CN117473130A - Service processing method, device, equipment, medium and program product - Google Patents
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Abstract
The present invention relates to the field of big data processing technologies, and in particular, to a service processing method, apparatus, device, medium, and program product. The service processing method comprises the following steps: responding to the service processing instruction, and determining a target data type from at least one data type according to the service processing instruction; determining a target database corresponding to the service processing instruction from at least one database according to the target data type; according to the target data type, carrying out joint modeling by adopting a target database and an initial database to obtain a target joint model; and obtaining a processing result corresponding to the service processing instruction by adopting the target joint model. By the arrangement, under the premise that the data is not out of the domain, the synergy of different source data is realized, the accuracy and generalization capability of the model are improved, the response speed of the service processing instruction is accelerated, and the service processing efficiency is improved.
Description
Technical Field
The present invention relates to the field of big data processing technologies, and in particular, to a service processing method, apparatus, device, medium, and program product.
Background
With the development of internet technology, online services provide more and more convenient services for users. And simultaneously, a large amount of service related data is generated on each service platform. In practical application, service data is important data for each service platform, which leads to the occurrence of data islanding, and in order to meet the existing service requirements, the service data of a plurality of service platforms are required to be called at the same time, but a common service processing method usually consumes a large amount of time due to data interaction among the plurality of service platforms, which can reduce service response speed and seriously affect service processing efficiency.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a service processing method, apparatus, device, medium, and program product that can improve service processing efficiency.
In a first aspect, the present application provides a service processing method, including:
responding to a service processing instruction, and determining a target data type from at least one data type according to the service processing instruction;
determining a target database corresponding to the service processing instruction from at least one database according to the target data type;
according to the target data type, adopting the target database and an initial database to carry out joint modeling to obtain a target joint model;
and obtaining a processing result corresponding to the business processing instruction by adopting the target joint model.
In one embodiment, the determining, according to the target data type, a target database corresponding to the service processing instruction from at least one database includes:
determining the association value of the target data type and each database according to the data type set corresponding to the target data type and each database;
and determining a target database corresponding to the service processing instruction from the databases according to the association value.
In one embodiment, after performing joint modeling with the initial database by using the target database according to the target data type, to obtain a target joint model, the method further includes:
the target database, the initial database and the target joint model are stored in a joint mode;
after determining the target database corresponding to the service processing instruction from at least one database according to the target data type, the method further comprises:
and comparing and matching the target database corresponding to the business processing instruction with a target database corresponding to a target joint model stored in the past, and taking the target joint model corresponding to the matched target database as the target joint model corresponding to the business processing instruction when the matching is successful.
In one embodiment, the service processing instruction carries at least one target data tag;
at least one data type corresponds to at least one data tag one by one;
the determining, according to the service processing instruction, a target data type from at least one data type includes:
and matching the data type corresponding to the target data tag as the target data type according to the one-to-one correspondence between the data type and the data tag.
In one embodiment, the method further comprises:
comparing and matching the target data tag carried by the service processing instruction with the target data tag carried by the service processing instruction received in the past, and determining the matching degree;
when the matching degree corresponding to the business processing instruction received in the past reaches a preset matching degree threshold, taking the target joint model corresponding to the business processing instruction received in the past as the target joint model corresponding to the business processing instruction.
In one embodiment, the performing joint modeling with the target database and the initial database according to the target data type to obtain a target joint model includes:
generating a screening instruction according to the target data type, and respectively sending the screening instruction to the target database and the initial database; the target database is used for screening out first training data according to the screening instruction; the initial database is used for screening out second training data according to the screening instruction;
generating a training instruction and respectively sending the training instruction to the target database and the initial database; the target database is used for training an initial model by adopting the first training data according to the training instruction to obtain a first joint sub-model; the initial database is used for training an initial model by adopting the second training data according to the training instruction to obtain a second joint sub-model;
acquiring the first joint sub-model and the second joint sub-model;
and obtaining the target joint model according to the first joint sub-model and the second joint sub-model.
