CN113467847A

CN113467847A - Service data processing method and device

Info

Publication number: CN113467847A
Application number: CN202110814367.7A
Authority: CN
Inventors: 曹慧霞; 洪楷; 徐士立; 李孝宁; 张廷进; 吴海洋; 刘专; 胡凡; 刘江冬
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2019-01-29
Filing date: 2019-01-29
Publication date: 2021-10-01
Also published as: CN109814933A; CN109814933B

Abstract

The embodiment of the invention discloses a method and a device for processing service data, wherein the method comprises the following steps: the method comprises the steps that a server obtains a target user state sent by a terminal device, and a target performance data set aiming at a target service is obtained based on the target user state; determining a target condition probability value corresponding to at least one performance attribute in the target service respectively according to the target performance data set, and generating performance attribute configuration information for the terminal equipment according to the target condition probability value; and sending the performance attribute configuration information to the terminal equipment so that the terminal equipment performs initialization setting on at least one performance attribute in the target service based on the performance attribute configuration information. By adopting the embodiment of the invention, the attribute options after the initialization setting can be matched with the actual performance of the terminal equipment.

Description

Service data processing method and device

The present application is a divisional application of a chinese patent application filed on 29/1/2019 under the name of "a service data processing method and apparatus", with the application number of 201910086897.7, and the entire contents of the application are incorporated by reference in the present application.

Technical Field

The present invention relates to the field of communications, and in particular, to a method and an apparatus for processing service data.

Background

With the popularization of internet technology and intelligent devices, the frequency of users handling daily services through terminal devices is increasing, and the frequency has become an indispensable user demand.

In the prior art, when a user uses a terminal device to process an application of an entertainment service type, initialization setting is mainly performed on application attribute options (such as attribute options of application resolution, definition and the like) under different terminal device models through human experience, so that the consideration factor of the initialization setting is single, and the initialization setting has great limitation, so that the initialization setting of the application is unreasonable, and the attribute options after the initialization setting cannot be matched with the actual performance of the terminal device easily.

Disclosure of Invention

Embodiments of the present invention provide a method and an apparatus for processing service data, which enable an attribute option after initialization to be matched with actual performance of a terminal device.

One aspect of the present invention provides a method for processing service data, which is applied to a server and includes:

acquiring a target user state sent by terminal equipment, and acquiring a target performance data set aiming at a target service based on the target user state;

determining a target condition probability value corresponding to at least one performance attribute in the target service respectively according to the target performance data set, and generating performance attribute configuration information for the terminal equipment according to the target condition probability value;

and sending the performance attribute configuration information to the terminal equipment so that the terminal equipment performs initialization setting on at least one performance attribute in the target service based on the performance attribute configuration information.

Another aspect of the present invention provides a method for processing service data, where the method is applied to a terminal device, and includes:

sending a target user state to a server so that the server acquires a target performance data set aiming at a target service based on the target user state, and generating performance attribute configuration information for the terminal equipment according to the target performance data set; the performance attribute configuration information is determined by a target condition probability value corresponding to at least one performance attribute in the target service respectively;

and receiving the performance attribute configuration information, and performing initialization setting on at least one performance attribute in the target service based on the performance configuration information.

Another aspect of the present invention provides a service data processing apparatus, including:

the data set acquisition module is used for acquiring a target user state sent by the terminal equipment and acquiring a target performance data set aiming at a target service based on the target user state;

a configuration information generating module, configured to determine, according to the target performance data set, a target condition probability value corresponding to at least one performance attribute in the target service, and generate performance attribute configuration information for the terminal device according to the target condition probability value;

a configuration information sending module, configured to send the performance attribute configuration information to the terminal device, so that the terminal device performs initialization setting on the at least one performance attribute in the target service based on the performance attribute configuration information.

Another aspect of the present invention provides another service data processing apparatus, including:

a user state sending module, configured to send a target user state to a server, so that the server obtains a target performance data set for a target service based on the target user state, and generates performance attribute configuration information for the terminal device according to the target performance data set; the performance attribute configuration information is determined by a target condition probability value corresponding to at least one performance attribute in the target service respectively;

and the performance attribute setting module is used for receiving the performance attribute configuration information and carrying out initialization setting on at least one performance attribute in the target service based on the performance configuration information.

Another aspect of the present invention provides a service data processing apparatus, including: a processor and a memory;

the processor is connected to a memory for storing program code, and the processor is configured to invoke the program code to perform the method according to one/another aspect of an embodiment of the invention.

Another aspect of embodiments of the present invention provides a computer storage medium storing a computer program comprising program instructions that, when executed by a processor, perform a method according to one/another aspect of embodiments of the present invention.

According to the embodiment of the invention, the user state of the login user is detected, the target performance data set aiming at the target service in the corresponding time range is obtained based on the user state, the target condition probability values respectively corresponding to a plurality of performance attributes in the target service can be determined according to the data information in the target performance data set, and further the performance attribute configuration information can be generated for the terminal equipment, so that the terminal equipment can carry out initialization setting on the performance attributes in the target service based on the performance attribute configuration information, and in consideration of the historical data information of the user aiming at the target service, compared with the initialization setting only through artificial experience, the attribute option after initialization setting can be matched with the actual performance of the terminal equipment.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic view of a scenario of a service initialization setting process according to an embodiment of the present invention;

fig. 2 is a timing diagram of a service data processing method according to an embodiment of the present invention;

fig. 3 is a schematic diagram of a target service initialization setting timing sequence according to an embodiment of the present invention;

fig. 4 is a timing diagram of another service data processing method according to an embodiment of the present invention;

5 a-5 c are schematic diagrams of a real-time calculation framework for target service data according to an embodiment of the present invention;

fig. 6 is a schematic flowchart of a service data processing method according to an embodiment of the present invention;

fig. 7 is a schematic flowchart of another service data processing method according to an embodiment of the present invention;

fig. 8 is a schematic flowchart of another service data processing method according to an embodiment of the present invention;

fig. 9 is a schematic diagram of a framework of a service data processing method according to an embodiment of the present invention;

fig. 10 is a schematic structural diagram of a service data processing apparatus according to an embodiment of the present invention;

fig. 11 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention;

fig. 12 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention;

fig. 13 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

Referring to fig. 1, fig. 1 is a schematic view of a scenario of a service initialization setting process according to an embodiment of the present invention. As shown in fig. 1, a user may open a service processing application, that is, a client, from a terminal device 200, first, a service initial login interface is displayed on a display interface of the terminal device 200, and for a user performing service processing for the first time, that is, the user state of the user is a cold start user, registration information (for example, information such as an account, a password, and a user name) needs to be filled in for registration. After the user is successfully registered, before starting to perform service processing, the terminal device 200 may send a cold start state of the user to the server 100, and the server 100 may obtain, based on the cold start state, performance parameters of all users performing the service processing in the previous week from a database to form a performance data set, where the performance parameters of each user in the performance data set may include data of a client corresponding to the user (e.g., an operation state of the service, settings for each attribute of the service, and the like) and device performance index data (e.g., a CPU usage rate, a service usage memory, a device idle memory, a device frequency reduction temperature, and the like). Based on the performance parameters of the users in the performance data set, spark (a fast and general calculation engine involved for large-scale data processing) may be used in combination with bayesian theorem to calculate, offline, a conditional probability value corresponding to each attribute in the service under the condition that the operation state of the service is a smooth state in each model, so as to determine an attribute corresponding to a maximum conditional probability value in each attribute type, thereby generating performance attribute configuration information, the server 100 may send the performance attribute configuration information to the terminal device 100, and the terminal device 100 may perform initialization setting for each performance attribute in the service processing process of the user based on the performance attribute configuration information. For example, the attribute types in the service include three types, namely image quality, high-definition display and high-frame-rate mode, the image quality includes three attributes, namely high, medium and low, the high-definition display includes two attributes, namely off and on, the high-frame-rate mode includes two attributes, namely off and on, the condition probability values corresponding to the 7 attributes can be obtained based on the performance data set, namely condition probability value 1, condition probability value 2, … … and condition probability value 7, if the maximum condition probability values in the attribute types are respectively condition probability value 2, condition probability value 4 and condition probability value 6, the generated performance attribute configuration information is medium image quality in the image quality attribute types, high-definition display is turned off in the high-definition attribute types, and the high-frame-rate mode is turned off in the high-frame-rate mode attribute types; the terminal equipment can carry out initialization setting on the service according to the received performance attribute configuration information and display the service on a display interface. The terminal device can comprise a mobile phone, a tablet computer, a notebook computer and a palm computer.

Referring to fig. 2, fig. 2 is a timing diagram of a service data processing method according to an embodiment of the present invention. As shown in fig. 2, the method may include:

step S201, the terminal equipment sends the state of a target user to a server;

specifically, when a terminal device opens a target service client (such as a mobile client), a terminal display interface displays an initial login interface of the target service client, a target user (a user corresponding to the terminal device is referred to as a target user herein) can perform an input operation (for example, input an account and a password) on the login interface, the terminal device can determine a target user state of the target user based on the operation of the target user and send the target user state to a server, where the target user state may include a cold start state and a hot start state, for example, when the terminal device detects that account information of the target user is stored in local data, the target user state may be determined as the hot start state, and when the account information of the target user is not detected, the target user state is determined as the cold start state.

