CN115984002B - Data processing method and device for vehicle transaction management - Google Patents
Data processing method and device for vehicle transaction management Download PDFInfo
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Abstract
The application discloses a data processing method and device for vehicle transaction management. Comprising the following steps: acquiring service request data; carrying out service embedded point processing based on service characteristics on service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedded point processing; carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data; and determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data. After data processing based on service embedded points is carried out on service request data, the data generated by the service request are updated to vehicle link data; by carrying out service prediction processing on the vehicle link data, a service prediction result is obtained, unified management of collection, analysis and pushing of the vehicle transaction process data is realized, and the technical effect of improving the vehicle transaction efficiency is realized.
Description
Technical Field
The present application relates to the field of internet, and in particular, to a data processing method and apparatus for vehicle transaction management.
Background
As demand for vehicles increases, vehicle traffic increases and second hand traffic increases. In the second-hand vehicle industry, vehicles buy vehicles from auctions to merchants, and the vehicles need to carry out subsequent operations such as passing home, certificate handling and the like. For a company conducting a second-hand car auction, it is necessary to provide services and sites for the auction, pass, and license for the merchant, and it is necessary to manage data of each flow of the car. In the prior art, only a single process in a vehicle transaction flow can be managed, systematic management of data of each flow is lacked, and the data of the whole transaction flow is difficult to manage, so that the efficiency of obtaining vehicle information of each flow is lower, and the transaction efficiency is affected.
Therefore, the transaction efficiency of the second-hand cart transaction process in the prior art is low.
Disclosure of Invention
The main aim of the application is to provide a data processing method for vehicle transaction management, so as to solve the problem of lower transaction efficiency in the process of vehicle transaction of a second-hand vehicle in the prior art, and realize the technical effect of improving the vehicle transaction efficiency.
To achieve the above object, a first aspect of the present application proposes a data processing method for vehicle transaction management, including:
acquiring service request data, wherein the service request data is data for representing a request service in a vehicle transaction process;
carrying out service embedded point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedded point processing;
carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data, wherein the service prediction data is used for representing the service data in a predicted vehicle transaction link;
and determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data.
In some optional embodiments of the present application, performing service embedded point processing based on service features on the service request data, to obtain vehicle link data includes:
performing recognition processing based on first service characteristics on the service request data to obtain first service characteristic data, wherein the first service characteristic data is data for representing service characteristics corresponding to the service request data;
the service request data is subjected to identification processing based on vehicle identification to obtain first vehicle identification data, wherein the first vehicle identification data is data for representing the vehicle identification corresponding to the service request data;
and updating the preset service link data according to the first vehicle identification data and the first service characteristic data to obtain the vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the first service is updated by the vehicle corresponding to the first vehicle identification.
In some optional embodiments of the present application, performing service prediction processing on the vehicle link data based on a preset service prediction model, and obtaining service prediction data includes:
performing recognition processing based on second service characteristics on the vehicle link data to obtain second service characteristic data, wherein the second service characteristic data is characteristic data corresponding to prediction service in the vehicle link data;
matching a prediction model corresponding to the second service characteristic in a preset service prediction model database to obtain preset service prediction model data;
and carrying out service prediction processing based on a second service characteristic on the vehicle link data based on the preset service prediction model data to obtain the service prediction data.
In some alternative embodiments of the present application, determining transaction hint data from the traffic prediction data and the vehicle link data and outputting the transaction hint data includes:
the service prediction data and the vehicle link data are subjected to identification processing of recommended features to obtain a plurality of recommended feature data, wherein the recommended feature data are feature data used for representing pushing of the recommended data in the vehicle transaction process;
recommendation calculation processing based on a preset recommendation algorithm model is respectively carried out on the plurality of recommendation characteristic data to obtain a plurality of recommendation coefficient data, wherein the plurality of recommendation coefficient data are respectively used for representing recommendation coefficients corresponding to a plurality of recommendation characteristics;
and screening the plurality of recommendation coefficient data based on a preset recommendation rule to obtain the transaction prompt data, wherein the transaction prompt data comprises the service prediction data and service data corresponding to a plurality of recommendation coefficients meeting a preset recommendation threshold in the vehicle link data.
