Log Generation Method and Device

Abstract

The present application provides a log generation method and apparatus. The log generation method includes: receiving initial log information; parsing the initial log information to obtain log content information, a module identifier, and a classification identifier associated with the log content information; determining an initial log sequence according to the module identifier, and writing the log content information divided according to the classification identifier into the initial log sequence; and when the initial log sequence meets a preset log conversion condition, generating target log information corresponding to the initial log sequence through a log processing model. By this method, automatic generation and typesetting of updated logs can be achieved, communication is enhanced, workload is saved, and the efficiency of log generation is improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a log generation method. This application also relates to a log generation device, a computing device, and a computer-readable storage medium. Background Art

[0002] With the development of Internet technology, various application programs are being used more and more widely, and the speed of update and iteration is also getting faster and faster. Technical personnel achieve the technological progress and functional improvement of application programs through successive generations of updated versions. In this context, update logs for introducing the updated content of application programs are being used more and more frequently. When creating an update log, in the prior art, it is necessary for the log writer to communicate with the technical personnel who updated the application program. Only after fully understanding the updated content of the application program can it be ensured that the written update log can be presented to the users of the application program, so that users can understand the updated content of the application program through the update log. However, the process of creating an update log in this way has relatively high quality requirements for the log writer. The writer not only needs to have a relatively comprehensive understanding of the product culture but also needs to have a rich accumulation of professional knowledge at the relevant technical level to ensure that the written update log can meet the conversion of update information from technical personnel to users. Moreover, the time cost consumed in this process of creating an update log cannot meet the increasingly frequent update environment of application programs. Therefore, there is an urgent need for a method to solve the above problems. Summary of the Invention

[0003] In view of this, embodiments of this application provide a log generation method to solve the technical defects existing in the prior art. Embodiments of this application also provide a log generation device, a computing device, and a computer-readable storage medium.

[0004] According to the first aspect of the embodiments of this application, a log generation method is provided, including:

[0005] Receiving initial log information;

[0006] Parsing the initial log information to obtain log content information, and a module identifier and a classification identifier associated with the log content information;

[0007] Determining an initial log sequence according to the module identifier, and writing the log content information divided according to the classification identifier into the initial log sequence;

[0008] When the initial log sequence meets the preset log conversion condition, generating target log information corresponding to the initial log sequence through a log processing model.

[0009] Optionally, the receiving of the initial log information includes:

[0010] Receiving a log update request;

[0011] In response to the log update request, scanning the log submission record to obtain log time information;

[0012] Reading the initial log information based on the log submission record and the log time information.

[0013] Optionally, the determining of the initial log sequence according to the module identifier includes:

[0014] Traversing the log sequence library to determine the log sequence identifiers of each log sequence in the log sequence library;

[0015] Comparing the log sequence identifiers of each log sequence with the module identifier;

[0016] Selecting the log sequence with the same identifier as the initial log sequence according to the comparison result.

[0017] Optionally, the writing of the log content information divided according to the classification identifier into the initial log sequence includes:

[0018] Dividing the log content information based on the classification identifier to obtain at least one sub-log content information;

[0019] Determining the writing positions corresponding to each sub-log content information in the initial log sequence based on the classification identifier;

[0020] Writing each sub-log content information into the initial log sequence according to the writing position.

[0021] Optionally, the generating of the target log information corresponding to the initial log sequence by the log processing model includes:

[0022] Reading the log content information to be processed and the corresponding classification identifier to be processed in the initial log sequence;

[0023] Constructing an information vector corresponding to the log content information to be processed and an identifier vector corresponding to the classification identifier to be processed;

[0024] Fusing the information vector and the identifier vector, and inputting the fused log vector to be processed into the log processing model for processing to obtain the target log information.

[0025] Optionally, the reading of the log content information to be processed and the corresponding classification identifier to be processed in the initial log sequence includes:

[0026] Select all the log content information in the initial log sequence as the log content information to be processed; and select all the classification identifiers in the initial log sequence as the classification identifiers to be processed.

[0027] Or,

[0028] Determine the log content information in the initial log sequence that does not contain the selection identifier as the log content information to be processed; select the classification identifier corresponding to the log content information that does not contain the selection identifier as the classification identifier to be processed.