In a second aspect, the present application further provides a service processing apparatus, including:
the response module is used for responding to the service processing instruction and determining a target data type from at least one data type according to the service processing instruction;
the determining module is used for determining a target database corresponding to the service processing instruction from at least one database according to the target data type;
the modeling module is used for carrying out joint modeling by adopting the target database and the initial database according to the target data type to obtain a target joint model;
and the processing module is used for obtaining a processing result corresponding to the service processing instruction by adopting the target joint model.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the service processing method according to any one of the above embodiments.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the service processing method according to any of the above embodiments.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the service processing method according to any of the above embodiments.
According to the business processing method, the device, the equipment, the medium and the program product, the automatic matching of the target database can be realized according to the data which are actually needed, and the synergistic effect of different source data can be realized on the premise that the data does not exist in a domain, so that the finally obtained target joint model can fully utilize the data information of a plurality of databases on the premise of protecting the privacy of the data, the accuracy and the generalization capability of the target joint model can be improved, the response speed of business processing instructions is further accelerated, and the business processing efficiency is improved.
Drawings
FIG. 1 is an application environment diagram of a business processing method in one embodiment;
FIG. 2 is a flow diagram of a business processing method in one embodiment;
FIG. 3 is a flow diagram of a business processing method in one embodiment;
FIG. 4 is a flow diagram of a business processing method in one embodiment;
FIG. 5 is a flow diagram of a business processing method in one embodiment;
FIG. 6 is a flow diagram of a business processing method in one embodiment;
FIG. 7 is a block diagram of a business processing device in one embodiment;
fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
The service processing method provided by the embodiment of the application can be applied to an application environment shown in fig. 1. Wherein, at least one first server 102 and terminal 104 respectively communicate with a second server 106 via a network.
For example, the service processing method is applied to the terminal 104, and the terminal 104 responds to the service processing instruction and determines the target data type from at least one data type according to the service processing instruction; then, according to the target data type, determining a target database corresponding to the service processing instruction from the data storage system, namely the database, of at least one first server 102; according to the target data type, performing joint modeling by adopting a target database and a data storage system of the secondary server 106, namely an initial database, so as to obtain a target joint model; and finally, obtaining a processing result corresponding to the business processing instruction by adopting a target joint model. The terminal 104 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers. The first server 102 and the second server 106 may be implemented as separate servers or as a server cluster composed of a plurality of servers. The terminal 102 and the first server 104 and the second server 106 may be directly or indirectly connected through wired or wireless communication means, for example, through a network connection.
For another example, the service processing method is applied to the second server 106, the terminal 102 can receive the service processing instruction through the man-machine interaction interface, when the terminal 104 receives the service processing instruction, the service processing instruction is sent to the second server 106, and the second server 106 determines the target data type from at least one data type according to the service processing instruction; then, according to the target data type, determining a target database corresponding to the service processing instruction from the data storage system, namely the database, of at least one first server 102; according to the target data type, carrying out joint modeling by adopting a target database and a corresponding data storage system, namely an initial database, so as to obtain a target joint model; and finally, obtaining a processing result corresponding to the business processing instruction by adopting a target joint model. It will be appreciated that the data storage system may be a stand-alone storage device, or the data storage system may be located on the first server or the second server, or the data storage system may be located on another terminal.
In one embodiment, a service processing method is provided, where the service processing method is applied to a terminal to illustrate, it is understood that the method may also be applied to a second server, and may also be applied to a system including the terminal and the second server, and implemented through interaction between the terminal and the second server. As shown in fig. 2, the service processing method includes:
step 202, responding to the service processing instruction, and determining the target data type from at least one data type according to the service processing instruction.
The service processing instruction may refer to an instruction for performing corresponding analysis processing on the data.
As an example, the business processing request may be, for example, a request for performing a behavior risk assessment according to the corresponding data, or may be a request for performing resource change prediction according to the corresponding data, or may be a request for performing product circulation situation prediction according to the corresponding data.
The service processing request may be sent by a man-machine interaction interface of the terminal, and the man-machine interaction interface of the terminal may be a specific platform interface.
The data type refers to a category or class of data for describing characteristics and properties of the data. Common data types include identity information of the interactive object, number information of resource transfers, authorization information of the interactive object, and the like.