In some optional embodiments of the present application, after performing service embedded point processing based on service features on the service request data to obtain vehicle link data, the data processing method further includes:
carrying out recognition processing based on a link flow on the vehicle link data to obtain link flow characteristic data, wherein the link flow characteristic data is characteristic data used for representing a flow in the vehicle link data;
comparing the link flow characteristic data with preset link flow characteristic data to judge whether the link flow corresponding to the link flow characteristic data meets preset link flow rules,
if the link flow corresponding to the link flow characteristic data meets a preset link flow rule, obtaining the vehicle link data;
and if the link flow corresponding to the link flow characteristic data does not meet the preset link flow rule, outputting link abnormality prompt information.
In some optional embodiments of the present application, after determining transaction hint data from the traffic prediction data and the vehicle link data and outputting the transaction hint data, the data processing method further comprises:
acquiring service query request data, wherein the service query request data is data for representing a request query service;
carrying out identification processing based on identity characteristics on the service query request data to obtain query identity characteristic data;
performing recognition processing based on service characteristics on the service query request data to obtain query service characteristic data;
and matching the service data corresponding to the query identity characteristic data and the query service characteristic data in a preset system database to obtain target query data.
According to a second aspect of the present application there is provided a data processing apparatus for vehicle transaction management, comprising:
the system comprises a data acquisition module, a service request module and a service request module, wherein the data acquisition module is used for acquiring service request data, wherein the service request data is data for representing a request service in a vehicle transaction process;
the service embedding point module is used for carrying out service embedding point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedding point processing;
the business prediction module is used for carrying out business prediction processing on the vehicle link data based on a preset business prediction model to obtain business prediction data, wherein the business prediction data is used for representing the business data in a predicted vehicle transaction link;
and the prompt output module is used for determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data.
In some optional embodiments of the present application, the service burial point module includes:
the first service identification module is used for carrying out identification processing based on first service characteristics on the service request data to obtain first service characteristic data, wherein the first service characteristic data is data for representing service characteristics corresponding to the service request data;
the vehicle identification module is used for carrying out identification processing based on vehicle identification on the service request data to obtain first vehicle identification data, wherein the first vehicle identification data is data for representing the vehicle identification corresponding to the service request data;
and the link updating module is used for updating the preset service link data according to the first vehicle identification data and the first service characteristic data to obtain the vehicle link data, wherein the vehicle link data is data used for representing a vehicle transaction link after the vehicle corresponding to the first vehicle identification updates the first service.
According to a third aspect of the present application, there is provided a computer-readable storage medium storing computer instructions for causing the computer to execute the above-described data processing method for vehicle transaction management.
According to a fourth aspect of the present application, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to cause the at least one processor to perform the data processing method for vehicle transaction management described above.
The technical scheme provided by the embodiment of the application can comprise the following beneficial effects:
in the application, service request data is acquired, wherein the service request data is data for representing a request service in a vehicle transaction process; carrying out service embedded point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedded point processing; carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data, wherein the service prediction data is used for representing the service data in a predicted vehicle transaction link; and determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data. After data processing based on service burial points is carried out on service request data, the data generated by the service request are updated to vehicle link data, unified management of all node data in the vehicle transaction process is achieved, service prediction results are obtained through service prediction processing on the vehicle link data, and are output, management of all node data and service prediction in the vehicle transaction process are completed, data acquisition, analysis and pushing in the vehicle transaction process are achieved, the problem that the efficiency of second-hand vehicle transaction is low in the prior art is solved, and the technical effect of improving the vehicle transaction efficiency is achieved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, are included to provide a further understanding of the application and to provide a further understanding of the application with regard to the other features, objects and advantages of the application. The drawings of the illustrative embodiments of the present application and their descriptions are for the purpose of illustrating the present application and are not to be construed as unduly limiting the present application. In the drawings:
FIG. 1 is a flow chart of a data processing method for vehicle transaction management provided herein;
FIG. 2 is a flow chart of a data processing method for vehicle transaction management provided herein;
FIG. 3 is a flow chart of a data processing method for vehicle transaction management provided herein;
FIG. 4 is a flow chart of a data processing method for vehicle transaction management provided herein;
FIG. 5 is a schematic diagram of a data processing apparatus for vehicle transaction management provided herein;
fig. 6 is a schematic diagram of another data processing apparatus for vehicle transaction management provided herein.
