
The term used in embodiments of the present invention is only to be not intended to be limiting merely for for the purpose of describing particular embodiments
The present invention.In the embodiment of the present invention and the "an" of singular used in the attached claims, " described " and "the"
It is also intended to including most forms, unless the context clearly indicates other meaning, " a variety of " generally comprise at least two.
It should be appreciated that term "and/or" used herein is only a kind of incidence relation for describing affiliated partner, indicate
There may be three kinds of relationships, for example, A and/or B, can indicate: individualism A, exist simultaneously A and B, individualism B these three
Situation.In addition, character "/" herein, typicallys represent the relationship that forward-backward correlation object is a kind of "or".
It will be appreciated that though may be described in embodiments of the present invention using term first, second, third, etc..,
But these ... it should not necessarily be limited by these terms.These terms be only used to by ... distinguish.For example, not departing from implementation of the present invention
In the case where example range, first ... can also be referred to as second ..., and similarly, second ... can also be referred to as the
One ....
Depending on context, word as used in this " if ", " if " can be construed to " ... when " or
" when ... " or " in response to determination " or " in response to detection ".Similarly, context is depended on, phrase " if it is determined that " or " such as
Fruit detection (condition or event of statement) " can be construed to " when determining " or " in response to determination " or " when detection (statement
Condition or event) when " or " in response to detection (condition or event of statement) ".
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
Include, so that commodity or device including a series of elements not only include those elements, but also including not clear
The other element listed, or further include for this commodity or the intrinsic element of device.In the feelings not limited more
Under condition, the element that is limited by sentence "including a ...", it is not excluded that in the commodity or device for including the element also
There are other identical elements.
Embodiment 1
Referring to Fig. 1, the embodiment of the present invention provides a kind of enterprise customer's portrait construction method, this method is by fully considering
Business scenario, the scale of enterprise and industry attribute, realization draw a portrait to different classes of enterprise.
This method is drawn a portrait for enterprise customer in building system, and the portrait building system includes obtaining module, cleaning mould
Block, model construction module, portrait building module, this method comprises:
Step 1, it obtains module and obtains enterprise customer in the history feature data of internet platform, wherein the history is special
Levying data includes basic attribute data, behavior property data and service attribute data；
Specifically, mainly acquiring the historical data of three enterprise's essential attribute, behavior property, service attribute aspects.It is described
The basic attribute data of enterprise includes: enterprise ID, scope of the enterprise, enterprise in platform registion time, the affiliated industry of enterprise.The row
Include: enterprise employer from platform website is entered to the predominating path for leaving platform website for attribute data, is mainly employed including enterprise
It is main whether browsed shop, platform website residence time, whether had consulting behavior.The service attribute data are mainly wrapped
Include: submit the order time, submit order number, order sources, the conclusion of the business order time, conclusion of the business order number, whether cancel,
The affiliated classification of order, trade mode, nearly 1 year submission order number, conclusion of the business order number.
Step 2, cleaning module cleans the abnormal data in the history feature data；
Specifically, deleting the abnormal data in the history feature data；The abnormal data includes each category
Empty data, repeated data in property feature and logical data is not met.
It further may include that the processing of 0-1 standardized calculation is carried out to the characteristic after the cleaning.That is, will
Classified variable carries out the processing of 0-1 standardized calculation.
Step 3, model construction module analyzes the history feature data of different enterprise customers, building decision tree training mould
Type；
Specifically, being determined using the history basic attribute data of enterprise customer, behavior property data, the building of service attribute data
Plan tree training pattern.Decision tree (decision tree) is a tree construction, specifically can be binary tree or non-binary trees；Tree
Each leaf node indicates the test on a characteristic attribute in structure, and each branch represents this characteristic attribute in some codomain
Output, and each leaf node store a classification.The selection course of root node feature includes: in the decision tree
Firstly, determine the comentropy H (X) of each variable,Become
The uncertainty of amount is bigger, and entropy is also bigger, and information content required for it is made clear is also bigger, and entropy is the flat of whole system
Equal size of message.
