CN113792901A - Service processing method and device, storage medium and electronic equipment - Google Patents
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Abstract
The disclosure provides a service processing method, a service processing device, a storage medium and electronic equipment, and relates to the technical field of computers. The service processing method comprises the following steps: acquiring service state data of each demand party at each preset time in a service period; determining service input data of the target demand party at the current preset moment according to the service state data of each demand party and service configuration information aiming at the target demand party, and distributing service resources for the target demand party according to the service input data; and updating the service configuration information by using the service feedback data of the target demand party at the next preset time. The method and the device solve the problem that reasonable service input data cannot be determined.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a service processing method, a service processing apparatus, a computer-readable storage medium, and an electronic device.
Background
With the development of the internet, a plurality of demand parties (such as enterprises, merchants, individual users, and the like) process services by accessing an internet platform, and the platform party needs to allocate appropriate service resources, such as web page resources, cloud computing resources, and the like, to the demand parties to meet the service requirements.
However, because the total amount of the business scale of the demand party is generally high, and the business demands of the demand parties are different, how to make a proper business plan for different demand parties is to avoid the demand parties from obtaining too many or too low resources, and to achieve global business resource balance and optimization, which is a problem to be solved urgently by the platform.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure provides a service processing method, a device, a computer-readable storage medium, and an electronic device, thereby solving, at least to a certain extent, a problem that reasonable service investment data cannot be determined in related technologies.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to a first aspect of the present disclosure, a service processing method is provided, including: acquiring service state data of each demand party at each preset time in a service period; determining service input data of the target demand party at the current preset moment according to the service state data of each demand party and service configuration information aiming at the target demand party, and distributing service resources for the target demand party according to the service input data; and updating the service configuration information by using the service feedback data of the target demand party at the next preset time.
In an exemplary embodiment of the present disclosure, the service configuration information includes priorities of service candidate input data under different service state data; the determining the service input data of the target demand party at the current scheduled time according to the service state data of each demand party and the service configuration information aiming at the target demand party comprises: searching the priority of corresponding service candidate input data according to the service state data of each demand party in the service configuration information; and determining the service input data of the target demand party from the service candidate input data according to the priority of the service candidate input data.
In an exemplary embodiment of the disclosure, the determining, from the service candidate investment data, service investment data of the target demand side according to a priority of the service candidate investment data includes: and determining the service input data of the target demand party from the service candidate input data by adopting the maximum priority according to the priority of the service candidate input data.
In an exemplary embodiment of the present disclosure, the service feedback data is determined in the following manner: and determining the service feedback data according to the service state data of the target demand party at the next preset time.
In an exemplary embodiment of the present disclosure, the business state data includes planning data and cumulative investment data; the determining the service feedback data according to the service state data of the target demand party at the next predetermined time includes: and when the accumulated investment data of the target demander at the next preset time is less than or equal to the plan data, determining the service feedback data according to the ratio of the accumulated investment data to the plan data.
In an exemplary embodiment of the present disclosure, the determining the service feedback data according to the service state data of the target demander at the next predetermined time includes: and when the accumulated investment data of the target demand side at the next preset time is larger than the plan data, determining the service feedback data according to the opposite number of the ratio of the accumulated investment data to the plan data.
In an exemplary embodiment of the present disclosure, the updating the service configuration information by using the service feedback data of the target demander at the next predetermined time includes: determining incremental information according to the service feedback data and experience parameters of the target demand party at the next preset time; and updating the service configuration information according to the increment information.
In an exemplary embodiment of the present disclosure, the service period is a service test period; and updating the service configuration information in a plurality of service test periods to obtain stable version service configuration information.
In an exemplary embodiment of the present disclosure, at any predetermined time within a business actual period, determining, according to the business state data of a target demand party, the business configuration information of the target demand party from the business configuration information; and determining the service input data of the target demand party at any preset time according to the service configuration information of the target demand party.