Detailed Description
In order to make the present application solution better understood by those skilled in the art, the following description will be made in detail and with reference to the accompanying drawings in the embodiments of the present application, it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, shall fall within the scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of the present application and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate in order to describe the embodiments of the present application described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In the present application, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal" and the like indicate an azimuth or a positional relationship based on that shown in the drawings. These terms are used primarily to better describe the present application and its embodiments and are not intended to limit the indicated device, element or component to a particular orientation or to be constructed and operated in a particular orientation.
Also, some of the terms described above may be used to indicate other meanings in addition to orientation or positional relationships, for example, the term "upper" may also be used to indicate some sort of attachment or connection in some cases. The specific meaning of these terms in this application will be understood by those of ordinary skill in the art as appropriate.
Furthermore, the terms "mounted," "configured," "provided," "connected," "coupled," and "sleeved" are to be construed broadly. For example, "connected" may be in a fixed connection, a removable connection, or a unitary construction; may be a mechanical connection, or an electrical connection; may be directly connected, or indirectly connected through intervening media, or may be in internal communication between two devices, elements, or components. The specific meaning of the terms in this application will be understood by those of ordinary skill in the art as the case may be.
In the second-hand vehicle industry, the second-hand vehicle transaction process comprises the following steps that vehicles buy vehicles from auctions to merchants, the vehicles need to carry out subsequent operations such as passing, certificate handling and the like, and in the transaction process, the transaction enterprises need to provide services such as auctions, passing and certificate handling for the merchants and places. In the prior art, only a single process in a vehicle transaction flow can be managed, systematic management of data of each flow is lacked, and the data of the whole transaction flow is difficult to manage, so that the efficiency of obtaining vehicle information of each flow is lower, and the transaction efficiency is affected.
In order to improve the management of vehicle transaction processes and the real-time dynamic display of auction vehicles, the management and data analysis are required to be performed from links of vehicle shooting, warehousing, auction, transaction and the like.
In some alternative embodiments of the present application, a data processing method for vehicle transaction management is provided, where the entire link in the vehicle transaction process is managed, and fig. 1 is a flowchart of a data processing method for vehicle transaction management provided in the present application, as shown in fig. 1, and the method includes the following steps:
s101: acquiring service request data;
the service request data is data for representing a request service in a vehicle transaction process, a plurality of service processes correspond to a plurality of service nodes in the vehicle transaction process, the service request data corresponds to the service nodes, for example, a service request is generated at a first service node, and the first service request data is obtained; and generating a service request at the second service node, and acquiring second service request data, wherein the service request data can comprise a plurality of service nodes or one service node.
S102: carrying out service embedded point processing based on service characteristics on service request data to obtain vehicle link data;
the vehicle link data are data used for representing the vehicle transaction link after being processed by the service burial points, the service request data acquired by different service nodes comprise the corresponding service burial points of the current service node, the service characteristics corresponding to the service request data are identified according to the burial point data in the service request data, the service request data are sorted into the vehicle link data according to the service characteristics, the standardized and unified management of the vehicle data in the transaction process is realized, and the efficiency of the second-hand vehicle in the transaction process is further improved.
In an alternative embodiment of the present application, there is provided a data processing method for vehicle transaction management, and fig. 2 is a flowchart of a data processing method for vehicle transaction management provided in the present application, as shown in fig. 2, and the method includes the following steps:
s201: carrying out identification processing based on the first service characteristics on the service request data to obtain first service characteristic data;
the first service characteristic data is data for representing a service characteristic corresponding to the service request data. And identifying service characteristic data included in the service request data, and updating the vehicle link data according to the identified service characteristic data. The service request data may include a plurality of service features, and the service request data may be identified according to the plurality of service features to obtain a plurality of service feature data, for example, the service request includes a request of a first service node and a request of a second service node, the service request data includes a first service request data and a second service request data, and the first service request data is subjected to first service feature identification to obtain first service feature data, and data corresponding to a transaction flow is generated for the first service node; and carrying out second service characteristic identification on the second service request data to obtain second service characteristic data.