Step S202, the server obtains a target performance data set aiming at the target service based on the state of the target user;

specifically, after receiving the target user state, the server may obtain data corresponding to the target user state from a database (storing service performance parameters of all users and corresponding terminal devices for the target service), as a target performance data set, where the target performance data set is a performance parameter selected from the database within a certain time period. Taking a hand game as an example, the server may obtain, from the database, all user data of a certain user or multiple users when playing the hand game based on different target user states, where the user data may include performance parameters of devices of the users playing the hand game, parameter setting conditions of each game in the game process, network states, fluency of the game, and the like.

Step S203, the server determines a target condition probability value corresponding to at least one performance attribute in the target service according to the target performance data set, and generates performance attribute configuration information for the terminal equipment according to the target condition probability value;

specifically, because the amount of the data in the target performance data set obtained in the foregoing manner is large, the server may use spark to perform parallel processing on the data in the target performance data set, and may improve the efficiency of large-scale data processing. The server can count the times that the multiple performance attributes in the target service in the target performance data set are respectively used and the times that the running state of the target service is in a fluent state, and further can determine the possibility that the running state of the target service is in the fluent state in the target performance data set, so that the target condition probability value corresponding to each performance attribute respectively, namely the possibility that each performance attribute is used can be calculated on the premise that the running state of the target service is in the fluent state. And generating performance attribute configuration information for the terminal equipment according to the target condition probability value of each performance attribute. For example, there are 3 performance attribute types in the target service, which are respectively a performance attribute type 1, a performance attribute type 2, and a performance attribute type 3, where the performance attribute type 1 includes a performance attribute 1, a performance attribute 2, and a performance attribute 3, the performance attribute type 2 includes a performance attribute 4 and a performance attribute 5, and the performance attribute type 3 includes a performance attribute 6 and a performance attribute 7; the server can calculate the target condition probability values respectively corresponding to the 7 individual performance attributes on the premise that the running state of the target service is a smooth state; if the performance attribute with the maximum target condition probability value in the performance attribute type 1 is the performance attribute 1, the performance attribute with the maximum target condition probability value in the performance attribute type 2 is the performance attribute 5, and the performance attribute with the maximum target condition probability value in the performance attribute type 3 is the performance attribute 7, performance attribute configuration information can be generated for the terminal device based on the performance attribute 1, the performance attribute 5, and the performance attribute 7, that is, the performance attribute 1, the performance attribute 5, and the performance attribute 7 are recommended for the terminal device as the initialization setting of the target service.

Step S204, the server sends performance attribute configuration information to the terminal equipment;

specifically, the server may send the generated performance attribute configuration information to the middle terminal device, and specifically may send the generated performance attribute configuration information to an optimization policy module for the target service in the terminal device, where the optimization policy module may trigger the initialization setting of the target service according to whether the received performance attribute configuration information triggers the initialization setting of the target service.

Step S205, the terminal device performs initialization setting on the at least one performance attribute in the target service based on the performance configuration information.

Specifically, the terminal device may display, on a device display interface, the performance attribute setting corresponding to the performance attribute configuration information after receiving the performance attribute configuration information.

Referring to fig. 3, fig. 3 is a timing diagram of initialization setting of a target service according to an embodiment of the present invention. As shown in fig. 3, taking the hand game as an example, the initialization setting process may include:

step S301, the server obtains initial game setting;

specifically, the hand game client may include an optimization policy module, where the optimization policy module includes all performance attribute option settings in the hand game, and when the target user opens the hand game client, the server may obtain the performance attribute option settings (e.g., the definition options of the hand game) in the hand game from the optimization policy module, and through the descriptions of step S201 to step S203 in the embodiment corresponding to fig. 2, the server may recommend the initialization settings for the performance attribute options in the hand game.

Step S302, the optimization strategy module at the client returns the setting;

specifically, the server may send the recommended performance attribute initialization setting to the optimization policy module of the mobile client, and may return to the performance attribute option setting interface of the mobile client.

Step S303, the optimization strategy module is updated regularly;

specifically, the optimization policy module may trigger a performance attribute option setting optimization request at regular time, so as to update the performance attribute option setting in the hand game.

Step S304, an optimization strategy module in the client triggers a strategy to a client interface to request adjustment;

specifically, after receiving the performance attribute initialization setting sent by the server, the optimization policy module may trigger a policy to request the mobile client interface to adjust the performance attribute option setting.

Step S305, the client interface carries out policy check;

specifically, after receiving the request adjustment of the optimization policy module, the client interface may check the performance attribute initialization setting, and perform a preliminary screening.

Step S306, the client interface adjusts and recommends test sending strategy configuration to the client;

specifically, after the check is passed, the performance attribute initialization setting may be sent to the client to adjust the recommended test.

Step S307, the client adjusts the recommended test and returns the adjustment result to the optimization strategy module.

Specifically, after receiving the performance attribute initialization setting, the client adjusts the recommendation test, and then detects, in the background, that the mobile game sets the performance attribute according to the performance attribute initialization setting, and then the degree of matching between the initialization setting and the terminal device is set, and if the degree of matching is good (if the degree of matching is higher than 80%), the client may return a confirmation result to the optimization policy module through the mobile game client interface, and if the degree of matching is low (if the degree of matching is lower than 30%), the client may adjust the performance attribute initialization setting, and return the adjusted result to the optimization policy module through the mobile game client interface.

The method comprises the steps of obtaining a target user state sent by a terminal device through a server, obtaining a target performance data set aiming at a target service in a corresponding time range from a database based on the target user state, determining target condition probability values respectively corresponding to a plurality of performance attributes in the target service according to data information in the target performance data set, and further generating performance attribute configuration information for the terminal device, so that the terminal device initializes the performance attributes in the target service based on the performance attribute configuration information, and compared with the method of initializing only through artificial experience, the method can enable attribute options after initialization to be matched with the actual performance of the terminal device in consideration of the difference of users and historical data information of the users aiming at the target service.

Referring to fig. 4, fig. 4 is a timing diagram of another service data processing method according to an embodiment of the present invention. The method can comprise the following steps:

step S401, the terminal equipment sends the target user state to a server;

step S402, the server obtains a target performance data set aiming at the target service based on the state of the target user;

step S403, the server determines a target condition probability value corresponding to at least one performance attribute in the target service according to the target performance data set, and generates performance attribute configuration information for the terminal device according to the target condition probability value;

step S404, the server sends performance attribute configuration information to the terminal equipment;

for a specific implementation manner of steps S401 to S404, refer to the description of steps S201 to S204 in the embodiment corresponding to fig. 2, which is not described herein again.

Step S405, the terminal device displays the performance attribute configuration information on a screen, and when a second confirmation response aiming at the performance attribute configuration information is detected, the terminal device performs initialization setting on at least one performance attribute based on the second confirmation response and the performance attribute configuration information;

specifically, the terminal device may display the received performance attribute configuration information on a display interface of the client, and a target user corresponding to the terminal device may confirm or adjust the performance attribute configuration information on the display interface, and when the terminal device detects a confirmation response of the target user for the performance attribute configuration information, that is, the target user has already confirmed or adjusted the performance attribute configuration information, each performance attribute in the target service may be initialized and set based on the confirmation response of the target user and the performance attribute configuration information.

Step S406, the terminal equipment acquires a plurality of unit service information related to the target service, and determines the running state of the target service based on each unit service information;

specifically, after each performance attribute in the target service is initialized, the terminal device may start processing the target service, and after one unit service is processed and before the next unit service is processed, the terminal device may collect the processed unit service information, and according to the unit service information, may determine the operation state of the completed unit service. The Unit service information may include setting conditions of each performance attribute in the target service, an average value of usage rates of Central Processing Units (CPUs) in the Unit service Processing process, a maximum value of the usage rates of the CPUs, a minimum value of the usage of the CPUs, a maximum value of battery temperatures of the devices, a minimum value of down-conversion temperatures, a Frame Per Second (FPS) jitter rate, a low FPS Frame rate, whether the FPS is stuck, a minimum value of remaining memory of the devices, a memory used by the target service, an area where the terminal device is located, and a service scene ID of the Unit service. Taking a hand game as an example, the unit service may refer to data of each game pair, and each piece of collected data is a behavior record of the user, so that data in one game is required to be used as a calculation unit according to the user identifier and a map identifier in the game, data features are summarized, settings such as game image quality, a high frame rate mode, high definition display and the like, device performance parameters and the like are included, that is, the obtained game data is preprocessed, and based on the data features in the game pair, an operation state (smooth or stuck) of the game can be determined.

Step S407, if the running state of the target service is a stuck state, acquiring available device resources of the terminal device and service demand resources corresponding to the target service, and determining recommended configuration information of the target service based on the performance attribute configuration information, the available device resources and the service demand resources;

specifically, if the running state of the unit service in the target service is a stuck state, the terminal device may obtain available device resources of the device (that is, the minimum value of the remaining CPU and the remaining device memory in the device except for the maximum value of the CPU used in the device), and service requirement resources of the target service (that is, resources required for the running state of the target service to reach a smooth state from the stuck state in the device in the service scene where the service scene ID is located); if the device cannot provide the service demand resource for the target service, lower recommended configuration information can be provided for the target service based on the performance attribute configuration information, that is, the performance priority of the performance attribute configuration information is greater than that of the recommended configuration information. Taking a hand game as an example, if the game state of a certain game is a pause state, judging whether the equipment (such as a mobile phone) has the remaining CPU and memory for game calling, if so, acquiring the required resource of the equipment model in the scene according to the game scene ID of the game, and loading the equipment resource for the game so as to enable the game to reach a smooth state; if not, the target service is set to be reduced, for example, the image quality is reduced, based on the setting of the game (i.e., the performance attribute configuration information).