According to a second aspect of the present disclosure, a service processing apparatus includes: the service state data acquisition module is used for acquiring service state data of each demand party at each preset time in a service period; a service resource allocation module, configured to determine service investment data of the target demand party at a current predetermined time according to the service state data of each demand party and service configuration information for the target demand party, and allocate service resources to the target demand party according to the service investment data; and the service configuration information updating module is used for updating the service configuration information by using the service feedback data of the target demand party at the next preset time.
According to a third aspect of the present disclosure, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described service processing method.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the above-described business processing method via execution of the executable instructions.
The technical scheme of the disclosure has the following beneficial effects:
in the service processing process, on one hand, the service input data of the target demand party at the current preset time is determined according to the service state data of each demand party and the service configuration information aiming at the target demand party, and the service input data is provided for the target demand party by combining the service state data of each demand party and taking the service configuration information as the basis, so that the blind input of the target demand party to the service is avoided, the unreasonable service resource distribution is avoided, if the service resource distribution is too much, the resource waste is caused, the service resource distribution is too little, and the normal service processing cannot be realized; in addition, the scheme is favorable for the platform side to balance and optimize the global service resource allocation. On the other hand, the service configuration information is updated through the service feedback data so as to continuously optimize the service configuration strategy aiming at the target demand party, so that the service input data provided for the target demand party is more reasonable and reliable, and the distribution of service resources is further improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is apparent that the drawings in the following description are only some embodiments of the present disclosure, and that other drawings can be obtained from those drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart illustrating a method of business process processing in the exemplary embodiment;
FIG. 2 illustrates a flow chart of determining business engagement data for a target demand party in the exemplary embodiment;
fig. 3 shows a flowchart of updating service configuration information in the present exemplary embodiment;
FIG. 4 is a flow chart illustrating a service test cycle update in the exemplary embodiment;
FIG. 5 is a flow chart illustrating the determination of target customer service engagement data during a service life cycle in the exemplary embodiment;
FIG. 6 is a block diagram showing the structure of a business process processing apparatus according to the exemplary embodiment;
fig. 7 shows an electronic device for implementing the above method in the present exemplary embodiment.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and the like. In other instances, well-known technical solutions have not been shown or described in detail to avoid obscuring aspects of the present disclosure.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus their repetitive description will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
In the related art, because the total amount of the business scale of the demand party is generally high, and the business demands of the demand parties are different, how to make a proper business plan for different demand parties is to avoid the demand parties from obtaining too many or too low resources, and simultaneously realize global business resource balance and optimization, which is a problem to be solved urgently by the platform.
For example, in the process of the display information release service, a website embeds display information bits in a webpage, when a user opens the webpage, the website or an online platform releases the display information to the corresponding display information bits in real time, if the user is interested in the display information bits, the user usually clicks to open the corresponding display information pages or videos, the display information is released to the user in a targeted and directional manner, and the display information meeting the user requirements is provided for the user. The demanders who want to obtain the display information bit putting opportunity usually need to determine corresponding service investment for each display information, and the judgment platform determines the display information which can be displayed on the display information bit by comparing the service investment given by each demander.
However, in the process of displaying information delivery service, since the requesting party does not know the service input given by other requesting parties who want to obtain the opportunity of delivering the display information bits, the requesting party cannot determine reasonable service input, which often results in that the service input of the requesting party is too small, the opportunity of delivering the display information bits cannot be obtained, or the service input of the requesting party is too large, which results in too high cost.
In view of one or more of the above problems, exemplary embodiments of the present disclosure provide a traffic processing method.
Fig. 1 shows a schematic flow of service processing in the present exemplary embodiment, including the following steps S110 to S130:
step S110, acquiring service state data of each demand party at each preset time in a service period;
step S120, determining service input data of the target demand party at the current preset time according to the service state data of each demand party and the service configuration information aiming at the target demand party, and distributing service resources for the target demand party according to the service input data;
step S130, updating the service configuration information by using the service feedback data of the target demander at the next predetermined time.