S202: the service request data is subjected to identification processing based on vehicle identification, so that first vehicle identification data are obtained;
the first vehicle identification data is data for representing vehicle identification corresponding to service request data, the service request data is data generated in the current vehicle transaction process, and current vehicle identification information corresponding to the service request data is identified, such as vehicle vin codes, vehicle brands, model numbers and the like.
S203: and updating the preset service link data according to the first vehicle identification data and the first service characteristic data to obtain the vehicle link data.
The vehicle link data is data for indicating a vehicle transaction link after updating the first service for the vehicle corresponding to the first vehicle identification. The preset system server stores data of transaction flows of a plurality of vehicles. The vehicle identification data corresponds to the vehicle identification of the vehicle link in the preset system database, and the service characteristic data corresponds to the link flow in the vehicle link in the preset system database. Identifying whether a link corresponding to the vehicle identification data exists in a preset system database, and if the link corresponding to the vehicle identification data exists in the system, updating the link according to the service characteristic data to obtain a vehicle link; if the link corresponding to the vehicle identification data does not exist in the system, constructing the link corresponding to the vehicle identification data according to the corresponding service characteristics, and obtaining the vehicle link data. And the corresponding links are matched in a preset system server according to the vehicle identification data, and no precedence relation exists between the corresponding links matched in the preset system service according to the service characteristic data.
In another optional embodiment of the present application, a data processing method for vehicle transaction management is provided, where after performing service embedded point processing based on service characteristics on service request data to obtain vehicle link data, the method includes:
carrying out identification processing based on a link flow on vehicle link data to obtain link flow characteristic data, wherein the link flow characteristic data is characteristic data used for representing a flow in the vehicle link data; comparing the link flow characteristic data with preset link flow characteristic data to judge whether the link flow corresponding to the link flow characteristic data meets the preset link flow rule or not, and if the link flow corresponding to the link flow characteristic data meets the preset link flow rule, obtaining vehicle link data; and if the link flow corresponding to the link flow characteristic data does not meet the preset link flow rule, outputting link abnormality prompt information.
After the service embedded point processing based on the service characteristics is carried out, the obtained vehicle link data is judged based on the link rule, whether link abnormality conditions such as link errors, link deletions, link repetition and the like exist in the current vehicle link data is judged, and link abnormality prompt information is data, wherein the link abnormality prompt information comprises abnormal link positioning information, abnormal link state information and the like.
S103: carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data;
the service prediction data is used for representing the service data in the predicted vehicle transaction link, and the related service prediction is carried out on the vehicle link data obtained after link-based arrangement, so that part of the service is predicted in the vehicle transaction process, and a manager can conveniently make a decision on the vehicle transaction.
In an alternative embodiment of the present application, there is provided a data processing method for vehicle transaction management, and fig. 3 is a flowchart of a data processing method for vehicle transaction management provided in the present application, as shown in fig. 3, and the method includes the following steps:
s301: the vehicle link data is subjected to recognition processing based on the second service characteristics to obtain second service characteristic data;
the second service characteristic data is characteristic data corresponding to the predicted service in the vehicle link data. And acquiring related data corresponding to the preset predicted service from the vehicle link data according to the preset predicted service to obtain predicted service characteristic data, wherein the preset predicted service comprises a plurality of services to obtain a plurality of corresponding predicted service characteristic data.
S302: matching a prediction model corresponding to the second service characteristic in a preset service prediction model database to obtain preset service prediction model data;
the preset service prediction model database stores a plurality of service prediction models which need to be used for predicting service, the service prediction models correspond to the predicted service characteristics, and the data corresponding to the predicted service characteristics in the vehicle link data are predicted according to the service prediction models corresponding to the predicted service characteristics. For example, the business prediction model is a prediction model of business such as a yield of a shooting vehicle, a circulation period of the vehicle, a turnover rate of the vehicle, a warehouse age of the vehicle, and a shooting yield.
S303: and carrying out service prediction processing on the vehicle link data based on the second service characteristic based on the preset service prediction model data to obtain service prediction data.
S104: and determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data.
When the service prediction data and the vehicle link data are displayed, the manager is difficult to intuitively observe the important data, and the important data in the vehicle transaction process is conveniently monitored by calculating the recommendation coefficients corresponding to the service prediction data and the vehicle link data.