Optionally, the available device resources and the service requirement resources may be calculated by an ai (intelligent intelligence) chip in the terminal device, and whether to adjust the performance attribute configuration information in the target service is determined according to the calculation result.

Step S408, if the running state of the target service is a smooth state, generating recommended configuration information of the target service according to the information of each unit service;

specifically, if the running state of the unit service in the target service is a smooth state, the probability that each performance attribute in the target service is used can be calculated by using an AI chip in the terminal device according to the unit service information collected by the device, and the performance attribute with the highest probability in each performance attribute type is determined as the recommended configuration information. Taking a hand game as an example, after a certain game is finished, the AI chip in the device can calculate the game data collected by the device to obtain an ideal setting condition in the game, and compared with the actual setting condition of the game, whether the game setting needs to be adjusted can be judged to achieve the best game effect in the same game scene.

Step S409, the terminal device displays the recommended configuration information on a screen, and when a first confirmation response aiming at the recommended configuration information is detected, attribute setting is carried out on at least one performance attribute based on the first confirmation response and the recommended configuration information.

Specifically, after the recommended configuration information of the target service is determined, a prompt window related to the recommended configuration information may be displayed on a display interface of the terminal device, the target user may perform a confirmation operation on the display interface, and when the terminal device detects a confirmation response of the target user with respect to the recommended configuration information, the terminal device may perform attribute setting on each performance attribute in the target service based on the confirmation response and the recommended configuration information.

Please refer to fig. 5a together, which is a schematic diagram of a real-time calculation framework for target service data according to an embodiment of the present invention, as shown in fig. 5a, taking a game as an example, a game initialization state 401 may be implemented through steps S401 to S405 in the embodiment corresponding to fig. 4, which is not repeated here, after a game is initialized, when a target user plays the game, a data acquisition module in a mobile phone may acquire game data of the target user in real time and store the acquired data in a game database 402, after the target user plays a game, an AI chip in the mobile phone may acquire game data 403 of a previous game of the target user from the game database 402, which may include a game mode, a frame rate, a scene, a display mode, a resolution, power consumption, and the like, and perform a card pause calculation 407 of the game based on the game data 403 of the previous game, the AI chip may also obtain a mobile phone performance parameter 405 from a mobile phone hardware database 406, which may include a CPU, a GPU, a memory, an IO bandwidth, a network traffic, a battery power, a power consumption, and the like, and may perform a temperature calculation 409 of a game based on the mobile phone performance parameter 405, and the AI chip may calculate a resource 404 required by the game in real time based on the game data 403 in the previous round and the mobile phone performance parameter 405, which may include a CPU, a Graphics Processing Unit (GPU), a memory consumption, and the like required by the game.

If the calculation result of the morton calculation 407 is that the previous game of the user is in a morton state, the available resources of the mobile phone and the resources 404 required by the game in the performance parameters 405 of the mobile phone can be obtained, when the available resources of the mobile phone are greater than the resources 404 required by the game, the bayesian probability calculation 408 is not needed to be executed, the real-time popup window optimization strategy 410 is directly executed, the available resources of the mobile phone are called for the game, an interface prompt window as shown in fig. 5a is displayed on the mobile client, and the user can confirm the game by clicking a cancel button or a confirm button on the display interface; when the available resources of the mobile phone are less than or equal to the resources 404 required by the game, the bayesian probability calculation 408 may not be executed, the real-time popup optimization policy 410 is directly executed for the performance-reducing attribute setting of the game, the interface prompt window shown in fig. 5b is displayed on the mobile client, and the user can perform the confirmation operation by clicking the "cancel" button or the "confirm" button on the display interface, so as to achieve the purpose of reducing the image quality.

If the calculation result of the katon calculation 407 is that the previous game of the user is in a smooth state, the AI chip may perform bayesian probability calculation 408 based on the katon calculation 407, the temperature calculation 409, and the game data 403 of the previous game to obtain the corresponding optimal attribute setting in the game (i.e. the best game effect can be achieved in the same game scene), then a prompt window as shown in fig. 5c may be displayed in the display interface of the mobile client, and the target user may perform a confirmation operation by clicking a "cancel" button or a "confirm" button on the display interface to determine whether to adjust the attribute setting in the target service.

The method and the device for processing the unit business acquire the state of the target user sent by the terminal device through the server, acquire the target performance data set aiming at the target business in the corresponding time range from the database based on the state of the target user, and generate the performance attribute configuration information for the terminal device according to the target performance data set, so that the terminal device can initialize and set the performance attribute in the target business based on the performance attribute configuration information. Therefore, the terminal equipment can provide diversified initialization settings for the target service according to the state of the target user, and can adjust the attribute settings of the target service in real time according to the available equipment resources of the terminal equipment, so that the dynamic optimization of the equipment resources is realized.

Referring to fig. 6, fig. 6 is a schematic flowchart of a service data processing method according to an embodiment of the present invention. As shown in fig. 6, the method may include:

step S601, a server acquires a target user state sent by a terminal device, and if the target user state is a cold start state, service performance parameters of all users associated with the target service in a first time range are determined as a target performance data set;

specifically, the server may receive a target user state sent by the terminal device, and if the target user state is a cold start state, that is, the target user corresponding to the terminal device first installs and registers the target service, the server may obtain service performance parameters of all users associated with the target service within the previous week from the database, and determine the obtained service performance parameters as a target performance data set. Taking a hand game as an example, if a target user corresponding to a terminal device first installs and registers the hand game, the state of the target user is a cold start state, and the server can acquire relevant data of all users who have logged in the hand game in the previous week from an official database of the hand game, wherein the relevant data may include network data in a game process, performance parameters of devices used by the users, various setting parameters of a client of the hand game, and the like.

Step S602, obtaining frame rate sets respectively corresponding to each model from the target performance data set; the frame rate set comprises a plurality of frame rate subsets, and the plurality of frame rate subsets are determined by a plurality of unit service information associated with the target service;

specifically, after the target performance data set is obtained, the target performance data set may be divided according to machine types to obtain frame rate sets (FPS sets) corresponding to each machine type, that is, each machine type corresponds to one FPS set, each FPS set may include a plurality of FPS subsets, and one FPS subset may be determined by one unit service information associated in the target service. Taking a hand game as an example, each FPS set can represent game performance parameters under each device model (such as a mobile phone model), and for a game of game type, each FPS subset can represent all FPS values generated in a complete game according to a time sequence; for non-game-play type games, each subset of FPSs may represent all of the FPS values generated in a time series within the same game scene ID. The FPS acquisition frequency is 5 seconds per point, i.e., one FPS value is obtained every 5 seconds.

Step S603, dividing each frame rate subset in the frame rate set to obtain a plurality of frame rate groups corresponding to each frame rate subset;

specifically, the FPS subsets in the FPS set may be divided, and the FPS values in each FPS subset are divided into a plurality of FPS groups according to the collection time sequence. For example, if a subset of FPSs has 20 FPS values, and the subset of FPSs is divided into 5 groups, each FPS group can include 4 FPS values. It should be noted that, taking hand-game as an example, the number of FPS groups divided by each FPS subset may be adjusted for different game services, and the larger the number of divided FPS groups is, the larger the influence on the subsequent katon score is. For example, for two different game services, a and B, each subset of FPSs associated with the a game service can be divided into 6 groups and each subset of FPSs associated with the B game service can be divided into 5 groups.

Step S604, generating a frame rate average value corresponding to each frame rate subset, and determining an average weight and a variance weight corresponding to each frame rate subset based on the frame rate groups and the frame rate average value;

specifically, the FPS average value corresponding to each of the FPS subsets may be calculated, and according to the FPS average value, the average weight of the FPS subset corresponding to the FPS average value may be generated, where the value range of the average weight may be [0.1, 1], and the specific calculation manner may be represented as:

wherein MEAN may be expressed as an FPS average value, MEAN _ factor may be expressed as an average value weight, MEAN _ THRESHOLD _1 (average THRESHOLD 1) and MEAN _ THRESHOLD _2 (average THRESHOLD 2) are two boundary values, FPS average value may be divided into three different gears, a lower gear when the average value is smaller than MEAN _ THRESHOLD _1, a middle gear when the average value is between MEAN _ THRESHOLD _1 and MEAN _ THRESHOLD _2, a higher gear when the average value is larger than MEAN _ THRESHOLD _2, setting of the boundary values mainly considers the highest frame of traffic and the own characteristics of the client performing the target traffic processing, MEAN _ co _ x and MEAN _ interrupt _ x (x may be 1 or 2) as parameters in order to ensure that the final average value weight is proportional to the FPS average value, and the lower gear is dominant in the final score calculation at the lower gear.

