CN107133697A - Estimate method, device, equipment and the storage medium of driver's order wish - Google Patents
Estimate method, device, equipment and the storage medium of driver's order wish Download PDFInfo
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- CN107133697A CN107133697A CN201710304975.7A CN201710304975A CN107133697A CN 107133697 A CN107133697 A CN 107133697A CN 201710304975 A CN201710304975 A CN 201710304975A CN 107133697 A CN107133697 A CN 107133697A
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- 238000004422 calculation algorithm Methods 0.000 claims description 28
- 238000012549 training Methods 0.000 claims description 14
- 238000010801 machine learning Methods 0.000 claims description 12
- 238000007637 random forest analysis Methods 0.000 claims description 12
- 238000003066 decision tree Methods 0.000 claims description 11
- 238000012706 support-vector machine Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 3
- 238000012545 processing Methods 0.000 description 10
- 238000004891 communication Methods 0.000 description 6
- 230000000977 initiatory effect Effects 0.000 description 6
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- 230000006870 function Effects 0.000 description 5
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- 230000003287 optical effect Effects 0.000 description 4
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- 230000006399 behavior Effects 0.000 description 2
- 239000003795 chemical substances by application Substances 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 230000001133 acceleration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
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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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
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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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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Abstract
The embodiment of the invention discloses a kind of method for estimating driver's order wish, device, equipment and storage medium.The method for estimating driver's order wish includes：Sequence information is determined according to the order that online taxi service platform is received；The sequence information is inputted into the corresponding driver's order wish prediction model of the first driver, and obtains order wish of first driver for the order.The embodiment of the present invention is by the way that sequence information is inputted in the corresponding order wish prediction model of the first driver, obtain order wish of first driver for order, it so not only can correctly identify the driver for being ready order, lift online dial-a-cab success rate, and related personnel or online taxi service platform is understood the order wish situation of each driver, it is easy to be managed driver.
Description
Technical field
The present embodiments relate to Internet technical field, more particularly to a kind of method for estimating driver's order wish, dress
Put, equipment and storage medium.
Background technology
With the high development and the popularization of smart machine of Internet technology, traditional traffic technique is progressively evolved
For intelligent transportation system.In the prior art, (drop, excellent step, Divine Land, Yi Dao are for example dripped using online dial-a-cab software more than passenger
Deng), called a taxi, made one, car, the interaction relationship between road are presented in new ways by intelligent terminals such as mobile phones, with
Traditional mode of calling a taxi is compared, and realizes more accurately and efficiently go on a journey to a certain extent.
And in online dial-a-cab, different driver's order wish difference is huge.Online dial-a-cab provider often becomes
To in keeping the high driver of order wish by various means.Meanwhile, it is necessary to which order is sent with charge free as far as possible during distribute leaflets
The driver high to order wish, promotes successfully chauffeur.Therefore, how to evaluate the order wish of driver has to online dial-a-cab
Significance.
At present, the order wish of driver is mainly evaluated by some simple indexs, for example, pushes away single order ratio, Si Ji
Line duration, order amount and completion order amount of money etc..It is high to the discrimination of driver and the above method has very big randomness,
With similar order than driver may order wish difference it is huge.The driver for example having is intended near Large-sized Communication hinge
Order, order rate is very high, but but very low in non-hot region order wish.If simply evaluating department using order rate
Machine order wish, can produce very large deviation.
The content of the invention
The embodiment of the present invention provides a kind of method for estimating driver's order wish, device, equipment and storage medium, Ke Yizheng
The driver for being ready order is really identified, online dial-a-cab success rate is lifted.
In a first aspect, the embodiments of the invention provide a kind of method for estimating driver's order wish, this method includes：
Sequence information is determined according to the order that online taxi service platform is received；
The sequence information is inputted into the corresponding driver's order wish prediction model of first driver, and obtains described the
Order wish of one driver for the order.
Second aspect, the embodiment of the present invention additionally provides a kind of device for estimating driver's order wish, and the device includes：
Sequence information determining module, the order for being received according to online taxi service platform determines sequence information；
Order wish determining module, is estimated for the sequence information to be inputted into the corresponding driver's order wish of the first driver
Model, and obtain order wish of first driver for the order.