Secondly, determining the conditional information entropy of each variable, i.e., according to the comentropy under the conditions of certain
Again, information gain-ratio g is utilizedr=IG (X)/Hm(X)=H (Y)-H (Y/X)/Hm(X) feature is selected, wherein IG
(X)=H (Y)-H (Y/X) is information gain.
Step 4, portrait building module labels to enterprise customer according to the decision tree training pattern, and building enterprise uses
Family portrait.Specifically, referring to Fig. 2, described label to enterprise customer according to the decision tree training pattern, comprising:
Step 41, since root node, the corresponding characteristic of enterprise customer to be sorted is tested；
Step 42, the characteristic is assigned to by its child node according to the test result, at this time each child node pair
Answer a value of this feature；
Step 43, continue to carry out the characteristic recurrence test and distribute, until reaching leaf node, leaf node is deposited
The classification put is as enterprise customer's label.
Further, which comprises enterprise customer portrait is analyzed, the institute of internet platform client is obtained
Belong to classification.Client's classification includes important value client, important holding client, important development client and important keeps client.
Specifically, carrying out analysis to enterprise customer portrait is classified using RFM model, RFM analysis is basis
Enterprise customer's active degree and transaction amount contribution, carry out a kind of method that user is worth subdivision；Nearest one can specifically be passed through
Secondary consumption R (Recency), consuming frequency F (Frequency), three dimensions of spending amount M (Monetary), by enterprise customer
It is divided into important value client, important holding client, important development client and important keeps this 4 seed type of client.
Concrete analysis process include: firstly, calculate RFM items score value, wherein consumption the date it is closer apart from current date,
Score is higher；Trading frequency is higher, and score is higher；Transaction amount is higher, and score is higher；Then RFM score value is summed up；Last basis
RFM score value classifies to enterprise customer.
In another embodiment, further the portrait of the analysis result of data and each enterprise customer can be summarized and carry out can
It is presented depending on changing.Specifically, visualization result is carried out respective handling to marketing personnel.
Enterprise customer provided in an embodiment of the present invention draws a portrait essential attribute of the construction method according to medium and small micro- enterprise, behavior category
Property, the data such as service attribute, the characteristics of portraying different scales enterprises service demand, have more specific aim and reality compared to artificial marketing
Effect, is retained simultaneously for client and customer value excavation provides a solution.
Embodiment 2
Referring to Fig. 3, the embodiment of the present invention provides a kind of enterprise customer's portrait building system 300, which includes:
Obtain module 310, cleaning module 320, model construction module 330 and portrait building module 340.
The acquisition module 310 is for obtaining enterprise customer in the history feature data of internet platform, wherein described to go through
History characteristic includes basic attribute data, behavior property data and service attribute data.Specifically, the basic category of the enterprise
Property data include: enterprise ID, scope of the enterprise, enterprise in platform registion time, the affiliated industry of enterprise.The behavior property data packet
Include: enterprise employer mainly includes whether enterprise employer browsed from platform website is entered to the predominating path for leaving platform website
Shop, platform website residence time, whether had consulting behavior.The service attribute data specifically include that submission order
Whether the time submits order number, order sources, the conclusion of the business order time, conclusion of the business order number, cancels, the affiliated class of order
Mesh, trade mode, nearly 1 year submission order number, conclusion of the business order number.
The cleaning module 320 is used for the abnormal data cleaned in the history feature data.Specifically, the cleaning mould
Block 320 deletes the abnormal data in the history feature data；The abnormal data includes in each attributive character
Empty data, repeated data and logical data is not met.
It further may include standard processing modules 350, by being carried out based on 0-1 standardization to the characteristic after the cleaning
Calculation processing.That is, classified variable is carried out the processing of 0-1 standardized calculation.