The variance corresponding to each of the plurality of FPS groups may be calculated, and the variance weight of the FPS subset corresponding to each of the plurality of FPS groups may be generated according to the variance of each FPS group, where the specific calculation formula of the variance weight is:

wherein, the variance in the above formula (1)_iVariance, var _ score, representing FPS packets_iRepresents the weights of the FPS packets, and sum _ var _ score represents the sum of the weights of the FPS packets, i.e.Weight of a subset of FPS, N_splitThe number of FPS packets is represented, VAR _ MIN represents a variance threshold, the threshold is a minimum fluctuation variance set for a target service performance, that is, the variance threshold affects a user only when the fluctuation variance of the FPS is greater than VAR _ MIN within a small interval, the variance threshold is adjusted for different unit service requirements in actual conditions, VAR _ COEF is a parameter, and the larger the parameter is, the larger the variance affects the final stuck score.

Step S605, generating a pause mark corresponding to each frame rate subset according to the average weight and the variance weight;

specifically, based on the average weight and the variance weight, a katon score corresponding to each FPS subset can be obtained, where a numeric range of the katon score is [1, 100], and a specific calculation manner can be expressed as:

score＝max(mean_factor×(100-sum_var_score),1.0) (2)

the above calculation equation (2) ensures that the final stuck score is proportional to the FPS mean and inversely proportional to the FPS variance. Based on the katton score, a katton mark corresponding to each FPS subset can be generated, and the calculated katton score is smaller than the katton score threshold and can be marked as a katton point by setting a katton score threshold.

Step S606, generating a first probability value corresponding to each model according to the Catton mark;

specifically, the stuck condition of the unit service corresponding to each FPS subset can be known according to the obtained stuck marks corresponding to each FPS subset. According to the number of the stuck marks of all the FPS subsets in each model, the proportion of the number of the FPS subsets with the stuck marks to all the FPS subsets can be obtained, namely the probability value that the running state of the unit service is the stuck state, and the probability value that the running state is the smooth state, namely the first probability value, can be obtained according to the probability value that the running state is the smooth state because the running state is the stuck state and the smooth state are two events which are independent mutually.

Step S607, determining attribute probability parameters respectively corresponding to the at least one performance attribute according to the target performance data set, and determining conditional attribute probability parameters of which the attribute running state respectively corresponding to each performance attribute is a smooth state; the attribute running state corresponding to one performance attribute is the running state of the target service when the performance attribute is set;

specifically, according to the target performance attribute data set, the number of times each performance attribute in the target service is used in the model to which the terminal device belongs may be counted, so that the attribute probability parameter corresponding to each performance attribute may be set, and the conditional attribute probability parameter that the running state of the target service is a smooth state in the target service under the condition that any performance attribute is set may be further obtained. Taking a hand trip as an example, assuming that three setting types of image quality setting, high-definition display and high-frame-rate mode are set on the basis of the hand trip, the image quality is provided with three high, medium and low gears, the high-definition display has two on and off gears, and the high-frame-rate mode has two on and off gears, the probabilities that the high-image quality, the medium-image quality, the low-image quality, the high-definition display on, the high-definition display off, the high-frame-rate mode on and the high-frame-rate mode off are set in the model to which the terminal device belongs can be determined according to the acquired hand trip data, and the conditional probability that the game is in a smooth state is set on the premise that each attribute is set.

Step S608, determining a target conditional probability corresponding to the at least one performance attribute in each attribute type in the at least one attribute type according to the first probability value, the attribute probability parameter, and the conditional attribute probability parameter;

specifically, after determining the first probability value corresponding to each model of the plurality of models, the first probability value that the operation state of the target service in the model to which the terminal device belongs is in a smooth state may be determined, and based on the condition, the attribute probability parameter and the conditional attribute probability parameter, the target condition probability value corresponding to each performance attribute may be calculated by using bayesian theorem. Taking a hand game as an example, the label of whether the game is smooth can be expressed as: { fast: fluency, slow: katton, the label of the image quality can be represented as pic, the low image quality is represented as 0, the medium image quality is represented as 1, the high image quality is represented as 2, the label of the high frame rate display can be represented as high frame mode, the label of the high frame rate display is closed is represented as 0, the label of the high frame rate display is opened is represented as 1, the label of the high definition display can be represented as resolution, the label of the high definition display is closed is represented as 0, the label of the high definition display is opened is represented as 1, the conditional probability corresponding to the high image quality in the smooth game state is calculated according to the Bayesian theorem, and the conditional probability can be represented as:

in the above formula (3), P (label ═ fast ') may indicate a first probability value that the user is smooth when playing the game in the model to which the terminal device belongs, P (pic ═ 2') may indicate a probability value set by the high image quality, and P (label ═ fast '| pic ═ 2') indicates a conditional probability value that the game is smooth when the high image quality is set.

The conditional probability corresponding to the image quality in the smooth game state is calculated and can be expressed as:

in the above formula (4), P (pic ═ 1 ') may represent a probability value of the middle picture quality setting, and P (label ═ fast ' | pic ═ 1 ') represents a conditional probability value of the smoothness of the game in the case of the middle picture quality setting.

The conditional probability corresponding to the low image quality in the smooth game state is calculated and can be expressed as:

in the above formula (5), P (pic ═ 0 ') may represent a probability value set by the low image quality, and P (label ═ fast ' | pic ═ 0 ') represents a conditional probability value for smooth game when the low image quality is set.

Calculating the conditional probability corresponding to turning off the high frame rate mode in the game fluency state can be expressed as:

in the above formula (6), P (highframe mode ═ 0 ') may represent a probability value for turning off the high frame rate mode, and P (label ═ fast ' | highframe mode ═ 0 ') represents a conditional probability value for smooth game when the high frame rate mode is turned off.

Calculating the conditional probability corresponding to the high frame rate mode being started in the game fluent state can be represented as:

in the above formula (7), P (highframe mode ═ 1 ') may represent a probability value for turning on the high frame rate mode, and P (label ═ fast ' | highframe mode ═ 1 ') represents a conditional probability value for smooth game in the case of turning on the high frame rate mode.

Calculating the conditional probability corresponding to starting high-definition display in the game fluent state can be expressed as:

in the above formula (8), P (resolution ═ 1 ') may represent a probability value for turning on the high definition display, and P (label ═ fast ' | resolution ═ 1 ') represents a conditional probability value for smooth game in the case of turning on the high definition display.

Calculating the conditional probability corresponding to the turning off of the high-definition display in the game fluency state can be expressed as:

in the above formula (9), P (resolution ═ 0 ') may represent a probability value for turning off the high definition display, and P (label ═ fast ' | resolution ═ 0 ') represents a conditional probability value for smooth game play when the high definition display is turned off.

Step S609, generating performance attribute configuration information of the terminal equipment according to the performance attribute with the maximum target condition probability value in each attribute type;

specifically, by comparing the target conditional probability values corresponding to the performance attributes in each attribute type, the performance attribute having the maximum target conditional probability in each attribute type can be determined, and the performance attribute configuration information is generated. Taking a tour as an example, by comparing the target condition probability values corresponding to the three image quality levels in the image quality settings, the setting corresponding to the maximum target condition probability value (assuming medium image quality) is obtained, and in the same manner, the setting corresponding to the maximum target condition probability value in the high definition display and the high frame rate mode can be determined (assuming that the high definition display is turned off and the high frame rate mode is turned off), and the medium image quality, the high definition display is turned off and the high frame rate mode is determined as the performance attribute configuration information.

Step S610, sending the performance attribute configuration information to the terminal device, so that the terminal device performs initialization setting on the at least one performance attribute in the target service based on the performance attribute configuration information.

The specific implementation manner of step S610 may refer to the description of step S204 in the embodiment corresponding to fig. 2, and is not described herein again.

The embodiment of the invention obtains the cold start state sent by the terminal equipment through the server, determines the service performance parameters of all users associated with the target service in the time range of the previous week in the database as the target performance data set, determines the first probability that the running state of the target service in each machine type in a plurality of machine types is in a smooth state according to the data information in the target performance data set, further determines the target condition probability values respectively corresponding to a plurality of performance attributes in the target service, and can generate performance attribute configuration information for the terminal equipment according to the performance attribute corresponding to the maximum target condition probability value in each performance attribute type, so that the terminal equipment can initialize the performance attributes in the target service based on the performance attribute configuration information, and the difference of the terminal equipment and the historical data information of the users are fully considered, compared with the method for initializing through only human experience, the method for initializing the terminal equipment enables the attribute options after initialization to be matched with the actual performance of the terminal equipment.

Referring to fig. 7, fig. 7 is a schematic flowchart of another service data processing method according to an embodiment of the present invention. As shown in fig. 7, the method may include:

step S701, a server acquires a target user state sent by a terminal device, and if the target user state is a hot start state, service performance parameters of a target user corresponding to the terminal device in a second time range are determined as a target performance data set;

specifically, the server may receive a target user state sent by the terminal device, and if the target user state is a cold start state, that is, a log data record of a target user (a user corresponding to the terminal device is referred to as a target user) exists in the terminal device, the server may obtain, from a database, a service performance parameter associated with the target user in a previous day, and determine the obtained service performance parameter as a target performance data set. Taking a mobile game as an example, if a game data record of a target user exists in a terminal device, the state of the target user is a hot start state, a server may obtain, from an official database of the mobile game, related game data of the user playing the mobile game on the previous day, if the target user has no data record on the previous day, that is, the target user has not played a game on the previous day, the related game of the mobile game played by the target user on the last day may be obtained, and if the game record of the target user on the last day is 15 game records, the data of the 15 games of the target user may be obtained.