The third aspect, the embodiment of the present invention additionally provides a kind of equipment, including：
One or more processors；
Storage device, for storing one or more programs,
When one or more of programs are by one or more of computing devices so that one or more of processing
Device realizes any described method for estimating driver's order wish of the embodiment of the present invention.
Fourth aspect, the embodiment of the present invention additionally provides a kind of computer-readable recording medium, is stored thereon with computer
Program, the program realizes any described method for estimating driver's order wish of the embodiment of the present invention when being executed by processor.
The embodiment of the present invention obtains the by the way that sequence information is inputted in the corresponding order wish prediction model of the first driver
One driver so not only can correctly identify the driver for being ready order for the order wish of order, lift online chauffeur clothes
It is engaged in success rate, and related personnel or online taxi service platform is understood the order wish situation of each driver, is easy to pair
Driver is managed.
Brief description of the drawings
Fig. 1 is a kind of flow chart for method for estimating driver's order wish that the embodiment of the present invention one is provided；
Fig. 2 is a kind of flow chart for method for estimating driver's order wish that the embodiment of the present invention two is provided；
Fig. 3 is a kind of structure chart for device for estimating driver's order wish that the embodiment of the present invention three is provided；
Fig. 4 is a kind of structural representation for computer equipment that the embodiment of the present invention four is provided.
Embodiment
In order that the object, technical solutions and advantages of the present invention are clearer, below in conjunction with the accompanying drawings to specific reality of the invention
Example is applied to be described in further detail.It is understood that specific embodiment described herein is used only for explaining the present invention,
Rather than limitation of the invention.
It also should be noted that, for the ease of description, illustrate only in accompanying drawing part related to the present invention rather than
Full content.It should be mentioned that some exemplary embodiments are described before exemplary embodiment is discussed in greater detail
Into the processing or method described as flow chart.Although operations (or step) are described as the processing of order by flow chart,
It is that many of which operation can be by concurrently, concomitantly or while implement.In addition, the order of operations can be by again
Arrange.The processing can be terminated when its operations are completed, it is also possible to the additional step being not included in accompanying drawing.
The processing can correspond to method, function, code, subroutine, subprogram etc..
Embodiment one
Fig. 1 is a kind of flow chart for method for estimating driver's order wish that the embodiment of the present invention one is provided, the present embodiment
It is applicable to estimate the situation of driver's order wish, this method can estimate driver's order wish by provided in an embodiment of the present invention
Device perform, the device can be realized by the way of software and/or hardware, and the device can be integrated in terminal device or eventually
In the application end of end equipment.Wherein, terminal device can be but be not limited to mobile terminal (tablet personal computer or smart mobile phone), consolidate
Determine terminal (desktop computer or notebook).
Wherein, application end can be the plug-in unit for some client being embedded in terminal device, or be set for the terminal
The plug-in unit of standby operating system, with the behaviour for estimating driver's order wish client or terminal device being embedded in terminal device
The driver's order wish application program of estimating made in system is used cooperatively；Application end can also be for one in the terminal device solely
Vertical provides the client for estimating driver's order wish client, and the present embodiment is not limited to this.
As described in Figure 1, the method for the present embodiment is specifically included：
S101, the order received according to online taxi service platform determine sequence information.
Wherein, online taxi service platform can be server, be specifically as follows the server called a taxi of drop drop, excellent step and call a taxi
Server, the server called a taxi of the server hired a car of Divine Land or easy road etc..Accordingly, it is corresponding with line taxi service platform
Client corresponds to driver's client and chauffeur client, and wherein driver's client is being used in driver terminal equipment
The client of order, for example, correspond to drop drop call a taxi driver's client, Divine Land of driver's client, excellent step of calling a taxi and hire a car driver visitor
Hu Duanhuoyi calls a taxi in road driver's client etc..Chauffeur client is the client for chauffeur in subscriber terminal equipment
End, for example, correspond to drop drop call a taxi chauffeur client, Divine Land of chauffeur client, excellent step of calling a taxi and hire a car chauffeur client or easy road is beaten
Car chauffeur client etc..
The executive agent of the present embodiment be specifically as follows any one or more：Online taxi service platform, driver
Client, the device provided in an embodiment of the present invention for estimating driver's order wish.
Specifically, when executive agent is driver's client, the embodiment of this step is as follows：During the useful car demand of user
Order request is initiated to online taxi service platform by chauffeur client, online taxi service platform receives order request
Afterwards, corresponding order is sent to the client of one or more drivers.For ease of subsequent descriptions, in the present embodiment, preferably
To send client corresponding to the first driver.