In an alternative embodiment of the present application, there is provided a data processing method for vehicle transaction management, and fig. 4 is a flowchart of a data processing method for vehicle transaction management provided in the present application, as shown in fig. 4, and the method includes the following steps:
s401: the method comprises the steps of carrying out identification processing of recommended features on service prediction data and vehicle link data to obtain a plurality of recommended feature data;
the plurality of recommended feature data is feature data for representing pushing of the plurality of recommended data during the vehicle transaction.
S402: recommendation calculation processing based on a preset recommendation algorithm model is respectively carried out on the plurality of recommendation characteristic data, and a plurality of recommendation coefficient data are obtained;
the plurality of recommendation coefficient data are respectively used for representing recommendation coefficients corresponding to the plurality of recommendation features;
s403: and screening the plurality of recommendation coefficient data based on a preset recommendation rule to obtain transaction prompt data.
The transaction prompting data comprises business prediction data and business data corresponding to a plurality of recommendation coefficients meeting a preset recommendation threshold value in the vehicle link data.
In the embodiment of the application, the business prediction data and the vehicle link data meeting the recommendation rule are recommended to the digital large screen by calculating and sequencing the recommendation coefficients of the business prediction data and the vehicle link data, so that a user or a manager can monitor important data in the vehicle transaction process.
In another alternative embodiment of the present application, after determining the transaction hint data from the traffic prediction data and the vehicle link data and outputting the transaction hint data, the data processing method further comprises:
acquiring service query request data, wherein the service query request data is data for representing a request for querying a service; carrying out identification processing based on identity characteristics on service query request data to obtain query identity characteristic data; carrying out identification processing based on service characteristics on service query request data to obtain query service characteristic data; and matching service data corresponding to the query identity characteristic data and the query service characteristic data in a preset system database to obtain target query data.
When receiving a request of inquiring data from a client or a manager, identifying an identity characteristic corresponding to the inquiring request, determining the authority of the current user according to the identity characteristic, matching corresponding service data according to the user authority and the user inquiring service characteristic, and outputting the service data to a user terminal.
In another alternative embodiment of the present application, there is provided a data processing apparatus for vehicle transaction management, and fig. 5 is a schematic diagram of the data processing apparatus for vehicle transaction management provided in the present application, as shown in fig. 5, and the apparatus includes:
a data obtaining module 51, configured to obtain service request data, where the service request data is data for representing a request service in a vehicle transaction process;
the service embedding point module 52 is configured to perform service embedding point processing based on service characteristics on the service request data to obtain vehicle link data, where the vehicle link data is data for representing a vehicle transaction link after the service embedding point processing;
the service prediction module 53 is configured to perform service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data, where the service prediction data is service data used for representing a predicted vehicle transaction link;
the prompt output module 54 is configured to determine transaction prompt data according to the traffic prediction data and the vehicle link data and output the transaction prompt data.
In another alternative embodiment of the present application, there is provided a data processing apparatus for vehicle transaction management, fig. 6 is a schematic diagram of another data processing apparatus for vehicle transaction management provided in the present application, as shown in fig. 6, including:
the first service identification module 61 is configured to perform identification processing based on a first service feature on service request data to obtain first service feature data, where the first service feature data is data for representing a service feature corresponding to the service request data;
the vehicle identification module 62 is configured to perform identification processing based on a vehicle identification on the service request data, so as to obtain first vehicle identification data, where the first vehicle identification data is data for representing a vehicle identification corresponding to the service request data;
the link updating module 63 is configured to update the preset service link data according to the first vehicle identifier data and the first service feature data to obtain vehicle link data, where the vehicle link data is data for indicating a vehicle transaction link after updating the first service for the vehicle corresponding to the first vehicle identifier.
The specific manner in which the operations of the units in the above embodiments are performed has been described in detail in the embodiments related to the method, and will not be described in detail here.