In the service processing process, on one hand, the service input data of the target demand party at the current preset time is determined according to the service state data of each demand party and the service configuration information aiming at the target demand party, and the service input data is provided for the target demand party by combining the service state data of each demand party and taking the service configuration information as the basis, so that the blind input of the target demand party to the service is avoided, the unreasonable service resource distribution is avoided, if the service resource distribution is too much, the resource waste is caused, the service resource distribution is too little, and the normal service processing cannot be realized; in addition, the scheme is favorable for the platform side to balance and optimize the global service resource allocation. On the other hand, the service configuration information is updated through the service feedback data so as to continuously optimize the service configuration strategy aiming at the target demand party, so that the service input data provided for the target demand party is more reasonable and reliable, and the distribution of service resources is further improved.
Each step in fig. 1 will be described in detail below.
Step S110, obtaining the service status data of each demand party at each predetermined time in the service period.
The service cycle may be a complete phase of performing service processing, the execution time of one service cycle may be divided into a plurality of small phases, the divided time may be used as a predetermined time, for example, one day is required to execute one service cycle, the execution time of one service cycle may be divided into 24 phases according to hours, and each integral time is used as a predetermined time.
The demanding party is a party who wants to acquire a service resource, for example: and acquiring a demander for displaying the use right of the information bit, a demander for acquiring the computing resource of the server and the like. It should be noted that the display information may be an advertisement, a public service video, a notification announcement, and the like, and the display information bit is a display bit provided by a website or a platform for displaying the display information.
The service state data may be a service state presented by the demanding party for the service resource, such as budget cost, actual cost, and the like given by the demanding party for the service resource.
Step S120, determining service input data of the target demand party at the current preset time according to the service state data of each demand party and the service configuration information aiming at the target demand party, and distributing service resources for the target demand party according to the service input data.
The target demand party can be any one of the demand parties, and the service investment data can be determined for the target demand party, wherein the service investment data can be regarded as competitiveness provided by the demand party when the demand party acquires the service resources, namely the probability of acquiring the service resources is higher when the service investment data is larger, for example, the service investment data can be a bid when the demand party acquires the information display position; the projected cost of the demander in acquiring the server computing resources may also be considered.
In an optional implementation manner, the service configuration information includes a priority of each service candidate investment data under different service state data. The traffic engagement data of the target demand party may be determined through steps S210 to S220 as shown in fig. 2:
step S210, searching the priority of the corresponding service candidate input data according to the service state data of each demand party in the service configuration information.
The service candidate investment data is alternative data of the service investment data, and the service investment data is determined from the service candidate investment data. The priority is an index for determining the traffic investment data from the traffic candidate investment data.
The service configuration information in the above process may be set as a configuration table. An advertisement bidding service configuration table as shown in table 1, wherein budget is the budget amount of the demander on the day, consumption is the amount of the demander that has been spent on the day, the candidate bid data may be the candidate bids in table 1, and the candidate bids in the range of 0 to 100 are shown in table 1, and the budget and consumption of the demander and the priority of the candidate bid of the demander are corresponding to each predetermined time in the table, and the priority is initialized to 0. The service configuration information may provide basis and reference for the target demand party in determining the service investment data.
TABLE 1
Step S220, determining the service input data of the target demand party from the service candidate input data according to the priority of the service candidate input data.
In an optional implementation manner, determining the service investment data of the target demand party from the service candidate investment data according to the priority of the service candidate investment data may include: and determining the service input data of the target demand party from the service candidate input data by adopting the maximum priority according to the priority of the service candidate input data.
In the step shown in fig. 2, the service investment data is determined for the target demand party by setting the priority of the service candidate investment data in the service configuration information, and the service state is considered comprehensively, so that the reasonability of the determined service investment data is improved.
Step S130, updating the service configuration information by using the service feedback data of the target demander at the next predetermined time.
The service feedback data is a feedback of the service input data at the current time according to the service state data at the next scheduled time.
In an optional implementation manner, the service feedback data is determined as follows: and determining service feedback data according to the service state data of the target demand party at the next preset time.
The traffic status data may include planning data, which may be, for example, the budgets mentioned in table 1 above, and cumulative investment data, which may be, for example, the consumptions mentioned in table 1 above. And determining service feedback data through the service state data at the next moment so as to form feedback on the service input data at the current moment, and providing a feedback index for further establishing more reasonable service input data.