S102, the sequence information is inputted to the corresponding driver's order wish prediction model of the first driver, and obtain described
Order wish of first driver for the order.
Specifically, for each driver of online taxi service platform each self-corresponding driver's order meaning can be set up respectively in advance
It is willing to prediction model.In the present embodiment, driver's order wish prediction model is that the corresponding driver's order wish of the first driver is pre-
Estimate model, when the client of the first driver receives order, the sequence information of the order is inputted into the corresponding department of the first driver
Machine order wish prediction model, its output result can be order wish probability, and its probability is bigger, and just explanation driver's order is general
Rate is higher.It is of course also possible to which the sequence information is inputted into the corresponding driver's order wish prediction model of other drivers, and obtain
To order wish of other drivers for the order, specifically can by online taxi service platform service provider according to demand, choosing
The driver wanted to know about is selected, for example, the second driver, inputs the corresponding driver's order wish of the second driver pre- by the sequence information
Estimate model, and obtain second driver for order wish of the order, etc..
Wherein, at least one of following information can be included in the sequence information：By bus starting point, by bus terminal, by bus starting point
And/or by bus terminal whether be user home address, by bus starting point and/or by bus terminal whether be user work unit,
By bus starting point and/or by bus terminal whether be commercial circle, by bus starting point and/or by bus terminal whether be transport hub, order initiate
City, order initiate the time, type of vehicle, by bus starting point and by bus the distance between terminal, anticipated price, anticipated price with ordering
Order is averaged in Order average price ratio, predicted travel time, predicted travel speed and order initiation city in single-shot city
Travel speed ratio, whether pass through congestion regions and user's sex.Wherein, the order initiation time includes at least one of following letter
Breath：Whether the morning, whether afternoon, whether evening, whether night, week, hour and whether weekend.
The present embodiment obtains the first department by the way that sequence information is inputted in the corresponding order wish prediction model of the first driver
Machine so not only can correctly identify the driver for being ready order for the order wish of order, lifted online dial-a-cab into
Power, and related personnel or online taxi service platform is understood the order wish situation of each driver, it is easy to driver
It is managed.For example, when system sends order with charge free, order wish high driver will be shipped to order more, can so keep one here
A little good drivers, eliminate the low driver of some order wishes.
Embodiment two
Fig. 2 is a kind of flow chart for method for estimating driver's order wish that the embodiment of the present invention two is provided.The present embodiment
Optimized, in the present embodiment, the corresponding driver's order wish of first driver is estimated based on above-described embodiment
Model is obtained preferably by following manner：Obtain driver information, the History Order of first driver of first driver
Information；The corresponding driver's order wish of first driver is set up according to the driver information and History Order information and estimates mould
Type.
Accordingly, the method for the present embodiment is specifically included：
S201, driver information, the History Order information of the first driver for obtaining the first driver.
Wherein, the driver information can include driver's location dependent information and/or driver's historical information.Wherein, the department
Machine location dependent information can include at least one of following information：Current translational speed, current moving state duration, present bit
Put, prostitution operating range, expected prostitution running time and expected prostitution average overall travel speed.Wherein, driver's historical information
At least one of following information can be included：It is the ratio for the prostitution operating range average that prostitution operating range and driver have received orders, pre-
In prostitution traveling average time ratio that phase prostitution running time and driver have received orders, preset time period push away single order ratio,
Average online hours in driver's preset time period initiate average online in all driver's preset time periods in city with order
The default quantile of online hours and order initiate all driver's preset times in city in duration ratio, driver's preset time period
The ratio of identical default quantile average of online hours in section, in driver's preset time period averagely push away single number and order initiation
Single number ratio is averagely pushed away in city in all driver's preset time periods, average order number of times and order hair in driver's preset time period
Play all driver's preset time periods in city single number is inscribed and accounted for than the mobile status time in track in, driver's preset time period
All driver's preset time periods in city are initiated than the mobile status time accounting and order in track in, driver's preset time period
The ratio of mobile status time accounting average in interior track.