In summary, in the present application, service request data is obtained, where the service request data is data for indicating a request service in a vehicle transaction process; carrying out service embedded point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedded point processing; carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data, wherein the service prediction data is used for representing the service data in a predicted vehicle transaction link; and determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data. After data processing based on service burial points is carried out on service request data, the data generated by the service request are updated to vehicle link data, unified management of all node data in the vehicle transaction process is achieved, service prediction results are obtained through service prediction processing on the vehicle link data, and are output, management of all node data and service prediction in the vehicle transaction process are completed, data acquisition, analysis and pushing in the vehicle transaction process are achieved, the problem that the efficiency of second-hand vehicle transaction is low in the prior art is solved, and the technical effect of improving the vehicle transaction efficiency is achieved.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order other than that illustrated herein.
It will be apparent to those skilled in the art that the elements or steps of the application described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, or they may alternatively be implemented in program code executable by computing devices, such that they may be stored in a memory device for execution by the computing devices, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module. Thus, the present application is not limited to any specific combination of hardware and software.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (7)
1. A data processing method for vehicle transaction management, comprising:
acquiring service request data, wherein the service request data is data for representing a request service in a vehicle transaction process;
carrying out service embedded point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedded point processing; performing recognition processing based on first service characteristics on the service request data to obtain first service characteristic data, wherein the first service characteristic data is data for representing service characteristics corresponding to the service request data; the service request data is subjected to identification processing based on vehicle identification to obtain first vehicle identification data, wherein the first vehicle identification data is data for representing the vehicle identification corresponding to the service request data; updating preset service link data according to the first vehicle identification data and the first service characteristic data to obtain the vehicle link data, wherein the vehicle link data is data used for representing a vehicle transaction link after a vehicle corresponding to the first vehicle identification updates a first service;
identifying whether a link corresponding to the vehicle identification data exists in a preset system database, and if the link corresponding to the vehicle identification data exists in the system, updating the service link according to the first service characteristic data to obtain the vehicle link data; if the service link corresponding to the vehicle identification data does not exist in the system, constructing the service link corresponding to the vehicle identification data according to the corresponding service characteristics to obtain vehicle link data;
judging the vehicle link data based on a link rule to judge whether the vehicle link data meets a preset link flow rule, and if the vehicle link data has data for representing link errors, link deletions and link repetition abnormal states, outputting link abnormality prompt information, wherein the link abnormality prompt information comprises abnormal link positioning and abnormal link state information;
carrying out service prediction processing on the vehicle link data based on a preset service prediction model to obtain service prediction data, wherein the service prediction data is used for representing service data in a predicted vehicle transaction link, and the service data is used for representing service, and the service comprises vehicle yield, vehicle circulation period, vehicle turnover rate, vehicle warehouse age and shooting yield;
determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data;
the service prediction data and the vehicle link data are subjected to identification processing of recommended features to obtain a plurality of recommended feature data, wherein the recommended feature data are feature data used for representing pushing of the recommended data in the vehicle transaction process; recommendation calculation processing based on a preset recommendation algorithm model is respectively carried out on the plurality of recommendation characteristic data to obtain a plurality of recommendation coefficient data, wherein the plurality of recommendation coefficient data are respectively used for representing recommendation coefficients corresponding to a plurality of recommendation characteristics; and screening the plurality of recommendation coefficient data based on a preset recommendation rule to obtain the transaction prompt data, wherein the transaction prompt data comprises the service prediction data and service data corresponding to a plurality of recommendation coefficients meeting a preset recommendation threshold in the vehicle link data.
2. The data processing method according to claim 1, wherein performing traffic prediction processing on the vehicle link data based on a preset traffic prediction model, obtaining traffic prediction data includes:
performing recognition processing based on second service characteristics on the vehicle link data to obtain second service characteristic data, wherein the second service characteristic data is characteristic data corresponding to prediction service in the vehicle link data;
matching a prediction model corresponding to the second service characteristic in a preset service prediction model database to obtain preset service prediction model data;
and carrying out service prediction processing based on a second service characteristic on the vehicle link data based on the preset service prediction model data to obtain the service prediction data.