Step S702, determining a second probability value corresponding to the terminal equipment according to the target performance data set; the second probability value is a probability value that the running state based on the target service in the terminal equipment is a smooth state;

specifically, for a target performance data set acquired by a target user in a hot-start state, a second probability value that an operation state of a target service in the terminal device is in a smooth state may be determined, and a specific calculation manner may refer to a calculation manner of the first probability value in steps S602 to S606 in the embodiment corresponding to fig. 6, which is not described herein again.

Step S703, determining a target conditional probability value corresponding to the at least one performance attribute in each attribute type in the at least one attribute type, respectively, based on the second probability value, and determining first candidate configuration information corresponding to a maximum target conditional probability value in each attribute type;

specifically, based on the second probability value, a target condition probability value corresponding to each performance attribute in the target service may be determined, and based on the target condition probability value, the first candidate configuration information in the target service may be determined. The generation manner of the first candidate configuration information may refer to the description of the generation manner of the performance attribute configuration information in steps S607 to S609 in the embodiment corresponding to fig. 6, and is not described herein again.

Step S704, obtaining default configuration information of the terminal device, and if the performance priority of the first to-be-selected configuration information is greater than the performance priority of the default configuration information, obtaining a target performance index parameter corresponding to the terminal device and a standard performance index parameter for the target service; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the terminal device is located;

specifically, the server may obtain default configuration information of the terminal device, where the default configuration information may refer to performance attribute configuration information in a latest unit service of the target user, and if the performance priority of the first to-be-selected configuration information is greater than the performance priority of the default configuration information (taking a hand trip as an example, it is assumed that an image quality in the first to-be-selected configuration information is set to be a high image quality and an image quality in the default configuration information is set to be a medium image quality), the server may obtain corresponding target performance index parameters in the terminal device and standard performance index parameters for the target service, where the target performance index parameters may include a maximum CPU usage rate, a service memory, a maximum device temperature, a minimum FPS jitter rate, and a minimum FPS low frame rate for the target service in the terminal device, and the standard performance index parameters may refer to a maximum performance index among performance index parameters of multiple devices in an operator in a province where the terminal device is located The standard parameters may include a maximum CPU utilization, a maximum service memory, a minimum down-conversion temperature, a maximum FPS jitter rate, and a maximum FPS low frame rate, which are configured higher in the same province operator.

Step S705, if the target performance parameter is less than or equal to the standard performance index parameter, determining the first to-be-selected configuration information as the performance attribute configuration information of the terminal device, otherwise determining the default configuration information as the performance attribute configuration information of the terminal device;

specifically, if the target performance parameter is less than or equal to the standard performance index parameter, that is, the maximum CPU utilization rate of the terminal device for the target service is less than or equal to the maximum CPU utilization rate higher configured in the province operator where the terminal device is located, the service memory is less than or equal to the maximum game memory higher configured in the province operator where the terminal device is located, the maximum handset temperature is less than or equal to the minimum down-conversion temperature higher configured in the province operator where the terminal device is located, the minimum FPS jitter rate is less than or equal to the maximum FPS jitter rate higher configured in the province operator where the terminal device is located, the minimum FPS low frame rate is less than or equal to the maximum FPS low frame rate higher configured in the province operator where the terminal device is located, and determining the first to-be-selected configuration information as the performance attribute configuration information of the terminal equipment, otherwise determining the default configuration information as the performance attribute configuration information of the terminal equipment.

Step S706, if the performance priority of the first to-be-selected configuration information is less than or equal to the performance priority of the default configuration information, determining the first to-be-selected configuration information as the performance attribute configuration information of the terminal device;

specifically, if the performance priority of the first to-be-selected configuration information is less than or equal to the performance priority of the default configuration information, the first to-be-selected configuration information obtained by using the bayesian theorem is directly determined as the performance attribute configuration information of the terminal device. Taking a hand game as an example, assuming that the high definition display in the first candidate configuration information is a closed high definition display and the high definition display in the default configuration information is an open high definition display, each game setting (first candidate configuration information) determined by the target condition probability value is determined as an initialization setting (performance attribute configuration information) for the game in the terminal device.

Step S707, sending the performance attribute configuration information to the terminal device, so that the terminal device performs initialization setting on the at least one performance attribute in the target service based on the performance attribute configuration information;

for a specific implementation manner of step S707, reference may be made to the description of step S204 in the embodiment corresponding to fig. 2, which is not described herein again.

The embodiment of the invention obtains the hot start state sent by the terminal equipment through the server, determines the service performance parameter of the target user corresponding to the terminal equipment in the time range of the previous day in the database as a target performance data set, determines the second probability that the running state of the target user in the target service is a fluent state according to the data information in the target performance data set, further determines the target condition probability values respectively corresponding to a plurality of performance attributes in the target service, and further generates performance attribute configuration information for the terminal equipment according to the performance attribute corresponding to the maximum target condition probability value in each performance attribute type, the target performance parameter of the terminal equipment and the standard performance index parameter in the area where the terminal equipment is located, so that the terminal equipment initializes the performance attribute in the target service based on the performance attribute configuration information, the difference of the terminal equipment and the historical data information of the user are fully considered, and compared with the method for initializing only through human experience, the method and the device can enable the attribute options after initialization to be matched with the actual performance of the terminal equipment.

Referring to fig. 8, fig. 8 is a schematic flowchart of another service data processing method according to an embodiment of the present invention. As shown in fig. 8, the method may include:

step S801, a terminal device sends a target user state to a server, so that the server acquires a target performance data set aiming at a target service based on the target user state, and generates performance attribute configuration information for the terminal device according to the target performance data set; the performance attribute configuration information is determined by a target condition probability value corresponding to at least one performance attribute in the target service respectively;

step S802, the terminal equipment receives the performance attribute configuration information, and performs initialization setting on at least one performance attribute based on the performance configuration information in the target service;

step S803, the terminal device obtains a plurality of unit service information associated with the target service, and determines the running state of the target service based on each unit service information;

step S804, if the running state of the target service is a stuck state, acquiring available equipment resources of the terminal equipment and service demand resources corresponding to the target service;

for a specific implementation manner of steps S801 to S804, reference may be made to the description of steps S401 to S407 in the embodiment corresponding to fig. 4, and details are not repeated here.

Step S805, if the available device resource is larger than the service demand resource, calling the available device resource for the target service, and determining the performance attribute configuration information as the recommended configuration information of the target service;

specifically, if the obtained available device resource is greater than the service requirement resource in the target service processing process, that is, the obtained available device resource indicates in the device that the remaining device resource is available for the target service to call, the terminal device may directly call the available device resource for the target service, and after the device resource is called, the performance attribute configuration information in the previous unit service may be directly used as the recommended configuration information for the next unit service processing in the target service. Taking a game-play-pair hand game as an example, if the game play is stuck, the remaining resources of the user equipment (e.g., a mobile phone), such as the remaining CPU and a memory, can be obtained, and the resources required for the game to run smoothly under the same scene and setting as the game play are obtained, and when the remaining resources of the equipment are greater than the resources required for the game play, the terminal equipment can load the equipment resources for the game play and continue to maintain the settings in the game play of the last game play pair.

Step S806, if the available device resource is less than or equal to the service demand resource, generating recommendation configuration information according to the performance attribute configuration; the performance priority of the recommended configuration information is smaller than that of the performance attribute configuration information;

specifically, if the obtained available device resource is less than or equal to the service requirement resource in the target service processing process, that is, it indicates that there is no remaining device resource available for the target service to call in the device, the terminal device may reduce the performance priority of the performance attribute configuration information in the target service, and determine the performance attribute configuration information after reducing the performance priority as the recommended configuration information. Taking a game-type hand game as an example, if the game is played in a game-playing manner, the remaining resources of the user equipment (e.g., a mobile phone), such as the remaining CPU and the remaining memory, can be obtained, and the resources required for the game to run smoothly under the same scene and setting as the game-playing manner are obtained.

Step S807, if the running state of the target service is a smooth state, determining a unit condition probability value corresponding to the at least one performance attribute in each attribute type in at least one attribute type, and determining second to-be-selected configuration information corresponding to a maximum unit condition probability value in each attribute type;

specifically, if the running state of the target service is calculated to be the smooth state according to the unit service information, the unit condition probability value corresponding to each performance attribute in the target service can be determined, the unit condition probability values corresponding to each performance attribute in each attribute type are compared, the performance attribute corresponding to the maximum unit condition probability value in each attribute type is determined as the second configuration information to be selected, and for the calculation manner of the smooth state and the generation manner of the second configuration information to be selected, reference may be made to the description of step S602 to step S609 in the embodiment corresponding to fig. 6, which is not described herein again. Taking a game-play type hand game as an example, at the time interval between game play and game play of a user, because the terminal device can collect game data of the user in real time, an AI chip in the device can acquire the game data in the previous game play of the user and perform a stuck calculation on the data in the previous game play, and can determine the running state of the game play, if the running state is a smooth state, the probability value (unit condition probability value) of each performance setting can be recalculated based on the data of the game play, and based on the probability value, the performance setting corresponding to the maximum probability value in each attribute setting type is determined as the setting to be selected of the next game play.