, can be by starting point by bus and the position of terminal is converted into regional code by bus for the ease of subsequent treatment, change into area
The mode of domain coding has a variety of, is not specifically limited in the present embodiment, for example, can be GeoHash transfer algorithms, can also
It is the block that the shapes such as rectangle or hexagon are divided into according to longitude and latitude, then assigns different id to different blocks respectively
Or coding.
Wherein, the history that History Order information can receive for driver's client of the first driver in preset time period
The History Order of the sequence information of order, such as January.Or, it is driver's client of the first driver in preset geographical position
In the range of History Order, for example, in the History Order that can be received from driver's client of the first driver randomly choose one
Standby History Order, according to the driver position included in the standby History Order, is received from driver's client of the first driver
History Order in choose be located at the driver position pre-determined distance scope (for example, 500 meters) in order as History Order, and
Include standby History Order.
Comprising having connect History Order and/or do not connect History Order in the History Order of acquisition.Wherein, in History Order information
At least one of following information can be included：Order situation, by bus starting point, by bus terminal, by bus starting point and/or by bus terminal whether be
The home address of user, by bus starting point and/or by bus terminal whether be user work unit, by bus starting point and/or by bus eventually
Whether point is commercial circle, starting point of riding and/or whether terminal is transport hub, order initiation city, order initiation time, car by bus
Type, by bus starting point and by bus the distance between terminal, anticipated price, anticipated price and order are initiated order in city and are averaged
Whether price ratio, predicted travel time, predicted travel speed and order initiate order average overall travel speed ratio in city, pass through and gather around
Stifled region and user's sex.Wherein, the order initiation time includes at least one of following information：Whether the morning, whether afternoon,
Whether evening, whether night, week, hour and whether weekend.
S202, the corresponding driver's order wish of first driver is set up according to the driver information and History Order information
Prediction model.
A kind of optional embodiment of this step is that the History Order information includes connecing for each History Order
One-state；Each History Order is marked according to the order situation；Use the History Order after mark and the driver
Information is used as training data；And the training data is trained using machine learning method, obtain the first driver corresponding
Driver's order wish prediction model.
Wherein, order situation includes driver's order and the non-order of driver, for every History Order of the first driver, according to
History Order is marked first driver's order situation, and the sequence information of the History Order after mark and driver information are made
For training data.For example, for certain History Order, if first driver's order, marking the state of the History Order for
Order (for example, labeled as 1), if the non-order of the first driver, the state for marking the History Order is non-order (for example, mark
It is designated as 0).The History Order information and driver information of the substantial amounts of mark of the first driver can be thus obtained, and as instruction
Practice data, and training data is trained using machine learning method, obtain the corresponding driver's order wish of the first driver pre-
Estimate model.
Wherein, it can be used to lower at least one algorithm：Decision Tree algorithms, random forest Random Forest algorithms, iteration are determined
Plan tree GBDT algorithms and algorithm of support vector machine.
S203, the order received according to online taxi service platform determine sequence information.
S204, the sequence information is inputted to the corresponding driver's order wish prediction model of the first driver, and obtain described
Order wish of first driver for the order.
The present embodiment is built by the driver information of the first driver previously according to acquisition, the History Order information of the first driver
Found the corresponding driver's order wish prediction model of first driver.Then the driver of the driver of input first of sequence information is connect
Single wish prediction model, and then the order wish of the first driver is determined, the driver for being ready order not only can be correctly identified, is carried
Rise online dial-a-cab success rate, and related personnel or online taxi service platform is understood the order wish of each driver
Situation, is easy to be managed driver.For example, when system sends order with charge free, order wish high driver being shipped to order more,
Some good drivers can so be kept here, the low driver of some order wishes is eliminated.
Embodiment three
Fig. 3 is a kind of structure chart for device for estimating driver's order wish that the embodiment of the present invention three is provided.The present embodiment
It is applicable to estimate the situation of driver's order wish, the device can realize that the device can collect by the way of software and/or hardware
Into in terminal device or in the application end of terminal device.Wherein, terminal device can be but be not limited to mobile terminal (flat board
Computer or smart mobile phone), fixed terminal (desktop computer or notebook).
Wherein, application end can be the plug-in unit for some client being embedded in terminal device, or be set for the terminal
The plug-in unit of standby operating system, with the behaviour for estimating driver's order wish client or terminal device being embedded in terminal device
The driver's order wish application program of estimating made in system is used cooperatively；Application end can also be for one in the terminal device solely
Vertical provides the client for estimating driver's order wish client, and the present embodiment is not limited to this.