In an optional implementation manner, determining the service feedback data according to the service state data of the target demand party at the next predetermined time includes: and when the accumulated investment data of the target demand side at the next preset moment is less than or equal to the plan data, determining the service feedback data according to the ratio of the accumulated investment data to the plan data.
For example: and when the cost is not more than the budget, calculating R _1 as cost/budget, wherein R _1 is service feedback data. And calculating R _2 ═ cost-budget)/budget, wherein R _2 is service feedback data.
In an optional implementation manner, determining the service feedback data according to the service state data of the target demand party at the next predetermined time includes: and when the accumulated investment data of the target demand side at the next preset moment is larger than the plan data, determining the service feedback data according to the opposite number of the ratio of the accumulated investment data to the plan data.
For example: and when the cost is greater than the budget, calculating R _3 as-cost/budget, wherein R _3 is service feedback data. And calculating R _4 ═ - (cost-budget)/budget, wherein R _4 is service feedback data.
It should be noted that, the manner of determining the feedback data in the foregoing process is not exclusive, and is not limited to the above-mentioned several manners, and an appropriate manner of determining the feedback data may be selected according to a specific implementation situation.
In an optional implementation manner, updating the service configuration information by using the service feedback data of the target demand party at the next predetermined time may be implemented by steps S310 to S320 shown in fig. 3, where the implementation process is as follows:
step S310, determining increment information according to the service feedback data and the experience parameters of the target demand side at the next preset time.
The empirical parameters may be preset empirically by one skilled in the art. The incremental information is the change degree of the service configuration information when the service configuration information is updated.
For example, increaseThe quantitative information can be calculated by calculating Z ═ α · [ R + γ · max ·AQ(s2,A)-Q(s1,a)]Obtaining, where α and γ are two empirical parameters, R is service feedback data, maxAQ (s2, a) is the maximum value of the service configuration information corresponding to the service status data s2 at the next scheduled time, Q (s1, a) is the service configuration information of which the service input data corresponding to the service status data s1 at the current time is a, and Z is incremental information.
Step S320, updating the service configuration information according to the incremental information.
The update of the service configuration information may be performed by calculating Q (s1, a) '(Q (s1, a) + Z, where Q (s1, a) is the original service configuration information and Q (s1, a)' is the updated service configuration information.
In the step shown in fig. 3, the service configuration information is updated in an incremental information manner in combination with the service feedback data at the next scheduled time, so that dynamic update of the service configuration information is realized, and the adaptability of the service configuration information is improved.
In an alternative embodiment, the service period may be a service test period; and in a plurality of service test periods, updating the service configuration information to obtain stable version service configuration information.
The service test period can be completed off-line or on-line, and the stable version of service configuration information can be continuously updated until the deviation between the updated data and the original data of the service configuration information is lower than a set threshold value, or the operation of updating the service configuration information for a preset number of times is performed.
Fig. 4 shows a flowchart of service test cycle update, which includes the following specific processes:
step S401, starting updating, setting a state1 for the demand side, wherein the state1 is the service state data of the demand side at the current time;
step S402, setting a bid action for a demand party by a greedy strategy, wherein the action is service input data, and the greedy strategy is to select optimal service input data in service configuration information, for example, the service candidate input data with the highest priority can be selected as service input data;
step S403, counting cost of the demand party after 1 hour, and calculating state2 and reward, wherein the cost is accumulated investment data of the demand party, the state2 represents service state data of the demand party at the next preset time, and the reward represents service feedback data;
step S404, updating Q table according to state1, state2, reward and action, wherein Q table represents service configuration information table;
step S405, judging whether the updating time reaches 24 hours, wherein the 24 hours are taken as a service test period, and executing step S406 when the updating time of 24 hours is not finished; when the update is to 24 hours, step S407 is executed;
step S406, the state1 is updated to state2, and the process returns to the step S402 for circular execution;
in step S407, the update is completed, and the update of one cycle is completed.