The model construction module 330 is used to analyze the history feature data of different enterprise customers, constructs decision tree
Training pattern.Specifically, history basic attribute data, behavior property number of the model construction module 330 using enterprise customer
Decision tree training pattern is constructed according to, service attribute data.Decision tree (decision tree) is a tree construction, specifically can be with
It is binary tree or non-binary trees；Each leaf node indicates the test on a characteristic attribute in tree construction, and each branch represents this
Output of a characteristic attribute in some codomain, and each leaf node stores a classification.The model construction module 330 constructs
Include: to the selection method of root node feature during decision tree
Firstly, determine the comentropy H (X) of each variable,Become
The uncertainty of amount is bigger, and entropy is also bigger, and information content required for it is made clear is also bigger, and entropy is the flat of whole system
Equal size of message.
Secondly, determining the conditional information entropy of each variable, i.e., according to the comentropy under the conditions of certain
Again, information gain-ratio g is utilizedr=IG (X)/Hm(X)=H (Y)-H (Y/X)/Hm(X) feature is selected, wherein IG
(X)=H (Y)-H (Y/X) is information gain.
The portrait building module 340 is used to label to enterprise customer according to the decision tree training pattern, building enterprise
Industry user portrait.Specifically, the portrait constructs module 340, comprising:
Test module 341, for since root node, testing the corresponding characteristic of enterprise customer to be sorted；
Distribution module 342, for the characteristic to be assigned to its child node according to the test result, at this time each
Child node corresponds to a value of this feature；
Recurrence module 343, for continuing to carry out recurrence test to the characteristic and distribute, until reaching leaf node,
Using the classification of leaf node storage as enterprise customer's label.
Further, the system 300 includes analysis module 360, for analyzing enterprise customer portrait, is obtained
The generic of internet platform client.Client's classification includes important value client, important holding client, important development visitor
Family and important keep client.
Specifically, the analysis module 360 classifies to enterprise customer using RFM model, RFM analysis is according to enterprise
User's active degree and transaction amount contribution, carry out a kind of method that user is worth subdivision；R can be consumed by the last time
(Recency), enterprise customer is divided and is attached most importance to by three dimensions of consuming frequency F (Frequency), spending amount M (Monetary)
It wants value customer, important holding client, important development client and important keeps this 4 seed type of client.
The analytic process of the analysis module 360 includes: firstly, calculating RFM items score value, wherein consumption date distance
Current date is closer, and score is higher；Trading frequency is higher, and score is higher；Transaction amount is higher, and score is higher；Then RFM is summed up
Score value；Finally classified according to RFM score value to enterprise customer.
Further, the system 300 further includes a visual presentation module 370, for by the analysis result of data and often
The portrait of a enterprise customer summarizes and carries out visualization presentation.Specifically, visualization result is carried out corresponding position to marketing personnel
Reason.
Enterprise customer provided in an embodiment of the present invention draws a portrait essential attribute of the building system according to medium and small micro- enterprise, behavior category
Property, the data such as service attribute, the characteristics of portraying different scales enterprises service demand, have more specific aim and reality compared to artificial marketing
Effect, is retained simultaneously for client and customer value excavation provides a solution.
Embodiment 3
The present embodiment provides a kind of electronic equipment, which is used for the intelligent Matching method of property tax platform, and the electronics is set
It is standby, comprising: at least one processor；And the memory being connect at least one described processor communication；Wherein,
The memory is stored with the instruction that can be executed by one processor, and described instruction is by described at least one
Manage device execute so that at least one described processor can:
Enterprise customer is obtained in the history feature data of internet platform, wherein the history feature data include basic
Attribute data, behavior property data and service attribute data；
Clean the abnormal data in the history feature data；
The history feature data of different enterprise customers are analyzed, decision tree training pattern is constructed；
According to the decision tree training pattern, label to enterprise customer, building enterprise customer's portrait.
Embodiment 4
The embodiment of the present disclosure provides a kind of nonvolatile computer storage media, and the computer storage medium is stored with
The true from false of bills examination side in above-mentioned any means embodiment can be performed in computer executable instructions, the computer executable instructions
Method.