As shown in figure 3, described device includes：Order reception module 301 and order wish determining module 302, wherein：
The order that sequence information determining module 301 is used to be received according to online taxi service platform determines sequence information；
Order wish determining module 302 is used for the corresponding driver's order wish of the sequence information the first driver of input is pre-
Estimate model, and obtain order wish of first driver for the order.
Driver's order of estimating that the device for estimating driver's order wish of the present embodiment is used to perform the various embodiments described above is anticipated
The method of hope, its technical principle is similar with the technique effect produced, repeats no more here.
On the basis of the various embodiments described above, described device also includes：Driver information acquisition module 303 and model set up mould
Block 304；
Driver information acquisition module 303 is used for driver information, the history of first driver for obtaining first driver
Sequence information；
Model building module 304 is used to set up the first driver correspondence according to the driver information and History Order information
Driver's order wish prediction model.
On the basis of the various embodiments described above, the model building module 304 specifically for：
The History Order information includes the order situation for each History Order；According to the order situation to every
Individual History Order is marked；Training data is used as using the History Order after mark and the driver information；And use machine
Learning method is trained to the training data, obtains the corresponding driver's order wish prediction model of the first driver.
On the basis of the various embodiments described above, the machine learning method includes the one or more in following algorithm：
Decision Tree algorithms, random forest Random Forest algorithms, iteration decision tree GBDT algorithms and SVMs are calculated
Method.
The device for driver's order wish that what the various embodiments described above were provided estimate can perform any embodiment of the present invention and be carried
The method for estimating driver's order wish supplied, possesses to perform and estimates the corresponding functional module of method of driver's order wish and beneficial
Effect.
Example IV
Fig. 4 is a kind of structural representation for equipment that the embodiment of the present invention four is provided.Fig. 4 is shown suitable for being used for realizing this
The block diagram of the exemplary computer device 12 of invention embodiment.The computer equipment 12 that Fig. 4 is shown is only an example, no
Tackle the function of the embodiment of the present invention and carry out any limitation using range band.
As shown in figure 4, computer equipment 12 is showed in the form of universal computing device.The component of computer equipment 12 can be with
Including but not limited to：One or more processor or processing unit 16, system storage 28 connect different system component
The bus 18 of (including system storage 28 and processing unit 16).
Bus 18 represents the one or more in a few class bus structures, including memory bus or Memory Controller,
Peripheral bus, graphics acceleration port, processor or the local bus using any bus structures in a variety of bus structures.Lift
For example, these architectures include but is not limited to industry standard architecture (ISA) bus, MCA (MAC)
Bus, enhanced isa bus, VESA's (VESA) local bus and periphery component interconnection (PCI) bus.
Computer equipment 12 typically comprises various computing systems computer-readable recording medium.These media can be it is any can be by
The usable medium that computer equipment 12 is accessed, including volatibility and non-volatile media, moveable and immovable medium.
System storage 28 can include the computer system readable media of form of volatile memory, such as arbitrary access
Memory (RAM) 30 and/or cache memory 32.Computer equipment 12 may further include it is other it is removable/can not
Mobile, volatile/non-volatile computer system storage medium.Only as an example, storage system 34 can be used for read-write not
Movably, non-volatile magnetic media (Fig. 4 is not shown, is commonly referred to as " hard disk drive ").Although not shown in Fig. 4, can with
There is provided for the disc driver to may move non-volatile magnetic disk (such as " floppy disk ") read-write, and to removable non-volatile
The CD drive of CD (such as CD-ROM, DVD-ROM or other optical mediums) read-write.In these cases, each driving
Device can be connected by one or more data media interfaces with bus 18.Memory 28 can include the production of at least one program
Product, the program product has one group of (for example, at least one) program module, and these program modules are configured to perform of the invention each
The function of embodiment.
Program/utility 40 with one group of (at least one) program module 42, can be stored in such as memory 28
In, such program module 42 includes --- but being not limited to --- operating system, one or more application program, other programs
The realization of network environment is potentially included in each or certain combination in module and routine data, these examples.Program mould
Block 42 generally performs function and/or method in embodiment described in the invention.