The target data type refers to a data type corresponding to data which needs to be used when processing a service processing request.
And 204, determining a target database corresponding to the service processing instruction from at least one database according to the target data type.
Different databases may correspond to different service systems, and since the services provided by the different service systems are different, there are differences in the data stored in the corresponding databases, and the differences between the data may be represented in the following aspects: data type: for example, a database corresponding to an e-commerce system may store information such as inventory of products and specification information of products, and a database corresponding to an interaction support system may store information such as identity information of both interaction parties and quantity information of interaction resources; data volume and scale: the data volume and the scale processed by different service systems can be different, so that the databases corresponding to the different service systems can support data storage of different scales; data structure: the data structures of different business systems may differ; data security, etc.
The target database refers to a database in which data to be used is located when processing a service processing request.
And 206, carrying out joint modeling by adopting the target database and the initial database according to the target data type to obtain a target joint model.
This embodiment may be modeled using federal modeling methods, and conventional machine learning methods typically require that all data be collected to a server for training, which may lead to data leakage and privacy issues. The federal modeling avoids data transmission by means of model training on local servers of different databases, so that interactive resources are saved, and data security is improved.
The principle of federal modeling is that training of a model is distributed on a first server corresponding to a target database and a second server corresponding to an initial database, then the first server transmits model parameters related to the trained model to the second server, the second server updates the model according to the received parameters and sends the updated model parameters back to the first server, and the process can be iterated for a plurality of times until the model converges. Wherein the first server trained model may be an initial model obtained from the second server.
The target joint model refers to a model obtained by training data in a target database and a model obtained by training data in an initial database, and the models are obtained after combination.
And step 208, obtaining a processing result corresponding to the business processing instruction by adopting the target joint model.
The processing result refers to a result obtained by performing corresponding analysis processing on the data. When the business processing request is a request for performing behavior risk assessment according to the corresponding data, the processing result may be a risk assessment result, when the business processing request is a request for performing resource change prediction according to the corresponding data, the processing result may be a resource change prediction result, or when the business processing request is a request for performing product circulation condition prediction according to the corresponding data, the processing result may be a prediction result of the product circulation condition.
In the service processing method, when the terminal receives the service processing instruction, the terminal can determine the target database from the databases according to the data types corresponding to the data required to be used by the service processing instruction, so that automatic matching of the databases can be realized according to actual processing requirements, and the terminal can perform joint modeling on the target database and the initial database, so that the data in the target database and the data in the initial database can realize synergistic effect on the premise of not leaving a domain, and the finally obtained target joint model can fully utilize the data information of the databases on the premise of protecting the privacy of the data, so that the accuracy and the generalization capability of the target joint model can be improved.
As shown in fig. 3, in some alternative embodiments, the business process instructions carry at least one target data tag;
at least one data type corresponds to at least one data tag one by one;
step 202 comprises: step 202a, matching the data type corresponding to the target data tag to be the target data type according to the one-to-one correspondence between the data type and the data tag.
The data tag may be at least one of letters, characters or numbers, and the data type tag is used for uniquely identifying a data type, and a one-to-one mapping relationship between the data tag and a plurality of data types is pre-stored in the second server in this embodiment.
After receiving the service processing instruction, the terminal firstly acquires the target data tag carried by the service processing instruction, then compares the target data tag with all the data tags, and further takes the data type corresponding to the successfully compared data tag as the target data type.
As shown in fig. 4, in some alternative embodiments, step 204 includes:
step 2042, determining the association value of the target data type and each database according to the data type set corresponding to the target data type and each database;
and 2044, determining a target database corresponding to the service processing instruction from the databases according to the association value.
The data type set corresponding to the database refers to a set formed by data types corresponding to data stored in the database, and the data type set can reflect data content stored in the database.
In this embodiment, the data type set corresponding to the database may include at least one data tag, for example, and in step 2042, the terminal may determine the association value between the target data type and each database by comparing the target data tag carried by the service processing instruction with at least one data tag corresponding to each database.
As an example, the association value may refer to a matching degree between a target data tag carried by a service processing instruction and a data tag corresponding to each database, and the association value may be calculated by using the following formula:wherein (1)>The identification association value, r, represents the number of data labels matched with the target data labels in the data labels corresponding to the database, and N represents the total number of the target data labels carried by the service processing instruction.