Embodiment 5
The embodiment of the present disclosure provides a kind of electronic equipment, and the electronic equipment in the embodiment of the present disclosure may include but unlimited
In such as mobile phone, laptop, digit broadcasting receiver, PDA (personal digital assistant), PAD (tablet computer), PMP
The mobile terminal of (portable media player), car-mounted terminal (such as vehicle mounted guidance terminal) etc. and such as number TV,
The fixed terminal of desktop computer etc..
Electronic equipment may include processing unit (such as central processing unit, graphics processor etc.), can be according to storage
It is held in the program in read-only memory (ROM) or from the program that storage device is loaded into random access storage device (RAM)
The various movements appropriate of row and processing.In RAM, it is also stored with various programs and data needed for electronic device.Processing
Device, ROM and RAM are connected with each other by bus.Input/output (I/O) interface is also connected to bus.
In general, following device can connect to I/O interface: including such as touch screen, touch tablet, keyboard, mouse, camera shooting
The input unit of head, microphone, accelerometer, gyroscope etc.；Including such as liquid crystal display (LCD), loudspeaker, vibrator etc.
Output device；Storage device including such as tape, hard disk etc.；And communication device.Communication device can permit electronics and set
It is standby wirelessly or non-wirelessly to be communicated with other equipment to exchange data.
Particularly, in accordance with an embodiment of the present disclosure, it may be implemented as computer above with reference to the process of flow chart description
Software program.For example, embodiment of the disclosure includes a kind of computer program product comprising be carried on computer-readable medium
On computer program, which includes the program code for method shown in execution flow chart.In such reality
It applies in example, which can be downloaded and installed from network by communication device, or is mounted from storage device,
Or it is mounted from ROM.When the computer program is executed by processing unit, executes and limited in the method for the embodiment of the present disclosure
Above-mentioned function.
It should be noted that the above-mentioned computer-readable medium of the disclosure can be computer-readable signal media or meter
Calculation machine readable storage medium storing program for executing either the two any combination.Computer readable storage medium for example can be --- but not
Be limited to --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor system, device or device, or any above combination.Meter
The more specific example of calculation machine readable storage medium storing program for executing can include but is not limited to: have the electrical connection, just of one or more conducting wires
Taking formula computer disk, hard disk, random access storage device (RAM), read-only memory (ROM), erasable type may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In the disclosure, computer readable storage medium can be it is any include or storage journey
The tangible medium of sequence, the program can be commanded execution system, device or device use or in connection.And at this
In open, computer-readable signal media may include in a base band or as the data-signal that carrier wave a part is propagated,
In carry computer-readable program code.The data-signal of this propagation can take various forms, including but not limited to
Electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be computer-readable and deposit
Any computer-readable medium other than storage media, the computer-readable signal media can send, propagate or transmit and be used for
By the use of instruction execution system, device or device or program in connection.Include on computer-readable medium
Program code can transmit with any suitable medium, including but not limited to: electric wire, optical cable, RF (radio frequency) etc. are above-mentioned
Any appropriate combination.
Above-mentioned computer-readable medium can be included in above-mentioned electronic equipment；It is also possible to individualism, and not
It is fitted into the electronic equipment.
The calculating of the operation for executing the disclosure can be write with one or more programming languages or combinations thereof
Machine program code, above procedure design language include object oriented program language-such as Java, Smalltalk, C+
+, it further include conventional procedural programming language-such as " C " language or similar programming language.Program code can
Fully to execute, partly execute on the user computer on the user computer, be executed as an independent software package,
Part executes on the remote computer or executes on a remote computer or server completely on the user computer for part.
In situations involving remote computers, remote computer can pass through the network of any kind --- including local area network (LAN)
Or wide area network (WAN)-is connected to subscriber computer, or, it may be connected to outer computer (such as utilize Internet service
Provider is connected by internet).