Step S808, if the performance priority of the second to-be-selected configuration information is greater than or equal to the performance priority of the performance attribute configuration information, acquiring a target performance index parameter corresponding to the terminal device and a standard performance index parameter for the target service; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the terminal device is located;

step S809, if the target performance parameter is less than or equal to the standard performance index parameter, determining the second to-be-selected configuration information as recommended configuration information of the target service, otherwise determining the performance attribute configuration information as recommended configuration information of the target service;

step S810, if the performance priority of the second candidate configuration information is less than or equal to the performance priority of the performance attribute configuration information, determining the second candidate configuration information as the recommended configuration information of the target service;

the implementation manners of the steps S808 to S810 may refer to the descriptions of the steps S704 to S706 in the embodiment corresponding to fig. 7, and are not described herein again. It should be noted that the implementation process of steps S808 to S810 is performed on the AI chip of the device based on a certain unit service information, and the implementation process of steps S704 to S706 is performed offline on the spark of the server based on a large number of previous service performance parameters.

Step S811 of displaying the recommended configuration information on a screen, and performing attribute setting on the at least one performance attribute based on a first confirmation response and the recommended configuration information when the first confirmation response for the recommended configuration information is detected.

The specific implementation manner of step S811 may refer to the description of step S409 in the embodiment corresponding to fig. 4.

Referring to fig. 9, fig. 9 is a schematic diagram of a framework of a service data processing method according to an embodiment of the present invention. As shown in fig. 9, taking a hand trip as an example, the frame may include: real-time computing game settings and mobile phone resources 91, mobile phone game client 92, and offline computing game initialization settings 93;

the real-time game setting and mobile phone resource 91 may include a mobile phone AI chip 911, where the mobile phone AI chip 911 may calculate the available resource of the mobile phone in real time within the interval time when the user plays the game (for example, the interval time between two games), and calculate the conditional probability value corresponding to each performance attribute in the game in real time by using the bayesian theorem, and the specific calculation manner may refer to step S804 to step S810 in the embodiment corresponding to fig. 8, which is not described herein again. The mobile game client 92 may include a data acquisition module 921 and an optimization policy module 922, where the data acquisition module 921 is mainly responsible for acquiring and reporting data such as user game client data, mobile performance index data, and user network data (such as image quality, high frame rate mode, high definition display, frame rate, CPU, memory, and temperature); the optimization policy module 922 is mainly responsible for setting an optimization policy according to the content of a request policy (performance attribute configuration information or recommendation configuration information) of a server or a mobile phone AI chip and according to a game real-time running condition, and a specific optimization process may refer to the embodiment corresponding to fig. 3, which is not described again. The offline calculation game initialization setting 93 may include a data storage 931, a data query 932, a Spark 933, and a client background 934, where the data storage 931 is mainly responsible for cleaning (i.e., removing useless data) and storing data reported by the data acquisition module 921, the data query 932 is used to query data stored in the data acquisition module 921, so as to obtain the target performance data set, and the Spark 933 may be used to perform big data processing on the queried target performance data set, i.e., calculate a conditional probability value corresponding to each performance attribute in the game in real time by using bayesian theorem, so as to implement the game initialization setting. It should be noted that the real-time computer game setting and the mobile phone resource 91 and the mobile phone game client 92 are completed on the terminal device, and the offline computer game initialization setting 93 is completed on the server.

Referring to fig. 10, fig. 10 is a schematic structural diagram of a service data processing apparatus according to an embodiment of the present invention. As shown in fig. 10, the service data processing apparatus 1 may be applied to the server 100 in the corresponding embodiment of fig. 1, and the service data processing apparatus 1 may include a data set obtaining module 11, a configuration information generating module 12, and a configuration information sending module 13;

the data set acquisition module 11 is configured to acquire a target user state sent by a terminal device, and acquire a target performance data set for a target service based on the target user state;

a configuration information generating module 12, configured to determine, according to the target performance data set, a target condition probability value corresponding to at least one performance attribute in the target service, and generate performance attribute configuration information for the terminal device according to the target condition probability value;

a configuration information sending module 13, configured to send the performance attribute configuration information to the terminal device, so that the terminal device performs initialization setting on the at least one performance attribute in the target service based on the performance attribute configuration information.

For specific functional implementation manners of the data set obtaining module 11, the configuration information generating module 12, and the configuration information sending module 13, reference may be made to steps S202 to S204 in the embodiment corresponding to fig. 2, which is not described herein again.

As shown in fig. 10, the data set acquiring module 11 may include: a first acquisition unit 111, a second acquisition unit 112;

a first obtaining unit 111, configured to determine, if the target user state is a cold start state, service performance parameters of all users associated with the target service in a first time range as a target performance data set;

a second obtaining unit 112, configured to determine, if the target user state is a hot start state, a service performance parameter of a target user corresponding to the terminal device in a second time range as a target performance data set.

The specific functional implementation manner of the first obtaining unit 111 may refer to step S601 in the embodiment corresponding to fig. 6, and the specific functional implementation manner of the second obtaining unit 112 may refer to step S701 in the embodiment corresponding to fig. 7, which is not described herein again. Wherein, when the first acquiring unit 111 is executing the corresponding operation, the second acquiring unit 112 suspends executing the operation; when the second acquisition unit 112 is performing the corresponding operation, the first acquisition unit suspends the execution of the operation. The first obtaining unit 111 and the second obtaining unit 112 may be combined into the same obtaining unit.

As shown in fig. 10, the configuration information generating module 12 may include: a first probability determination unit 121, a first conditional probability determination unit 122, a generation unit 123, a second probability determination unit 124, a second conditional probability determination unit 125, a first comparison unit 126, a second comparison unit 127, and a third comparison unit 128;

a first probability determining unit 121, configured to determine, according to the target performance data set, a first probability value corresponding to each of the multiple models; the first probability value is a probability value that the running state of the target service is a smooth state in one machine type;

a first conditional probability determining unit 122, configured to determine, based on the first probability value, target conditional probability values respectively corresponding to the at least one performance attribute in each of at least one attribute type;

a generating unit 123, configured to generate performance attribute configuration information of the terminal device according to the performance attribute with the maximum target condition probability value in each attribute type;

a second probability determining unit 124, configured to determine a second probability value corresponding to the terminal device according to the target performance data set; the second probability value is a probability value that the running state based on the target service in the terminal equipment is a smooth state;

a second conditional probability determining unit 125, configured to determine, based on the second probability value, target conditional probability values respectively corresponding to the at least one performance attribute in each of the at least one attribute type, and determine first candidate configuration information corresponding to a maximum target conditional probability value in each attribute type;

a first comparing unit 126, configured to obtain default configuration information of the terminal device, and if the performance priority of the first to-be-selected configuration information is greater than the performance priority of the default configuration information, obtain a target performance index parameter corresponding to the terminal device and a standard performance index parameter for the target service; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the terminal device is located;

a second comparing unit 127, configured to determine the first to-be-selected configuration information as the performance attribute configuration information of the terminal device if the target performance parameter is less than or equal to the standard performance index parameter, and otherwise determine the default configuration information as the performance attribute configuration information of the terminal device;

a third comparing unit 128, configured to determine the first to-be-selected configuration information as the performance attribute configuration information of the terminal device, if the performance priority of the first to-be-selected configuration information is less than or equal to the performance priority of the default configuration information.

The specific functional implementation manners of the first probability determining unit 121, the first conditional probability determining unit 122, and the generating unit 123 may refer to step S602 to step S609 in the embodiment corresponding to fig. 6, and the specific functional implementation manners of the second probability determining unit 124, the second conditional probability determining unit 125, the first comparing unit 126, the second comparing unit 127, and the third comparing unit 128 may refer to step S702 to step S706 in the embodiment corresponding to fig. 7, which is not described herein again. Wherein, when the first probability determination unit 121, the first conditional probability determination unit 122, the generation unit 123 are performing the respective operations, the second probability determination unit 124, the second conditional probability determination unit 125, the first comparison unit 126, the second comparison unit 127, the third comparison unit 128 are suspending performing the operations; when the second probability determining unit 124, the second conditional probability determining unit 125, the first comparing unit 126, the second comparing unit 127, and the third comparing unit 128 are performing the respective operations, the first probability determining unit 121, the first conditional probability determining unit 122, and the generating unit 123 each suspend performing the operations.

As shown in fig. 10, the first probability determination unit 121 may include: a first acquisition subunit 1211, a dividing subunit 1212, a weight determining subunit 1213, a marker generating subunit 1214, a probability generating subunit 1215;

a first obtaining subunit 1211, configured to obtain, from the target performance data set, a frame rate set corresponding to each type; the frame rate set comprises a plurality of frame rate subsets, and the plurality of frame rate subsets are determined by a plurality of unit service information associated with the target service;

a dividing subunit 1212, configured to divide each frame rate subset in the frame rate sets to obtain a plurality of frame rate groups corresponding to each frame rate subset respectively;

a weight determining subunit 1213, configured to generate frame rate averages corresponding to the frame rate subsets, and determine, based on the frame rate groups and the frame rate averages, average weights and variance weights corresponding to the frame rate subsets;

a mark generating subunit 1214, configured to generate a katon mark corresponding to each frame rate subset according to the average weight and the variance weight;

a probability generating subunit 1215, configured to generate a first probability value corresponding to each model according to the morton label.