Computer equipment 12 can also be with one or more external equipments 14 (such as keyboard, sensing equipment, display 24
Deng) communication, the equipment communication interacted with the computer equipment 12 can be also enabled a user to one or more, and/or with making
Obtain any equipment (such as network interface card, modulatedemodulate that the computer equipment 12 can be communicated with one or more of the other computing device
Adjust device etc.) communication.This communication can be carried out by input/output (I/O) interface 22.Also, computer equipment 12 may be used also
To pass through network adapter 20 and one or more network (such as LAN (LAN), wide area network (WAN) and/or public network
Network, such as internet) communication.As illustrated, network adapter 20 is led to by other modules of bus 18 and computer equipment 12
Letter.It should be understood that although not shown in the drawings, can combine computer equipment 12 use other hardware and/or software module, including
But it is not limited to：Microcode, device driver, redundant processing unit, external disk drive array, RAID system, tape drive
And data backup storage system etc..
Processing unit 16 is stored in program in system storage 28 by operation, thus perform various function application and
Data processing, for example, realize the method for estimating driver's order wish that the embodiment of the present invention is provided：
Sequence information is determined according to the order that online taxi service platform is received；
The sequence information is inputted into the corresponding driver's order wish prediction model of the first driver, and obtains first department
Order wish of the machine for the order.
Further, the corresponding driver's order wish prediction model of first driver is obtained in the following way：
Obtain driver information, the History Order information of first driver of first driver；
The corresponding driver's order wish of first driver is set up according to the driver information and History Order information to estimate
Model.
Further, it is described that the corresponding driver of first driver is set up according to the driver information and History Order information
Order wish prediction model, including：
The History Order information includes the order situation for each History Order；
Each History Order is marked according to the order situation；
Training data is used as using the History Order after mark and the driver information；
And the training data is trained using machine learning method, obtain the corresponding driver's order meaning of the first driver
It is willing to prediction model.
Further, the machine learning method includes the one or more in following algorithm：
Decision Tree algorithms, random forest Random Forest algorithms, iteration decision tree GBDT algorithms and SVMs are calculated
Method.
Embodiment five
The embodiment of the present invention 5 additionally provides a kind of computer-readable recording medium, is stored thereon with computer program, the journey
The method for estimating driver's order wish provided such as all inventive embodiments of the application is provided when sequence is executed by processor：
Sequence information is determined according to the order that online taxi service platform is received；
The sequence information is inputted into the corresponding driver's order wish prediction model of the first driver, and obtains first department
Order wish of the machine for the order.
Further, the corresponding driver's order wish prediction model of first driver is obtained in the following way：
Obtain driver information, the History Order information of first driver of first driver；
The corresponding driver's order wish of first driver is set up according to the driver information and History Order information to estimate
Model.
Further, it is described that the corresponding driver of first driver is set up according to the driver information and History Order information
Order wish prediction model, including：
The History Order information includes the order situation for each History Order；
Each History Order is marked according to the order situation；
Training data is used as using the History Order after mark and the driver information；
And the training data is trained using machine learning method, obtain the corresponding driver's order meaning of the first driver
It is willing to prediction model.
Further, the machine learning method includes the one or more in following algorithm：
Decision Tree algorithms, random forest Random Forest algorithms, iteration decision tree GBDT algorithms and SVMs are calculated
Method.
The computer-readable storage medium of the embodiment of the present invention, can be using any of one or more computer-readable media
Combination.Computer-readable medium can be computer-readable signal media or computer-readable recording medium.It is computer-readable
Storage medium for example may be-but not limited to-the system of electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor, device or
Device, or any combination above.The more specifically example (non exhaustive list) of computer-readable recording medium includes：Tool
There are the electrical connections of one or more wires, portable computer diskette, hard disk, random access memory (RAM), read-only storage
(ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read-only storage (CD-
ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.In this document, computer-readable storage
Medium can be it is any include or storage program tangible medium, the program can be commanded execution system, device or device
Using or it is in connection.
Computer-readable signal media can be included in a base band or as the data-signal of carrier wave part propagation,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including but not limit
In electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be that computer can
Any computer-readable medium beyond storage medium is read, the computer-readable medium, which can send, propagates or transmit, to be used for
Used by instruction execution system, device or device or program in connection.
The program code included on computer-readable medium can be transmitted with any appropriate medium, including --- but do not limit
In wireless, electric wire, optical cable, RF etc., or above-mentioned any appropriate combination.
