CN113282379A - Service processing method and device based on big data and cloud computing - Google Patents
Service processing method and device based on big data and cloud computing Download PDFInfo
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- CN113282379A CN113282379A CN202011328123.XA CN202011328123A CN113282379A CN 113282379 A CN113282379 A CN 113282379A CN 202011328123 A CN202011328123 A CN 202011328123A CN 113282379 A CN113282379 A CN 113282379A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
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- G06F9/48—Program initiating; Program switching, e.g. by interrupt
- G06F9/4806—Task transfer initiation or dispatching
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Abstract
The service processing method and device based on big data and cloud computing provided by the invention firstly obtain first service processing information of a historical service terminal in a first service scene, secondly obtain second service processing information of the historical service terminal in a second service scene corresponding to a current service terminal, wherein the second service processing information is matched with the first service processing information, and then service processing evaluation is carried out on the current service terminal according to the first service processing information and the second service processing information. Therefore, the service processing evaluation of the current service terminal can be carried out, and the service evaluation accuracy of the current service terminal can be ensured.
Description
Technical Field
The invention relates to the technical field of big data and cloud computing, in particular to a business processing method and device based on big data and cloud computing.
Background
With the development of science and technology, the development of big data and cloud computing is more and more mature. However, the accuracy of service evaluation for current service terminals has long been a concern.
Disclosure of Invention
In order to solve the problems, the invention provides a business processing method and a business processing device based on big data and cloud computing.
A business processing method based on big data and cloud computing comprises the following steps:
acquiring first service processing information of a historical service terminal in a first service scene;
acquiring second service processing information of the historical service terminal in a second service scene corresponding to the current service terminal, wherein the second service processing information is matched with the first service processing information;
and performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
Further, the obtaining of the first service processing information of the historical service terminal in the first service scenario includes: acquiring first dynamic service processing information of a historical service terminal in a first service scene; the obtaining of the second service processing information of the historical service terminal in the second service scenario corresponding to the current service terminal includes: acquiring second dynamic service processing information of the historical service terminal in a second service scene corresponding to the current service terminal; the performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information includes: and performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information.
Further, the performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information includes: acquiring event weight information of at least two pieces of service event information on the first dynamic service processing information; acquiring update records of at least two pieces of update information on the second dynamic service processing information; and performing service processing evaluation on the current service terminal according to the event weight information of the at least two pieces of service event information, the updating records of the at least two pieces of updating information and the trained convolutional neural network corresponding to the second dynamic service processing information.
A business processing device based on big data and cloud computing comprises:
the first information acquisition module is used for acquiring first service processing information of the historical service terminal in a first service scene;
a second information obtaining module, configured to obtain second service processing information of the historical service terminal in a second service scenario corresponding to the current service terminal, where the second service processing information is matched with the first service processing information;
and the service processing evaluation module is used for carrying out service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
By applying the method and the device, first service processing information of a historical service terminal in a first service scene is obtained firstly, second service processing information of the historical service terminal in a second service scene corresponding to a current service terminal is obtained secondly, the second service processing information is matched with the first service processing information, and then service processing evaluation is carried out on the current service terminal according to the first service processing information and the second service processing information. Therefore, the service processing evaluation of the current service terminal can be carried out, and the service evaluation accuracy of the current service terminal can be ensured.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of a service processing method based on big data and cloud computing according to an embodiment of the present invention.
Fig. 2 is a functional block diagram of a service processing apparatus based on big data and cloud computing according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of a hardware structure of a server according to an embodiment of the present invention.
Detailed Description
In order to better understand the technical solutions of the present invention, the following detailed descriptions of the technical solutions of the present invention are provided with the accompanying drawings and the specific embodiments, and it should be understood that the specific features in the embodiments and the examples of the present invention are the detailed descriptions of the technical solutions of the present invention, and are not limitations of the technical solutions of the present invention, and the technical features in the embodiments and the examples of the present invention may be combined with each other without conflict.
Referring to fig. 1, a business processing method based on big data and cloud computing is shown, which is applied to a server and includes the contents described in the following steps S11-S13.
Step S11, obtaining first service processing information of the historical service terminal in the first service scenario.
Step S12, obtaining second service processing information of the historical service terminal in a second service scenario corresponding to the current service terminal, where the second service processing information matches with the first service processing information.
Step S13, performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
By applying the above steps S11-S13, first obtaining first service processing information of a historical service terminal in a first service scenario, and then obtaining second service processing information of the historical service terminal in a second service scenario corresponding to a current service terminal, where the second service processing information matches with the first service processing information, and then performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information. Therefore, the service processing evaluation of the current service terminal can be carried out, and the service evaluation accuracy of the current service terminal can be ensured.
Further, the obtaining of the first service processing information of the historical service terminal in the first service scenario includes: acquiring first dynamic service processing information of a historical service terminal in a first service scene; the obtaining of the second service processing information of the historical service terminal in the second service scenario corresponding to the current service terminal includes: acquiring second dynamic service processing information of the historical service terminal in a second service scene corresponding to the current service terminal; the performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information includes: and performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information.