[0029] Optionally, the initial log information is input and generated by a business operator through a log collection interface in a client and uploaded by the client; wherein, the log collection interface includes a module identifier selection sub-interface and a classification identifier selection sub-interface; the initial log information input by the business operator is collected through the module identifier selection sub-interface and the classification identifier selection sub-interface.

[0030] Optionally, the training of the log processing model includes:

[0031] Obtain initial sample log information, as well as the sample classification identifier and target sample log information corresponding to the initial sample log information;

[0032] Input the initial sample log information and the sample classification identifier into an initial log processing model for processing to obtain the predicted log information corresponding to the initial sample log information;

[0033] Adjust the parameters of the initial log processing model according to the target sample log information and the predicted log information until a log processing model that meets the training stop condition is obtained.

[0034] Optionally, after the step of generating the target log information corresponding to the initial log sequence by the log processing model, the following steps are further included:

[0035] Send the target log information to an audit node and receive an update request feedback by the audit node for the target log information;

[0036] Update the target log information according to the update request to obtain the log information to be published;

[0037] Perform a publishing process on the log information to be published according to a preset publishing policy.

[0038] Optionally, after obtaining the log information to be published, the following steps are further included:

[0039] Adjust the parameters of the log processing model according to the log information to be published and the target log information to update the log processing model.

[0040] According to a second aspect of the embodiments of the present application, a log generation device is provided, including:

[0041] A receiving module, configured to receive initial log information;

[0042] An analysis module, configured to analyze the initial log information to obtain log content information, as well as a module identifier and a classification identifier associated with the log content information;

[0043] A writing module, configured to determine an initial log sequence according to the module identifier, and write the log content information divided according to the classification identifier into the initial log sequence;

[0044] A generation module, configured to generate target log information corresponding to the initial log sequence through a log processing model when the initial log sequence meets a preset log conversion condition.

[0045] According to a third aspect of the embodiments of the present application, a computing device is provided, including:

[0046] A memory and a processor;

[0047] The memory is used to store computer-executable instructions, and when the processor executes the computer-executable instructions, the steps of the log generation method are implemented.

[0048] According to a fourth aspect of the embodiments of the present application, a computer-readable storage medium is provided, which stores computer-executable instructions, and when the instructions are executed by a processor, the steps of the log generation method are implemented.

[0049] According to a fifth aspect of the embodiments of the present application, a chip is provided, which stores a computer program, and when the computer program is executed by the chip, the steps of the log generation method are implemented.

[0050] The log generation method provided by the present application receives initial log information, then obtains log content information, a module identifier, and a classification identifier related to the initial log information, determines an initial log sequence related to the log content information according to the module identifier, divides the log content information according to the classification identifier and writes it into the relevant position of the initial log sequence, and finally, when the initial log sequence meets a preset log conversion condition, generates target log information corresponding to the initial log sequence through a log processing model, realizing the automated generation and typesetting of updated logs, enhancing communication, saving workload, and improving the efficiency of log generation. Description of the Drawings

[0051] Figure 1 is a flowchart of a log generation method provided by an embodiment of the present application;

[0052] Figure 2 It is a schematic diagram of an operation interface of a log generation method provided by an embodiment of the present application;

[0053] Figure 3 It is a processing flow chart of a log generation method applied to a navigation software provided by an embodiment of the present application;

[0054] Figure 4 It is a schematic structural diagram of a log generation device provided by an embodiment of the present application;

[0055] Figure 5 It is a structural block diagram of a computing device provided by an embodiment of the present application. Detailed implementation manners

[0056] Many specific details are set forth in the following description in order to provide a thorough understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the connotation of the present application. Therefore, the present application is not limited by the specific implementations disclosed below.

[0057] The terms used in one or more embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of the present application. The singular forms "a", "the" and "said" used in one or more embodiments of the present application and the appended claims are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of the present application refers to and includes any or all possible combinations of one or more of the associated listed items.

[0058] It should be understood that although the terms first, second, etc. may be used in one or more embodiments of the present application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of one or more embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first.

[0059] First, the noun terms related to one or more embodiments of the present invention are explained.

[0060] SVN: It is an open-source version control system. Through the efficient management of the branch management system, in short, it is used for multiple people to jointly develop the same project, realize resource sharing, and achieve centralized management finally.

[0061] In this application, a log generation method is provided. This application also relates to a log generation device, a computing device, and a computer-readable storage medium, which will be described in detail one by one in the following embodiments.