It can be write with one or more programming languages or its combination for performing the computer that the present invention is operated
Program code, described program design language includes object oriented program language-such as Java, Smalltalk, C++,
Also including conventional procedural programming language-such as " C " language or similar programming language.Program code can be with
Fully perform, partly perform on the user computer on the user computer, as independent software kit execution, a portion
Divide part execution or the execution completely on remote computer or server on the remote computer on the user computer.
Be related in the situation of remote computer, remote computer can be by the network of any kind --- including LAN (LAN) or
Wide area network (WAN)-be connected to subscriber computer, or, it may be connected to outer computer (is for example carried using Internet service
Come for business by Internet connection).
Note, above are only presently preferred embodiments of the present invention and institute's application technology principle.It will be appreciated by those skilled in the art that
The invention is not restricted to specific embodiment described here, can carry out for a person skilled in the art it is various it is obvious change,
Readjust and substitute without departing from protection scope of the present invention.Therefore, although the present invention is carried out by above example
It is described in further detail, but the present invention is not limited only to above example, without departing from the inventive concept, also
Other more equivalent embodiments can be included, and the scope of the present invention is determined by scope of the appended claims.
Claims (10)
1. a kind of method for estimating driver's order wish, it is characterised in that including：
Sequence information is determined according to the order that online taxi service platform is received；
The sequence information is inputted into the corresponding driver's order wish prediction model of the first driver, and obtains first driver couple
In the order wish of the order.
2. according to the method described in claim 1, it is characterised in that the corresponding driver's order wish of first driver estimates mould
Type is obtained in the following way：
Obtain driver information, the History Order information of first driver of first driver；
The corresponding driver's order wish prediction model of first driver is set up according to the driver information and History Order information.
3. method according to claim 2, it is characterised in that described to be built according to the driver information and History Order information
The corresponding driver's order wish prediction model of first driver is found, including：
The History Order information includes the order situation for each History Order；
Each History Order is marked according to the order situation；
Training data is used as using the History Order after mark and the driver information；
And the training data is trained using machine learning method, obtain the corresponding driver's order wish of the first driver pre-
Estimate model.
4. method according to claim 3, it is characterised in that the machine learning method includes one kind in following algorithm
Or it is a variety of：
Decision Tree algorithms, random forest Random Forest algorithms, iteration decision tree GBDT algorithms and algorithm of support vector machine.
5. a kind of device for estimating driver's order wish, it is characterised in that including：
Sequence information determining module, the order for being received according to online taxi service platform determines sequence information；
Order wish determining module, mould is estimated for the sequence information to be inputted into the corresponding driver's order wish of the first driver
Type, and obtain order wish of first driver for the order.
6. device according to claim 5, it is characterised in that described device also includes：
Driver information acquisition module, driver information, the History Order of first driver letter for obtaining first driver
Breath；
Model building module, for setting up the corresponding driver of first driver according to the driver information and History Order information
Order wish prediction model.
7. device according to claim 6, it is characterised in that the model building module specifically for：
The History Order information includes the order situation for each History Order；Gone through according to the order situation to each
History order is marked；Training data is used as using the History Order after mark and the driver information；And use machine learning
Method is trained to the training data, obtains the corresponding driver's order wish prediction model of the first driver.
8. device according to claim 7, it is characterised in that the machine learning method includes one kind in following algorithm
Or it is a variety of：
Decision Tree algorithms, random forest Random Forest algorithms, iteration decision tree GBDT algorithms and algorithm of support vector machine.
9. a kind of equipment, it is characterised in that the equipment includes：
One or more processors；
Storage device, for storing one or more programs,
When one or more of programs are by one or more of computing devices so that one or more of processors are real
The existing method for estimating driver's order wish as described in any in claim 1-4.
10. a kind of computer-readable recording medium, is stored thereon with computer program, it is characterised in that the program is by processor
The method for estimating driver's order wish as described in any in claim 1-4 is realized during execution.
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| CN201710304975.7A CN107133697A (en) | 2017-05-03 | 2017-05-03 | Estimate method, device, equipment and the storage medium of driver's order wish |
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| CN113554387A (en) * | 2021-06-28 | 2021-10-26 | 杭州拼便宜网络科技有限公司 | Driver preference-based e-commerce logistics order allocation method, device, equipment and storage medium |
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