As an example, the terminal may use, as the target database, a database whose association value reaches a preset association value threshold according to the association value corresponding to each database. The target database may be one or more.
In some alternative embodiments, after step 206, further comprising:
the target database, the initial database and the target joint model are stored in a joint mode;
after step 204, the method further includes:
and comparing and matching the target database corresponding to the business processing instruction with the target database corresponding to the target joint model stored in the past, and taking the target joint model corresponding to the matched target database as the target joint model corresponding to the business processing instruction when the matching is successful.
In this embodiment, the terminal may store the target database, the initial database, and the target joint model in a joint manner, so that when a service processing instruction for performing analysis processing on data in the target database and data in the initial database is received again, the corresponding target joint model may be directly determined.
As an example, the target database and the initial database may be identified by using corresponding identity tags, where the identity tags may be at least one of letters, characters, or numbers, and the identity tags are used for uniquely identifying the databases, and in this embodiment, the second server pre-stores a one-to-one mapping relationship between the identity tags and the multiple databases.
The terminal can correspondingly store the identity label corresponding to the target database, the identity label corresponding to the initial database and the target joint model, the identity label corresponding to the target database and the identity label corresponding to the initial database are used as index labels, and when the identity label of the target database corresponding to the service processing request received by the terminal subsequently is matched with the identity label of the initial database and the index label stored in the past, the terminal can directly take the target joint model corresponding to the matched index label as the target joint model corresponding to the currently received service processing request.
As shown in fig. 5, in some alternative embodiments, the service processing method further includes:
step 502, comparing and matching a target data tag carried by a service processing instruction with a target data tag carried by a service processing instruction received in the past, and determining the matching degree;
and 504, when the matching degree corresponding to the business processing instruction received in the past reaches a preset matching degree threshold, taking the target joint model corresponding to the business processing instruction received in the past as the target joint model corresponding to the business processing instruction.
The matching degree can be calculated to obtain a correlation value by adopting the following formula:wherein (1)>Representing the associated value +.>The number of the target data labels carried by the service processing instruction is matched with the number of the target data labels carried by the service processing instruction received in the past, and M represents the total number of the target data labels carried by the service processing instruction.
As an example, the terminal may use, as the target joint model corresponding to the current service processing instruction, the target joint model corresponding to the service processing instruction whose matching degree reaches the preset matching degree threshold according to the matching degree corresponding to each previously received service processing instruction. The preset matching degree threshold may be 100%.
As shown in fig. 6, in some alternative embodiments, step 206 includes:
step 2062, generating a screening instruction according to the target data type, and respectively transmitting the screening instruction to a target database and an initial database; the target database is used for screening out first training data according to the screening instruction; the initial database is used for screening out second training data according to the screening instruction;
step 2064, generating training instructions and respectively transmitting the training instructions to the target database and the initial database; the target database is used for training an initial model by adopting first training data according to the training instruction to obtain a first joint sub-model; the initial database is used for training an initial model by adopting second training data according to the training instruction to obtain a second joint sub-model;
step 2066, obtaining a first joint sub-model and a second joint sub-model;
step 2068, obtaining the target joint model according to the first joint sub-model and the second joint sub-model.
The screening instruction refers to an instruction for screening data corresponding to the business processing instruction from a large amount of data.
The first training data refers to part of data required by the business processing instruction among all data contained in the target database.
The second training data refers to a part of data required by the service processing instruction among all the data contained in the initial database.
The screening instruction in this embodiment is generated by the terminal and is sent to the first server corresponding to the target database and the second server corresponding to the initial database respectively, the first server screens the first training data from the target database according to the screening instruction, and the second server screens the second training data from the initial database according to the screening instruction.
The training instruction refers to an instruction for performing model training by adopting data required by the business processing instruction.
The training instructions in the embodiment are generated by the terminal and are respectively sent to a first server corresponding to the target database and a second server corresponding to the initial database, the first server trains the original model by adopting first training data according to the training instructions to obtain a first joint sub-model, and the second server trains the original model by adopting second training data according to the training instructions to obtain a second joint sub-model. Wherein the original model may be originally stored in the data storage system by the second server, and after determining the target database in step 204, the second server may send the original model to the first server corresponding to the target database.