Further, the performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information includes: acquiring event weight information of at least two pieces of service event information on the first dynamic service processing information; acquiring update records of at least two pieces of update information on the second dynamic service processing information; and performing service processing evaluation on the current service terminal according to the event weight information of the at least two pieces of service event information, the updating records of the at least two pieces of updating information and the trained convolutional neural network corresponding to the second dynamic service processing information.
As shown in fig. 2, there is provided a business processing apparatus 200 based on big data and cloud computing, including:
a first information obtaining module 210, configured to obtain first service processing information of a historical service terminal in a first service scenario;
a second information obtaining module 220, configured to obtain second service processing information of the historical service terminal in a second service scenario corresponding to the current service terminal, where the second service processing information is matched with the first service processing information;
a service processing evaluation module 230, configured to perform service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
Referring to fig. 3, a hardware block diagram of the server 110 is provided.
Fig. 3 is a block diagram illustrating a server 110 according to an embodiment of the present invention. The server 110 in the embodiment of the present invention may be a server with data storage, transmission, and processing functions, as shown in fig. 3, the server 110 includes: memory 111, processor 112, network module 113, and big data and cloud computing based business processing device 200.
The memory 111, the processor 112, and the network module 113 are electrically connected directly or indirectly to enable transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 111 stores therein the big data and cloud computing based business processing apparatus 200, the big data and cloud computing based business processing apparatus 200 includes at least one software functional module that can be stored in the memory 111 in the form of software or firmware (firmware), and the processor 112 executes various functional applications and data processing by running the software programs and modules stored in the memory 111, for example, the big data and cloud computing based business processing apparatus 200 in the embodiment of the present invention, so as to implement the big data and cloud computing based business processing method in the embodiment of the present invention.
The Memory 111 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like. The memory 111 is used for storing a program, and the processor 112 executes the program after receiving the execution instruction.
The processor 112 may be an integrated circuit chip having data processing capabilities. The Processor 112 may be a general-purpose Processor including a Central Processing Unit (CPU), a Network Processor (NP), and the like. The various methods, steps and logic blocks disclosed in embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The network module 113 is used for establishing communication connection between the server 110 and other communication terminal devices through a network, and implementing transceiving operation of network signals and data. The network signal may include a wireless signal or a wired signal.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and that server 110 may include more or fewer components than shown in fig. 3 or have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
An embodiment of the present invention also provides a computer-readable storage medium, which includes a computer program. The computer program controls the server 110 on which the readable storage medium is executed to perform the above-mentioned method.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method can be implemented in other ways. The apparatus and method embodiments described above are illustrative only, as the flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present invention may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server 100, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes. It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The above are merely examples of the present application and are not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (4)
1. A business processing method based on big data and cloud computing is characterized by comprising the following steps:
acquiring first service processing information of a historical service terminal in a first service scene;
acquiring second service processing information of the historical service terminal in a second service scene corresponding to the current service terminal, wherein the second service processing information is matched with the first service processing information;
and performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
2. The method of claim 1, wherein obtaining the first service processing information of the historical service terminal in the first service scenario comprises: acquiring first dynamic service processing information of a historical service terminal in a first service scene; the obtaining of the second service processing information of the historical service terminal in the second service scenario corresponding to the current service terminal includes: acquiring second dynamic service processing information of the historical service terminal in a second service scene corresponding to the current service terminal; the performing service processing evaluation on the current service terminal according to the first service processing information and the second service processing information includes: and performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information.
3. The method according to claim 2, wherein the performing service processing evaluation on the current service terminal according to the first dynamic service processing information and the second dynamic service processing information comprises: acquiring event weight information of at least two pieces of service event information on the first dynamic service processing information; acquiring update records of at least two pieces of update information on the second dynamic service processing information; and performing service processing evaluation on the current service terminal according to the event weight information of the at least two pieces of service event information, the updating records of the at least two pieces of updating information and the trained convolutional neural network corresponding to the second dynamic service processing information.
4. A business processing device based on big data and cloud computing is characterized by comprising:
the first information acquisition module is used for acquiring first service processing information of the historical service terminal in a first service scene;
a second information obtaining module, configured to obtain second service processing information of the historical service terminal in a second service scenario corresponding to the current service terminal, where the second service processing information is matched with the first service processing information;
and the service processing evaluation module is used for carrying out service processing evaluation on the current service terminal according to the first service processing information and the second service processing information.
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CN1692364A (en) * | 2002-11-08 | 2005-11-02 | 松下电器产业株式会社 | Mutual evaluation system, terminal used therefor, and program thereof |
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CN1692364A (en) * | 2002-11-08 | 2005-11-02 | 松下电器产业株式会社 | Mutual evaluation system, terminal used therefor, and program thereof |
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Application publication date: 20210820 |