3. The data processing method according to claim 1, wherein after performing service embedded point processing based on service characteristics on the service request data to obtain vehicle link data, the data processing method further comprises:
carrying out recognition processing based on a link flow on the vehicle link data to obtain link flow characteristic data, wherein the link flow characteristic data is characteristic data used for representing a flow in the vehicle link data;
comparing the link flow characteristic data with preset link flow characteristic data to judge whether the link flow corresponding to the link flow characteristic data meets preset link flow rules,
if the link flow corresponding to the link flow characteristic data meets a preset link flow rule, obtaining the vehicle link data;
and if the link flow corresponding to the link flow characteristic data does not meet the preset link flow rule, outputting link abnormality prompt information.
4. The data processing method according to claim 1, characterized in that after determining transaction-cue data from the traffic prediction data and the vehicle link data and outputting the transaction-cue data, the data processing method further comprises:
acquiring service query request data, wherein the service query request data is data for representing a request query service;
carrying out identification processing based on identity characteristics on the service query request data to obtain query identity characteristic data;
performing recognition processing based on service characteristics on the service query request data to obtain query service characteristic data;
and matching the service data corresponding to the query identity characteristic data and the query service characteristic data in a preset system database to obtain target query data.
5. A data processing apparatus for vehicle transaction management, comprising:
the system comprises a data acquisition module, a service request module and a service request module, wherein the data acquisition module is used for acquiring service request data, wherein the service request data is data for representing a request service in a vehicle transaction process;
the service embedding point module is used for carrying out service embedding point processing based on service characteristics on the service request data to obtain vehicle link data, wherein the vehicle link data is data for representing a vehicle transaction link after the service embedding point processing;
the service embedded point module comprises: the first service identification module is used for carrying out identification processing based on first service characteristics on the service request data to obtain first service characteristic data, wherein the first service characteristic data is data for representing service characteristics corresponding to the service request data; the vehicle identification module is used for carrying out identification processing based on vehicle identification on the service request data to obtain first vehicle identification data, wherein the first vehicle identification data is data for representing the vehicle identification corresponding to the service request data; the link updating module is used for updating the preset service link data according to the first vehicle identification data and the first service characteristic data to obtain the vehicle link data, wherein the vehicle link data is data used for representing a vehicle transaction link after a vehicle corresponding to the first vehicle identification updates a first service;
identifying whether a link corresponding to the vehicle identification data exists in a preset system database, and if the link corresponding to the vehicle identification data exists in the system, updating the service link according to the first service characteristic data to obtain the vehicle link data; if the service link corresponding to the vehicle identification data does not exist in the system, constructing the service link corresponding to the vehicle identification data according to the corresponding service characteristics to obtain vehicle link data;
judging the vehicle link data based on a link rule to judge whether the vehicle link data meets a preset link flow rule, and if the vehicle link data has data for representing link errors, link deletions and link repetition abnormal states, outputting link abnormality prompt information, wherein the link abnormality prompt information comprises abnormal link positioning and abnormal link state information;
the business prediction module is used for carrying out business prediction processing on the vehicle link data based on a preset business prediction model to obtain business prediction data, wherein the business prediction data are business data used for representing predicted vehicle transaction links, the business data are data used for representing businesses, and the businesses comprise vehicle yield, vehicle circulation cycle, vehicle turnover rate, vehicle warehouse age and shooting place yield;
the prompt output module is used for determining transaction prompt data according to the business prediction data and the vehicle link data and outputting the transaction prompt data;
the service prediction data and the vehicle link data are subjected to identification processing of recommended features to obtain a plurality of recommended feature data, wherein the recommended feature data are feature data used for representing pushing of the recommended data in the vehicle transaction process; recommendation calculation processing based on a preset recommendation algorithm model is respectively carried out on the plurality of recommendation characteristic data to obtain a plurality of recommendation coefficient data, wherein the plurality of recommendation coefficient data are respectively used for representing recommendation coefficients corresponding to a plurality of recommendation characteristics; and screening the plurality of recommendation coefficient data based on a preset recommendation rule to obtain the transaction prompt data, wherein the transaction prompt data comprises the service prediction data and service data corresponding to a plurality of recommendation coefficients meeting a preset recommendation threshold in the vehicle link data.
6. A computer-readable storage medium storing computer instructions for causing the computer to execute the data processing method for vehicle transaction management according to any one of claims 1 to 4.
7. An electronic device, comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores a computer program executable by the at least one processor to cause the at least one processor to perform the data processing method for vehicle transaction management of any of claims 1-4.
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