Flow chart and block diagram in attached drawing are illustrated according to the system of the various embodiments of the disclosure, method and computer journey
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part of one module, program segment or code of table, a part of the module, program segment or code include one or more use
The executable instruction of the logic function as defined in realizing.It should also be noted that in some implementations as replacements, being marked in box
The function of note can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are actually
It can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it to infuse
Meaning, the combination of each box in block diagram and or flow chart and the box in block diagram and or flow chart can be with holding
The dedicated hardware based system of functions or operations as defined in row is realized, or can use specialized hardware and computer instruction
Combination realize.
Being described in unit involved in the embodiment of the present disclosure can be realized by way of software, can also be by hard
The mode of part is realized.Wherein, the title of unit does not constitute the restriction to the unit itself under certain conditions, for example, the
One acquiring unit is also described as " obtaining the unit of at least two internet protocol addresses ".
Claims (10)
- The construction method 1. a kind of enterprise customer draws a portrait, this method are drawn a portrait for enterprise customer in building system, the portrait building System includes obtaining module, cleaning module, model construction module, portrait building module, which is characterized in that this method comprises:Step 1, it obtains module and obtains enterprise customer in the history feature data of internet platform, wherein the history feature number According to including basic attribute data, behavior property data and service attribute data；Step 2, cleaning module cleans the abnormal data in the history feature data；Step 3, model construction module analyzes the history feature data of different enterprise customers, constructs decision tree training pattern；Step 4, portrait building module labels to enterprise customer according to the decision tree training pattern, and building enterprise customer draws Picture.
- 2. portrait construction method according to claim 1, which is characterized in that the basic attribute data include enterprise ID, Scope of the enterprise, enterprise are in internet platform registion time, the affiliated industry of enterprise.
- 3. portrait construction method according to claim 1, which is characterized in that the behavior property data include enterprise customer Whether browsed after into internet platform website shop, internet platform website residence time, whether had consulting go For.
- 4. portrait construction method according to claim 1, which is characterized in that the service attribute data include submitting order Whether the time submits order number, order sources, the conclusion of the business order time, conclusion of the business order number, cancels, the affiliated class of order Mesh, trade mode, nearly 1 year submission order number, conclusion of the business order number.
- 5. portrait construction method according to claim 1, which is characterized in that the abnormal data includes: history feature number Empty data in, do not meet logical data at repeated data.
- 6. portrait construction method according to claim 1, which is characterized in that according to the decision tree training pattern, to enterprise Industry user labelling, comprising:Since root node, the corresponding characteristic of enterprise customer to be sorted is tested；The characteristic is assigned to its child node according to the test result, each child node corresponds to this feature at this time One value；Continue to carry out the characteristic recurrence test and distribute, until reaching leaf node, the classification of leaf node storage is made For enterprise customer's label.
- 7. portrait construction method according to claim 1, which is characterized in that further comprise: being drawn to the enterprise customer As being analyzed, the generic of internet platform client is obtained.
- The building system 8. a kind of enterprise customer draws a portrait, the system construct for realizing the portrait of one of such as claim 1 to 7 Method characterized by comprisingModule is obtained, for obtaining enterprise customer in the history feature data of internet platform, wherein the history feature data Including basic attribute data, behavior property data and service attribute data；Cleaning module, the abnormal data for cleaning in the history feature data；Model construction module constructs decision tree training pattern for analyzing the history feature data of different enterprise customers；Portrait building module, for being labelled to enterprise customer according to the decision tree training pattern, building enterprise customer is drawn Picture.
- 9. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that described program is by processor Construction method of drawing a portrait as described in any one of claims 1 to 7 is realized when execution.