For specific functional implementation manners of the first obtaining subunit 1211, the dividing subunit 1212, the weight determining subunit 1213, the mark generating subunit 1214 and the probability generating subunit 1215, reference may be made to steps S602 to S606 in the embodiment corresponding to fig. 6, which is not described herein again.

As shown in fig. 10, the first conditional probability determining unit 122 may include: a second acquisition subunit 1221, a conditional probability generation subunit 1222;

a second obtaining subunit 1221, configured to determine, according to the target performance data set, attribute probability parameters corresponding to the at least one performance attribute respectively, and determine a conditional attribute probability parameter that an attribute operation state corresponding to each performance attribute is a smooth state; the attribute running state corresponding to one performance attribute is the running state of the target service when the performance attribute is set;

a conditional probability generating subunit 1222, configured to determine, according to the first probability value, the attribute probability parameter, and the conditional attribute probability parameter, a target conditional probability corresponding to the at least one performance attribute in each of the at least one attribute type respectively.

The specific functional implementation manners of the second obtaining subunit 1221 and the conditional probability generating subunit 1222 may refer to steps S607 to S608 in the embodiment corresponding to fig. 6, which are not described herein again.

Referring to fig. 11, fig. 11 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention. As shown in fig. 11, the service data processing apparatus 2 may correspond to the terminal device 200 in the embodiment corresponding to fig. 1, and the service data processing apparatus 2 may include: a user state sending module 21 and a performance attribute setting module 22;

a user state sending module 21, configured to send, by a terminal device, a target user state to a server, so that the server obtains a target performance data set for a target service based on the target user state, and generates performance attribute configuration information for the terminal device according to the target performance data set; the performance attribute configuration information is determined by a target condition probability value corresponding to at least one performance attribute in the target service respectively;

a performance attribute setting module 22, configured to receive the performance attribute configuration information by the terminal device, and perform initialization setting on the at least one performance attribute in the target service based on the performance configuration information.

For specific functional implementation manners of the user status sending module 21 and the performance attribute setting module 22, reference may be made to step S201 and step S205 in the embodiment corresponding to fig. 2, which is not described herein again.

As shown in fig. 11, the service data processing apparatus 2 may further include: a service information acquisition module 23, a first state determination module 24, a second state determination module 25, and a display module 26;

a service information obtaining module 23, configured to obtain, by the terminal device, multiple pieces of unit service information associated with the target service, and determine, based on each piece of unit service information, an operating state of the target service;

a first state determining module 24, configured to, if the running state of the target service is a stuck state, obtain an available device resource of the terminal device and a service demand resource corresponding to the target service, and determine, based on the performance attribute configuration information, the available device resource and the service demand resource, recommended configuration information of the target service;

a second state determining module 25, configured to generate recommended configuration information of the target service according to the information of each unit service if the running state of the target service is a smooth state;

a display module 26, configured to display the recommended configuration information on a screen, and perform attribute setting on the at least one performance attribute based on a first confirmation response and the recommended configuration information when the first confirmation response for the recommended configuration information is detected.

For specific functional implementation manners of the service information obtaining module 23, the first state determining module 24, the second state determining module 25, and the display module 26, reference may be made to steps S406 to S409 in the embodiment corresponding to fig. 4, which is not described herein again.

As shown in fig. 11, the first state determination module 24 may include: a first resource comparing unit 241, a second resource comparing unit 242;

a first resource comparing unit 241, configured to, if the available device resource is greater than the service demand resource, invoke the available device resource for the target service, and determine the performance attribute configuration information as recommended configuration information of the target service;

a second resource comparing unit 242, configured to generate recommended configuration information according to the performance attribute configuration if the available device resource is less than or equal to the service requirement resource; the performance priority of the recommended configuration information is smaller than the performance priority of the performance attribute configuration information.

The specific functional implementation manners of the first resource comparing unit 241 and the second resource comparing unit 242 may refer to steps S805 to S806 in the embodiment corresponding to fig. 8, which is not described herein again.

As shown in fig. 11, the second state determination module 25 may include: a second conditional probability determining unit 251, a fourth comparing unit 252, a fifth comparing unit 253, a sixth comparing unit 254;

a second conditional probability determining unit 251, configured to determine, if the operation state of the target service is a smooth state, a unit condition probability value corresponding to each of the at least one performance attribute in each of the at least one attribute type, and determine second candidate configuration information corresponding to a maximum unit condition probability value in each of the at least one attribute type;

a fourth comparing unit 252, configured to obtain a target performance index parameter corresponding to the terminal device and a standard performance index parameter for the target service if the performance priority of the second configuration information to be selected is greater than or equal to the performance priority of the performance attribute configuration information; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the terminal device is located;

a fifth comparing unit 253, configured to determine the second to-be-selected configuration information as recommended configuration information of the target service if the target performance parameter is less than or equal to the standard performance indicator parameter, and otherwise determine the performance attribute configuration information as recommended configuration information of the target service;

a sixth comparing unit 254, configured to determine the second to-be-selected configuration information as the recommended configuration information of the target service if the performance priority of the second to-be-selected configuration information is less than or equal to the performance priority of the performance attribute configuration information.

The specific functional implementation manners of the second conditional probability determining unit 251, the fourth comparing unit 252, the fifth comparing unit 253, and the sixth comparing unit 254 may refer to steps 807 to S810 in the embodiment corresponding to fig. 8, which is not described herein again.

Referring to fig. 12, fig. 12 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention. As shown in fig. 12, the service data processing apparatus 1000 may correspond to the server 100 in the embodiment corresponding to fig. 1, and the service data processing apparatus 1000 may include: the processor 1001, the network interface 1004, and the memory 1005, and the service data processing apparatus 1000 may further include: a user interface 1003, and at least one communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display) and a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a standard wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1004 may be a high-speed RAM memory or a non-volatile memory (e.g., at least one disk memory). The memory 1005 may optionally be at least one memory device located remotely from the processor 1001. As shown in fig. 12, a memory 1005, which is a kind of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a device control application program.

In the service data processing apparatus 1000 shown in fig. 12, the network interface 1004 may provide a network communication function; the user interface 1003 is an interface for providing a user with input; the processor 1001 may be configured to call a device control application stored in the memory 1005, so as to implement the description of the service data processing method in the embodiment corresponding to any one of fig. 2 to fig. 7, which is not described herein again. In addition, the beneficial effects of the same method are not described in detail.

It should be understood that the service data processing apparatus 1000 described in the embodiment of the present invention may perform the description of the service data processing method in the embodiment corresponding to any one of fig. 2 to fig. 7, and may also perform the description of the service data processing apparatus 1 in the embodiment corresponding to fig. 10, which is not described herein again. In addition, the beneficial effects of the same method are not described in detail.

Further, here, it is to be noted that: an embodiment of the present invention further provides a computer storage medium, where the computer storage medium stores the aforementioned computer program executed by the service data processing apparatus 1, and the computer program includes program instructions, and when the processor executes the program instructions, the description of the service data processing method in any one of the embodiments corresponding to fig. 2 to fig. 7 can be executed, so that details are not repeated here. In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in the embodiments of the computer storage medium to which the present invention relates, reference is made to the description of the method embodiments of the present invention.

Referring to fig. 13, fig. 13 is a schematic structural diagram of another service data processing apparatus according to an embodiment of the present invention. As shown in fig. 13, the service data processing apparatus 2000 may correspond to the terminal device 200 in the embodiment corresponding to fig. 1, and the service data processing apparatus 2000 may include: the processor 2001, the network interface 2004 and the memory 2005, the service data processing apparatus 2000 may further include: a user interface 2003, and at least one communication bus 2002. The communication bus 2002 is used to implement connection communication between these components. The user interface 2003 may include a Display (Display) and a Keyboard (Keyboard), and the optional user interface 2003 may further include a standard wired interface and a standard wireless interface. The network interface 2004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 2004 may be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The memory 2005 may optionally also be at least one memory device located remotely from the aforementioned processor 2001. As shown in fig. 13, the memory 2005, which is one type of computer storage medium, may include therein an operating system, a network communication module, a user interface module, and a device control application program.

In the service data processing apparatus 2000 shown in fig. 13, the network interface 2004 may provide a network communication function; and the user interface 2003 is primarily used to provide an interface for user input; the processor 2001 may be configured to invoke the device control application program stored in the memory 1005, so as to implement the description of the service data processing method in the embodiment corresponding to any one of fig. 2 to 5c and fig. 8, which is not described herein again. In addition, the beneficial effects of the same method are not described in detail.

It should be understood that the service data processing apparatus 2000 described in the embodiment of the present invention may perform the description of the service data processing method in the embodiment corresponding to any one of fig. 2 to 5c and fig. 8, and may also perform the description of the service data processing apparatus 2 in the embodiment corresponding to fig. 11, which is not described herein again. In addition, the beneficial effects of the same method are not described in detail.