[0062] In practical applications, due to the accelerating speed of application program version updates, the editing work of the update log after each version update has become increasingly common. However, since the audience for the update log is users, to enable users to understand the content of the application program version update and let them know the specific update content of the application program version update, the language used in the update log should be based on the cognitive level of users. Additionally, due to some special application scenarios in the application program, such as game programs, etc., when writing the update log, it should be more closely related to the game content to explain the update, which can facilitate user understanding and this method can also better arouse the emotions of users.

[0063] However, for the update log required above, its writers must have a complete understanding of the content of the application program and have a deep understanding of the technologies used in the application program update. Only in this way can they associate from a technical perspective to the user perspective and achieve the writing of an update log that meets the requirements. But this will undoubtedly increase the quality requirements for practitioners, and this completely manual method cannot guarantee efficiency during the writing process of the update log.

[0064] Therefore, in this application, a log generation method is proposed. Through automated log generation, it solves the requirements for the quality of practitioners and realizes the establishment efficiency of the update log establishment process, saving labor costs.

[0065] Figure 1 The flowchart of a log generation method provided according to an embodiment of the present application is shown, which specifically includes the following steps:

[0066] Step S102: Receive initial log information.

[0067] Among them, the initial log information can be understood as the update log uploaded by the technical personnel who updated the application program after the application program update is completed. The initial log information contains the module to which the update content belongs, such as different modules like characters, equipment, pets, etc. updated in a game program, the update type of the update content, such as different types like art, program, planning, etc. updated in the application program, and the description of the technical personnel regarding aspects such as the update content and update effect.

[0068] Based on this, the server-side receives the initial log information uploaded by the technical personnel, which contains information such as the module, type, content, and effect of the update content.

[0069] Further, in order to ensure that the initial log information received by the server contains the required specific content, it is necessary to ensure that the initial log content uploaded by the technical staff has a certain format limitation. In this embodiment, the specific implementation method is as follows:

[0070] The initial log information is generated by the business operator through the log collection interface in the client and uploaded by the client; among them, the log collection interface includes a module identifier selection sub-interface and a classification identifier selection sub-interface; the initial log information input by the business operator is collected through the module identifier selection sub-interface and the classification identifier selection sub-interface.

[0071] Among them, the business operator can be understood as the specific relevant technical staff who updates the application program and is responsible for the specific implementation process of the design and production of the program, screen, sound, etc. of the application program. The log collection interface can be understood as the interface for the business operator to upload the initial log information. It should be noted that the log collection interface can be a separately created input interface or an input interface attached to other mature platforms. The specific selection situation is determined by the actual application scenario and is not limited in this embodiment. The module identifier selection sub-interface can be understood as being used for the business operator to select the module to which the updated content of the application program belongs. Among them, preset module labels can be selected, and the business operator can also create custom module labels. The classification identifier selection sub-interface is similar to the module identifier selection sub-interface and is used for the business operator to select the type to which the updated content of the application program belongs. There are also two forms: preset and custom. It should be noted that the module identifier selection sub-interface and the classification identifier selection sub-interface can be established separately or combined together. The specific implementation form is determined by the actual usage scenario and is not limited in this embodiment. In addition, after the module identifier and the classification identifier are respectively selected through the module identifier selection sub-interface and the classification identifier selection sub-interface, an input template can be created based on the selected module identifier and classification identifier. The business operator can input the updated content and update effect of the application program based on this template. The implementation of the automatic generation of this template is determined by the actual usage scenario and is not limited in this embodiment.

[0072] For example, in the case of game updates, game developers' log upload for the updated content is authorized and executed based on the Ones task platform. A new task on the task platform needs to be created before it can be submitted to SVN. When there is an update to the SVN data, developers fill in the changed data during the update. When developers input in the log collection interface on the Ones task platform, they first select the sub-interface based on the module identifier and select the module identifier of the game update content as [a certain equipment]. Then, in the classification identifier selection sub-interface, they select the classification identifier of the game content update as "program logic". Then, based on the selected module identifier and "program logic", an update content input template "XX function is added, and XX is achieved." is generated. Developers input into the template and get "A equipment function is added, and the use of A equipment in the mecha combat mode is achieved." Finally, the above update content is uploaded as the initial log information G through the client.