In this embodiment, the screening of the first training data and the training process of the first joint sub-model are completed in the first server corresponding to the target database, the screening of the second training data and the training process of the second joint sub-model are completed in the second server corresponding to the initial database, and the data in the target database and the data in the initial database are not in the domain, so that the data security and the privacy are ensured.
In step 2068, the terminal may aggregate the first joint sub-model and the second joint sub-model to obtain the target joint model by using a simple averaging or weighted averaging process.
According to the business processing method, when the business processing instruction is received, the terminal can determine the target database from the databases according to the data types corresponding to the data needed to be used by the business processing instruction, so that the automatic matching of the databases can be realized according to the actual processing requirement, and the terminal can jointly store the target database, the initial database and the target joint model, so that when the business processing instruction for analyzing and processing the data in the target database and the data in the initial database is received again, the corresponding target joint model can be directly determined, or when the business processing instruction with higher similarity of the target data label carried by the business processing instruction is received, the target joint model corresponding to the past business processing instruction is directly used as the target joint model corresponding to the current business processing instruction, so that the determination of the target joint model is accelerated, the business response speed is accelerated, the business processing method can realize the cooperative function of the data of different data sources on the premise that the data is not out of a domain, and the target joint model can be fully utilized on the premise that the privacy of the data is protected, and the target joint model can be fully utilized by the target joint model.
It should be understood that, although the steps in the flowcharts related to the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a service processing device for implementing the service processing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the service processing device provided below may refer to the limitation of the service processing method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 7, there is provided a service processing apparatus 700, including: a first response module 702, a determination module 704, a modeling module 706, and a processing module 708, wherein:
the response module 702 is configured to determine, in response to the service processing instruction, a target data type from at least one data type according to the service processing instruction;
the determining module 704 is configured to determine, according to the target data type, a target database corresponding to the service processing instruction from at least one database;
the modeling module 706 is configured to perform joint modeling with the target database and the initial database according to the target data type, so as to obtain a target joint model;
the processing module 708 is configured to obtain a processing result corresponding to the service processing instruction by using the target joint model.
In some alternative embodiments, the determination module 704 is further configured to:
determining the association value of the target data type and each database according to the data type set corresponding to the target data type and each database;
and determining a target database corresponding to the service processing instruction from the databases according to the association value.
In some alternative embodiments, modeling module 706 is further configured to:
the target database, the initial database and the target joint model are stored in a joint mode;
the determination module 704 is further configured to:
and comparing and matching the target database corresponding to the business processing instruction with the target database corresponding to the target joint model stored in the past, and taking the target joint model corresponding to the matched target database as the target joint model corresponding to the business processing instruction when the matching is successful.
In some alternative embodiments, the business processing instructions carry at least one target data tag;
at least one data type corresponds to at least one data tag one by one;
the response module 702 is further configured to:
and matching the data type corresponding to the target data tag as the target data type according to the one-to-one correspondence between the data type and the data tag.
In some alternative embodiments, the determination module 704 is further configured to:
comparing and matching the target data tag carried by the service processing instruction with the target data tag carried by the service processing instruction received in the past, and determining the matching degree;
when the matching degree corresponding to the business processing instruction received in the past reaches a preset matching degree threshold, taking the target joint model corresponding to the business processing instruction received in the past as the target joint model corresponding to the business processing instruction.
In some alternative embodiments, modeling module 706 is further configured to:
generating a screening instruction according to the target data type, and respectively sending the screening instruction to a target database and an initial database; the target database is used for screening out first training data according to the screening instruction; the initial database is used for screening out second training data according to the screening instruction;
generating a training instruction, and respectively transmitting the training instruction to a target database and an initial database; the target database is used for training an initial model by adopting first training data according to the training instruction to obtain a first joint sub-model; the initial database is used for training an initial model by adopting second training data according to the training instruction to obtain a second joint sub-model;
acquiring a first joint sub-model and a second joint sub-model;
and obtaining a target joint model according to the first joint sub-model and the second joint sub-model.