- 10. a kind of electronic equipment characterized by comprisingOne or more processors；Storage device, for storing one or more programs, when one or more of programs are by one or more of processing When device executes, the construction method so that realization of one or more of processors is drawn a portrait as described in any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910389932.2A CN110135901A (en) | 2019-05-10 | 2019-05-10 | A kind of enterprise customer draws a portrait construction method, system, medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910389932.2A CN110135901A (en) | 2019-05-10 | 2019-05-10 | A kind of enterprise customer draws a portrait construction method, system, medium and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110135901A true CN110135901A (en) | 2019-08-16 |
Family
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| CN110717101A (en) * | 2019-09-30 | 2020-01-21 | 上海淇玥信息技术有限公司 | User classification method and device based on application behaviors and electronic equipment |
| CN110942338A (en) * | 2019-11-01 | 2020-03-31 | 支付宝(杭州)信息技术有限公司 | Marketing enabling strategy recommendation method and device and electronic equipment |
| CN111191713A (en) * | 2019-12-27 | 2020-05-22 | 大象慧云信息技术有限公司 | User portrait method and device based on invoice data |
| CN111784385A (en) * | 2020-06-19 | 2020-10-16 | 杭州未名信科科技有限公司 | Manufacturing industry-oriented client portrait construction method and device and computer storage medium |
| CN111798265A (en) * | 2020-05-27 | 2020-10-20 | 北京国电通网络技术有限公司 | Accurate marketing method and device suitable for enterprise users |
| CN111815173A (en) * | 2020-07-10 | 2020-10-23 | 东软集团（上海）有限公司 | Enterprise portrait assessment method based on association rule |
| CN111966904A (en) * | 2020-08-18 | 2020-11-20 | 平安国际智慧城市科技股份有限公司 | Information recommendation method based on multi-user portrait model and related device |
| CN112269778A (en) * | 2020-10-15 | 2021-01-26 | 西安工程大学 | Equipment fault diagnosis method |
| CN112446744A (en) * | 2020-12-14 | 2021-03-05 | 成都航天科工大数据研究院有限公司 | Method, system and medium for constructing enterprise portrait based on industrial product supply and demand platform |
| CN112580332A (en) * | 2020-11-19 | 2021-03-30 | 淮阴工学院 | Enterprise portrait method based on label layering and deepening modeling |
| CN113065894A (en) * | 2021-03-24 | 2021-07-02 | 天天惠民(北京)智能物流科技有限公司 | Data collection method and device based on user portrait and order analysis and storage medium |
| CN113079148A (en) * | 2021-03-25 | 2021-07-06 | 恒安嘉新（北京）科技股份公司 | Industrial Internet safety monitoring method, device, equipment and storage medium |
| CN113362097A (en) * | 2020-03-06 | 2021-09-07 | 北京京东振世信息技术有限公司 | User determination method and device |
| CN113486225A (en) * | 2021-07-06 | 2021-10-08 | 北京国联视讯信息技术股份有限公司 | Enterprise image display method and system based on big data |
| CN113793061A (en) * | 2021-09-27 | 2021-12-14 | 武汉众邦银行股份有限公司 | Business bank customer rating method and device integrating analytic hierarchy process (analytic hierarchy process) and RFM |
| WO2022016561A1 (en) * | 2020-07-22 | 2022-01-27 | 江苏宏创信息科技有限公司 | Ai modeling system and method for policy profiling based on big data |
| CN114185880A (en) * | 2021-12-10 | 2022-03-15 | 北京金堤科技有限公司 | Affiliated industry data determining method and device |
| CN114238615A (en) * | 2021-12-14 | 2022-03-25 | 淄博天大创新科技服务有限公司 | Enterprise service achievement data processing method and system |
| CN116776006A (en) * | 2023-08-24 | 2023-09-19 | 中资科技(江苏)有限公司 | Customer portrait construction method and system for enterprise financing |
| CN117726359A (en) * | 2024-02-08 | 2024-03-19 | 成都纳宝科技有限公司 | Interactive marketing method, system and equipment |