In an alternative embodiment, the target demand party service investment data may be determined in the service actual period through steps S510 to S520 shown in fig. 5, and the specific implementation process is as follows:
step S510, determining the service configuration information of the target demand party from the service configuration information according to the service state data of the target demand party at any preset time in a service actual period;
step S520, determining the service investment data of the target demand party at any predetermined time according to the service configuration information of the target demand party.
The process service actual period determination service investment data may be an online executed process.
In an optional implementation manner, the service configuration information may also be updated by using service feedback data of the target demand party at the next predetermined time corresponding to the service actual period.
The execution sequence of the service test period and the service actual period can be implemented by firstly completing the test period to train a stable version of service configuration information and then implementing the operation of the service actual period; the related operations of the service test period and the service actual period can also be executed alternately, namely, the service configuration information is updated in the service actual period stage, and the two period stages are updated together to obtain the stable version service configuration information.
Exemplary embodiments of the present disclosure also provide a video and audio matching apparatus. As shown in fig. 6, the service processing apparatus 600 may include:
a service status data obtaining module 610, configured to obtain service status data of each demand party at each predetermined time in a service period;
a service resource allocation module 620, configured to determine service investment data of the target demand party at a current predetermined time according to the service state data of each demand party and the service configuration information for the target demand party, and allocate service resources to the target demand party according to the service investment data;
and a service configuration information updating module 630, configured to update the service configuration information by using the service feedback data of the target demander at the next predetermined time.
In an optional implementation manner, the service configuration information in the service resource allocation module 620 includes priorities of the service candidate input data under different service state data; the traffic resource allocation module 620 includes:
the priority searching module is used for searching the priority of corresponding service candidate input data according to the service state data of each demand party in the service configuration information;
and the service input data determining module is used for determining the service input data of the target demand party from the service candidate input data according to the priority of the service candidate input data.
In an optional implementation, the traffic engagement data determining module is configured to: and determining the service input data of the target demand party from the service candidate input data by adopting the maximum priority according to the priority of the service candidate input data.
In an optional implementation manner, the service configuration information updating module 630 includes: a service feedback data determination module: and the data processing unit is used for determining the service feedback data according to the service state data of the target demand party at the next preset time.
In an alternative embodiment, the business state data includes planning data and cumulative investment data; the service feedback data determination module is configured to: and when the accumulated investment data of the target demand side at the next preset moment is less than or equal to the plan data, determining the service feedback data according to the ratio of the accumulated investment data to the plan data.
In an optional implementation manner, the service feedback data determining module is further configured to: and when the accumulated investment data of the target demand side at the next preset moment is larger than the plan data, determining the service feedback data according to the opposite number of the ratio of the accumulated investment data to the plan data.
In an optional implementation, the service configuration information updating module 630 is further configured to: determining incremental information according to the service feedback data and experience parameters of the target demand party at the next preset time; and updating the service configuration information according to the increment information.
In an optional implementation manner, the service processing apparatus 600 further includes: and the stable version service configuration information acquisition module is used for updating the service configuration information in a plurality of service test periods to obtain the stable version service configuration information when the service period is the service test period.
In an optional implementation manner, the service processing apparatus 600 further includes: the actual service input data determining module is used for determining the service configuration information of the target demand party from the service configuration information according to the service state data of the target demand party at any preset time in a service actual period; and determining the service input data of the target demand party at any preset time according to the service configuration information of the target demand party.
The specific details of each part in the service processing apparatus 600 are already described in detail in the method part embodiment, and details that are not disclosed may refer to the method part embodiment, and thus are not described again.
Exemplary embodiments of the present disclosure also provide a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, various aspects of the disclosure may also be implemented in the form of a program product comprising program code for causing an electronic device to perform the steps according to various exemplary embodiments of the disclosure described in the above-mentioned "exemplary methods" section of this specification, when the program product is run on the electronic device. The program product may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on an electronic device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The exemplary embodiment of the present disclosure also provides an electronic device capable of implementing the above method. An electronic device 700 according to such an exemplary embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 7, electronic device 700 may take the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: at least one processing unit 710, at least one memory unit 720, a bus 730 that connects the various system components (including the memory unit 720 and the processing unit 710), and a display unit 740.