The respective modules in the above-described service processing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 8. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement a business processing method. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 8 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, which when executed by a processor implements the service processing method described in any of the above embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the service processing method described in any of the above embodiments.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (10)
1. A method for processing a service, comprising:
responding to a service processing instruction, and determining a target data type from at least one data type according to the service processing instruction;
determining a target database corresponding to the service processing instruction from at least one database according to the target data type;
according to the target data type, adopting the target database and an initial database to carry out joint modeling to obtain a target joint model;
adopting the target joint model to obtain a processing result corresponding to the business processing instruction;
the determining, according to the target data type, a target database corresponding to the service processing instruction from at least one database includes:
determining the association value of the target data type and each database according to the data type set corresponding to the target data type and each database;
and determining a target database corresponding to the service processing instruction from the databases according to the association value.
2. The method according to claim 1, wherein the determining, according to the association value, a target database corresponding to the service processing instruction from the databases includes:
and taking the database with the association value reaching a preset association value threshold as a target database according to the association value corresponding to each database.
3. The method of claim 1, wherein after jointly modeling with the initial database using the target database according to the target data type to obtain a target joint model, the method further comprises:
the target database, the initial database and the target joint model are stored in a joint mode;
after determining the target database corresponding to the service processing instruction from at least one database according to the target data type, the method further comprises:
and comparing and matching the target database corresponding to the business processing instruction with a target database corresponding to a target joint model stored in the past, and taking the target joint model corresponding to the matched target database as the target joint model corresponding to the business processing instruction when the matching is successful.
4. The method of claim 1, wherein the business process instructions carry at least one target data tag;
at least one data type corresponds to at least one data tag one by one;
the determining, according to the service processing instruction, a target data type from at least one data type includes:
and matching the data type corresponding to the target data tag as the target data type according to the one-to-one correspondence between the data type and the data tag.
5. The method according to claim 4, wherein the method further comprises:
comparing and matching the target data tag carried by the service processing instruction with the target data tag carried by the service processing instruction received in the past, and determining the matching degree;
when the matching degree corresponding to the business processing instruction received in the past reaches a preset matching degree threshold, taking the target joint model corresponding to the business processing instruction received in the past as the target joint model corresponding to the business processing instruction.
6. The method of claim 1, wherein the performing joint modeling with the target database and an initial database according to the target data type to obtain a target joint model includes:
generating a screening instruction according to the target data type, and respectively sending the screening instruction to the target database and the initial database; the target database is used for screening out first training data according to the screening instruction; the initial database is used for screening out second training data according to the screening instruction;
generating a training instruction and respectively sending the training instruction to the target database and the initial database; the target database is used for training an initial model by adopting the first training data according to the training instruction to obtain a first joint sub-model; the initial database is used for training an initial model by adopting the second training data according to the training instruction to obtain a second joint sub-model;
acquiring the first joint sub-model and the second joint sub-model;
and obtaining the target joint model according to the first joint sub-model and the second joint sub-model.
7. A service processing apparatus, comprising:
the response module is used for responding to the service processing instruction and determining a target data type from at least one data type according to the service processing instruction;
the determining module is used for determining a target database corresponding to the service processing instruction from at least one database according to the target data type;
the modeling module is used for carrying out joint modeling by adopting the target database and the initial database according to the target data type to obtain a target joint model;
and the processing module is used for obtaining a processing result corresponding to the service processing instruction by adopting the target joint model.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the business processing method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the service processing method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the business processing method of any of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311435933.9A CN117473130A (en) | 2023-10-31 | 2023-10-31 | Service processing method, device, equipment, medium and program product |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311435933.9A CN117473130A (en) | 2023-10-31 | 2023-10-31 | Service processing method, device, equipment, medium and program product |
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| CN117473130A true CN117473130A (en) | 2024-01-30 |
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| CN202311435933.9A Pending CN117473130A (en) | 2023-10-31 | 2023-10-31 | Service processing method, device, equipment, medium and program product |
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- 2023-10-31 CN CN202311435933.9A patent/CN117473130A/en active Pending
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