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Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110717101A (en) * | 2019-09-30 | 2020-01-21 | 上海淇玥信息技术有限公司 | User classification method and device based on application behaviors and electronic equipment |
| CN110942338A (en) * | 2019-11-01 | 2020-03-31 | 支付宝(杭州)信息技术有限公司 | Marketing enabling strategy recommendation method and device and electronic equipment |
| CN111191713A (en) * | 2019-12-27 | 2020-05-22 | 大象慧云信息技术有限公司 | User portrait method and device based on invoice data |
| CN113362097A (en) * | 2020-03-06 | 2021-09-07 | 北京京东振世信息技术有限公司 | User determination method and device |
| CN113362097B (en) * | 2020-03-06 | 2023-11-07 | 北京京东振世信息技术有限公司 | User determination method and device |
| CN111798265A (en) * | 2020-05-27 | 2020-10-20 | 北京国电通网络技术有限公司 | Accurate marketing method and device suitable for enterprise users |
| CN111784385A (en) * | 2020-06-19 | 2020-10-16 | 杭州未名信科科技有限公司 | Manufacturing industry-oriented client portrait construction method and device and computer storage medium |
| CN111815173A (en) * | 2020-07-10 | 2020-10-23 | 东软集团（上海）有限公司 | Enterprise portrait assessment method based on association rule |
| WO2022016561A1 (en) * | 2020-07-22 | 2022-01-27 | 江苏宏创信息科技有限公司 | Ai modeling system and method for policy profiling based on big data |
| CN111966904A (en) * | 2020-08-18 | 2020-11-20 | 平安国际智慧城市科技股份有限公司 | Information recommendation method based on multi-user portrait model and related device |
| CN111966904B (en) * | 2020-08-18 | 2023-09-05 | 深圳平安智慧医健科技有限公司 | Information recommendation method and related device based on multi-user portrait model |
| CN112269778A (en) * | 2020-10-15 | 2021-01-26 | 西安工程大学 | Equipment fault diagnosis method |
| CN112580332A (en) * | 2020-11-19 | 2021-03-30 | 淮阴工学院 | Enterprise portrait method based on label layering and deepening modeling |
| CN112580332B (en) * | 2020-11-19 | 2022-07-12 | 淮阴工学院 | Enterprise portrait method based on label layering and deepening modeling |
| CN112446744A (en) * | 2020-12-14 | 2021-03-05 | 成都航天科工大数据研究院有限公司 | Method, system and medium for constructing enterprise portrait based on industrial product supply and demand platform |
| CN112446744B (en) * | 2020-12-14 | 2023-08-08 | 成都航天科工大数据研究院有限公司 | Method, system and medium for constructing enterprise portraits based on industrial product supply and demand platform |
| CN113065894A (en) * | 2021-03-24 | 2021-07-02 | 天天惠民(北京)智能物流科技有限公司 | Data collection method and device based on user portrait and order analysis and storage medium |
| CN113079148A (en) * | 2021-03-25 | 2021-07-06 | 恒安嘉新（北京）科技股份公司 | Industrial Internet safety monitoring method, device, equipment and storage medium |
| CN113486225A (en) * | 2021-07-06 | 2021-10-08 | 北京国联视讯信息技术股份有限公司 | Enterprise image display method and system based on big data |
| CN113486225B (en) * | 2021-07-06 | 2023-10-31 | 北京国联视讯信息技术股份有限公司 | Enterprise image display method and system based on big data |
| CN113793061A (en) * | 2021-09-27 | 2021-12-14 | 武汉众邦银行股份有限公司 | Business bank customer rating method and device integrating analytic hierarchy process (analytic hierarchy process) and RFM |
| CN114185880A (en) * | 2021-12-10 | 2022-03-15 | 北京金堤科技有限公司 | Affiliated industry data determining method and device |
| CN114238615A (en) * | 2021-12-14 | 2022-03-25 | 淄博天大创新科技服务有限公司 | Enterprise service achievement data processing method and system |
| CN116776006A (en) * | 2023-08-24 | 2023-09-19 | 中资科技(江苏)有限公司 | Customer portrait construction method and system for enterprise financing |
| CN116776006B (en) * | 2023-08-24 | 2023-10-27 | 中资科技(江苏)有限公司 | Customer portrait construction method and system for enterprise financing |
| CN117726359A (en) * | 2024-02-08 | 2024-03-19 | 成都纳宝科技有限公司 | Interactive marketing method, system and equipment |
| CN117726359B (en) * | 2024-02-08 | 2024-04-26 | 成都纳宝科技有限公司 | Interactive marketing method, system and equipment |
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