The memory unit 720 stores program code that may be executed by the processing unit 710 to cause the processing unit 710 to perform steps according to various exemplary embodiments of the present disclosure as described in the "exemplary methods" section above in this specification. For example, processing unit 710 may perform any one or more of the method steps of fig. 1-5.
The storage unit 720 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)721 and/or a cache memory unit 722, and may further include a read only memory unit (ROM) 723.
The memory unit 720 may also include programs/utilities 724 having a set (at least one) of program modules 725, such program modules 725 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 700 may also communicate with one or more external devices 800 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 700, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 700 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 760. As shown, the network adapter 760 communicates with the other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the exemplary embodiments of the present disclosure.
Furthermore, the above-described figures are merely schematic illustrations of processes included in methods according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functions of two or more modules or units described above may be embodied in one module or unit, according to exemplary embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the following claims.
Claims (12)
1. A method for processing a service, comprising:
acquiring service state data of each demand party at each preset time in a service period;
determining service input data of the target demand party at the current preset moment according to the service state data of each demand party and service configuration information aiming at the target demand party, and distributing service resources for the target demand party according to the service input data;
and updating the service configuration information by using the service feedback data of the target demand party at the next preset time.
2. The method of claim 1, wherein the service configuration information comprises a priority of each service candidate investment data under different service status data;
the determining the service input data of the target demand party at the current scheduled time according to the service state data of each demand party and the service configuration information aiming at the target demand party comprises:
searching the priority of corresponding service candidate input data according to the service state data of each demand party in the service configuration information;
and determining the service input data of the target demand party from the service candidate input data according to the priority of the service candidate input data.
3. The method of claim 2, wherein determining the traffic engagement data of the target demand party from the traffic candidate engagement data based on a priority of the traffic candidate engagement data comprises:
and determining the service input data of the target demand party from the service candidate input data by adopting the maximum priority according to the priority of the service candidate input data.
4. The method of claim 1, wherein the service feedback data is determined as follows:
and determining the service feedback data according to the service state data of the target demand party at the next preset time.
5. The method of claim 4, wherein the business state data includes planning data and cumulative investment data;
the determining the service feedback data according to the service state data of the target demand party at the next predetermined time includes:
and when the accumulated investment data of the target demander at the next preset time is less than or equal to the plan data, determining the service feedback data according to the ratio of the accumulated investment data to the plan data.
6. The method of claim 5, wherein the determining the service feedback data according to the service status data of the target demander at the next predetermined time comprises:
and when the accumulated investment data of the target demand side at the next preset time is larger than the plan data, determining the service feedback data according to the opposite number of the ratio of the accumulated investment data to the plan data.
7. The method according to claim 1, wherein the updating the service configuration information by using the service feedback data of the target demander at the next scheduled time comprises:
determining incremental information according to the service feedback data and experience parameters of the target demand party at the next preset time;
and updating the service configuration information according to the increment information.
8. The method of claim 1, wherein the service period is a service test period; and updating the service configuration information in a plurality of service test periods to obtain stable version service configuration information.
9. The method of claim 8, further comprising:
determining the service configuration information of a target demand party from service configuration information according to the service state data of the target demand party at any preset time in a service actual period;
and determining the service input data of the target demand party at any preset time according to the service configuration information of the target demand party.
10. A traffic processing apparatus, comprising:
the service state data acquisition module is used for acquiring service state data of each demand party at each preset time in a service period;
a service resource allocation module, configured to determine service investment data of the target demand party at a current predetermined time according to the service state data of each demand party and service configuration information for the target demand party, and allocate service resources to the target demand party according to the service investment data;
and the service configuration information updating module is used for updating the service configuration information by using the service feedback data of the target demand party at the next preset time.
11. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method of any one of claims 1 to 9.
12. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the method of any of claims 1 to 9 via execution of the executable instructions.
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