Further, here, it is to be noted that: an embodiment of the present invention further provides a computer storage medium, where the computer storage medium stores the aforementioned computer program executed by the service data processing apparatus 2, and the computer program includes program instructions, and when the processor executes the program instructions, the description of the service data processing method in any one of the embodiments corresponding to fig. 2 to 5c and fig. 8 can be executed, so that details are not repeated here. In addition, the beneficial effects of the same method are not described in detail. For technical details not disclosed in the embodiments of the computer storage medium to which the present invention relates, reference is made to the description of the method embodiments of the present invention.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.

The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims

1. A method for processing service data is characterized by comprising the following steps:

the client runs the target service and acquires the running state of the target service calculated by the terminal equipment; the operation state is determined by the terminal device based on a plurality of unit service information associated with the target service;

if the running state of the target service is a stuck state, the client acquires available equipment resources obtained by calculation of the terminal equipment and service demand resources corresponding to the target service, and determines recommended configuration information of the target service based on performance attribute configuration information, the available equipment resources and the service demand resources; the performance attribute configuration information is information for performing initialization setting on at least one performance attribute in the target service.

2. The method of claim 1, further comprising:

and the client displays the recommended configuration information, and performs attribute setting on the at least one performance attribute based on the first confirmation response and the recommended configuration information when detecting a first confirmation response aiming at the recommended configuration information.

3. The method of claim 1, further comprising:

and if the running state of the target service is a smooth state, the client acquires the recommended configuration information of the target service generated by the terminal equipment according to the information of each unit service.

4. The method of claim 1, wherein the determining the recommended configuration information of the target service based on the performance attribute configuration information, the available device resources, and the service-demanding resources comprises:

if the available equipment resource is larger than the service demand resource, calling the available equipment resource for the target service, and determining the performance attribute configuration information as the recommended configuration information of the target service;

if the available equipment resource is less than or equal to the service demand resource, generating recommendation configuration information according to the performance attribute configuration; the performance priority of the recommended configuration information is smaller than the performance priority of the performance attribute configuration information.

5. The method according to claim 3, wherein the client acquires recommended configuration information of the target service generated by the terminal device according to the information of each unit service, and comprises:

the client acquires the request strategy content generated by the terminal equipment; the request strategy content comprises the recommendation configuration information;

if the performance priority of second configuration information to be selected is greater than or equal to the performance priority of the performance attribute configuration information, and a target performance parameter corresponding to the terminal device is less than or equal to a standard performance index parameter of the target service, the recommended configuration information is the second configuration information to be selected; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the terminal device is located; the second candidate configuration information is determined by the performance attribute with the maximum unit condition probability value in each attribute type in at least one attribute type in the target service;

if the performance priority of the second candidate configuration information is greater than or equal to the performance priority of the performance attribute configuration information, and the target performance parameter corresponding to the terminal equipment is greater than the standard performance index parameter of the target service, the recommended configuration information is the performance attribute configuration information;

and if the performance priority of the second candidate configuration information is smaller than that of the performance attribute configuration information, the recommended configuration information is the second candidate configuration information.

6. The method of claim 1, further comprising:

the client displays an initial login interface of the target service, and identifies the target user state of the target user according to the input operation acquired by the terminal equipment; the input operation refers to the input operation of the target user aiming at the initial login interface;

acquiring performance attribute configuration information; the performance attribute configuration information is generated by target condition probability values respectively corresponding to at least one performance attribute in the target service, and the target condition probability values are determined based on a target performance data set associated with the target user state;

and performing initialization setting on the at least one performance attribute in the target service based on the performance attribute configuration information.

7. The method of claim 6, wherein the performance attribute configuration information is determined by the performance attribute having the maximum target conditional probability value in each of the at least one attribute type in the target service; the target condition probability value corresponding to at least one performance attribute in each attribute type is determined based on a first probability value corresponding to each type in a plurality of types, the first probability value refers to a probability value that the running state of the target service in one type is a smooth state, and the first probability value is determined according to the target performance data set.

8. A method for processing service data is characterized by comprising the following steps:

the client acquires performance attribute configuration information, and performs initialization setting on at least one performance attribute in a target service based on the performance attribute configuration information;

reporting game data, equipment performance parameters and the performance attribute configuration information in the game process to a server so that the server generates recommended configuration information according to the game data, the equipment performance parameters and the performance attribute configuration information in the target service;

and the client receives the recommended configuration information, and performs attribute setting on the at least one performance attribute based on the first confirmation response and the recommended configuration information when detecting a first confirmation response aiming at the recommended configuration information.

9. The method of claim 8,

if the server determines that the running state of the target service is a stuck state based on the game data, the recommended configuration information is determined based on the performance attribute configuration information, available equipment resources and service demand resources; the business need resources are determined based on device performance parameters and the game data.

10. The method of claim 8,

if the server determines that the running state of the target service is a smooth state based on the game data, the recommended configuration information is determined in second candidate configuration information and the performance attribute configuration information; the second candidate configuration information is determined by the performance attribute with the maximum unit condition probability value in each attribute type in at least one attribute type in the target service;

if the performance priority of second candidate configuration information is greater than or equal to the performance priority of the performance attribute configuration information, and the equipment performance parameter is less than or equal to the standard performance index parameter of the target service, the recommended configuration information is the second candidate configuration information; the standard performance index parameter is the maximum performance index parameter in the performance index parameters of a plurality of devices in the area where the client is located;

if the performance priority of the second candidate configuration information is greater than or equal to the performance priority of the performance attribute configuration information, and the equipment performance parameter is greater than the standard performance index parameter of the target service, the recommended configuration information is the performance attribute configuration information;

11. A method for processing service data is characterized by comprising the following steps:

the client reports game data, equipment performance parameters and network data in the game process to the server;

the server adds game data, device performance parameters and network data to a target performance data set according to the terminal device sending the target user state; the target performance data set is used for determining a target condition probability value corresponding to at least one performance attribute in a target service, the target condition probability value corresponding to at least one performance attribute in the target service is used for generating performance attribute configuration information for the terminal equipment sending the target user state, and the performance attribute configuration information is used for indicating the terminal equipment sending the target user state to carry out initialization setting on the at least one performance attribute in the target service.

12. A method for processing service data is characterized by comprising the following steps:

collecting game data of unit business of a target user in a target business, and storing the game data into a game database;

when the unit business is finished, acquiring the game data from the game database, acquiring equipment performance parameters from an equipment hardware database, and performing card-pause calculation on the unit business according to the game data to obtain the running state of the unit business;

if the running state of the unit business is a stuck state, calculating resources required by the game according to the game data and the equipment performance parameters, and determining the recommended configuration information of the target business based on the performance attribute configuration information, the available equipment resources and the resources required by the game; the recommended configuration information is used for resetting the at least one performance attribute.

13. The method of claim 12, further comprising:

if the running state of the unit service is a smooth state, determining a unit condition probability value corresponding to the at least one performance attribute in each attribute type according to the game data and the equipment performance parameters, determining second candidate configuration information corresponding to a maximum unit condition probability value in each attribute type, and determining the recommended configuration information in the second candidate configuration information and the performance attribute configuration information.

14. A method for processing service data is characterized by comprising the following steps:

acquiring game data, equipment performance parameters and performance attribute configuration information acquired by terminal equipment in a game process; the performance attribute configuration information refers to information that the terminal device depends on when initializing at least one performance attribute in a target service;

generating recommendation configuration information according to the game data, the equipment performance parameters and the performance attribute configuration information;

and sending the recommended configuration information to the terminal equipment.

15. The method of claim 14, wherein the method is performed by a game client and a server corresponding to the game client; the method further comprises the following steps:

the server acquires the performance attribute option setting in the target service; the performance attribute option setting includes an option of at least one performance attribute;

the server generates the performance attribute configuration information for the at least one performance attribute and sends the performance attribute configuration information to the game client;

and the game client triggers the terminal equipment to carry out initialization setting on at least one performance attribute in the target service based on the performance attribute configuration information.

16. The method of claim 15, further comprising:

the game client regularly triggers a performance attribute option setting optimization request, and requests a game client interface to adjust the performance attribute option setting based on the performance attribute option setting optimization request;

the game client interface checks the performance attribute configuration information, and if the performance attribute configuration information passes the check, the game client interface sends the performance attribute configuration information to the server;

after the server detects that the target service carries out initialization setting on the at least one performance attribute according to the performance attribute configuration information, the matching degree of the initialization setting and the terminal equipment is detected;

if the matching degree is greater than a first matching degree threshold value, returning a confirmation result to the game client through the game client interface, and informing the terminal device that the performance attribute configuration information is not adjusted by the game client based on the confirmation result;

and if the matching degree is smaller than a second matching degree threshold value, adjusting the performance attribute configuration information, returning the adjusted performance attribute configuration information to the game client through the game client interface, and triggering the terminal equipment to perform optimized setting on at least one performance attribute based on the adjusted performance attribute configuration information by the game client.

17. A service data processing apparatus, comprising: a processor and a memory;

the processor is coupled to a memory, wherein the memory is configured to store program code and the processor is configured to invoke the program code to perform the method of any of claims 1-16.

18. A computer storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions which, when executed by a processor, perform the method according to any one of claims 1-16.