[0073] In summary, through the above method, during the update process of the application program, the standardization of the initial log information upload by business operators is achieved, and the difficulty of generating the target log is simplified. It should be noted that in addition to this log collection interface, a defect correction interface can also be set up to distinguish between version updates and bug fixes of the application program. The specific page settings are determined by the actual usage situation and are not limited in this embodiment.

[0074] Furthermore, for the collection of the initial log information by the server, real-time collection of the initial log information is required after the log generation method starts to execute, which will cause waste of resources of the computing device. In this embodiment, the specific implementation method is as follows:

[0075] Receive a log update request; in response to the log update request, scan the log submission record to obtain the log time information; read the initial log information based on the log submission record and the log time information.

[0076] Among them, the log update request can be understood as an instruction to indicate the collection of the initial log information in the case where log generation is required; the log submission record can be understood as a record of all uploaded initial log information and their related information. It should be noted that these related information includes the upload time of the initial log information, the file size of the upload, etc. The specific content included is determined according to the actual scenario and is not limited in this embodiment. The log time information can be understood as information containing the upload time of the initial log information.

[0077] Based on this, receive the log update request, scan the log submission record according to the log update request to obtain the upload time of each initial log information contained in the log submission record, that is, the log time information. Then, according to the requirements, determine the initial log information that needs to be read based on the upload time of each initial log information and read it.

[0078] Continuing with the above example, after receiving the initial update request, scan the log submission records to determine the upload time of each initial log message. Based on this upload time, it is determined that the initial log message uploaded after the last game update is the initial log message G. Then, read the initial log message G in the log submission records.

[0079] In summary, through the above method, it is possible to read the initial log messages in the case of a log generation requirement, reducing the waste of computing resources in the real-time collection process.

[0080] Step S104: Parse the initial log message to obtain the log content information, as well as the module identifier and classification identifier associated with the log content information.

[0081] Specifically, after obtaining the initial log message, it is necessary to parse the initial log message to determine the module, classification, and specific update content for which the initial log message updates the application, so as to classify and process the initial log message and simplify the processing difficulty.

[0082] Among them, the log content information can be understood as including the specific content of the application update and the effects generated after the update; the module identifier can be understood as including the information of the specific module that has updated the application. For example, in a game program, updates to different modules such as characters, equipment, and pets, the information of these modules; the classification identifier can be understood as including the information of the specific update type for updating the application. For example, the application update types are different types such as art, program, and planning, the information of these types.

[0083] Based on this, after receiving the initial log message, parse the initial log message to determine the module identifier indicating the specific update of the application corresponding to the initial log message, and the classification identifier indicating the specific update type of the application corresponding to the initial log message.

[0084] Step S106: Determine the initial log sequence according to the module identifier, and write the log content information divided according to the classification identifier into the initial log sequence.

[0085] Specifically, after determining the module and update type for which the application is updated according to the initial log message, it is necessary to classify and process the log content information in the initial log message to reduce the processing complexity.

[0086] Among them, the initial log sequence can be understood as a sequence for storing the log content information in the initial log information for updating the same module. It should be noted that each element in the initial log sequence is log content information, and the order of its elements is clear, which can correspond to different application program update types. Its specific arrangement order is determined by the actual usage scenario and is not limited in this embodiment.

[0087] Based on this, for the module of the application program updated according to the initial log content indicated by the module identifier, the corresponding initial log sequence is selected, and according to the indication of the classification identifier, the log content information is written into the corresponding position in the initial log sequence. It should be noted that the number of module identifiers and classification identifiers included in an initial log information is not fixed. For example, there are two module identifiers A1 and A2 and three classification identifiers b1, b2 in a certain initial log information. Assuming its display form is A1{b1: 111; b2: 222}, A2{b2: 333}, where, in this case, it can be divided into three parts "b1: 111", "b2: 222", "b2: 333" according to the classification identifier, and then according to the indication of the module identifier, "b1: 111" and "b2: 222" are stored in the initial log sequence corresponding to A1, and "b2: 333" is stored in the initial log sequence corresponding to A2. Among them, there are cases where there are the same module identifier but different classification identifiers, such as "b1: 111" and "b2: 222", and there are also cases where there are the same classification identifier but different module identifiers, such as "b2: 222" and "b2: 333". The above forms do not affect the specific division and allocation writing.

[0088] Furthermore, in most cases, the application program contains multiple modules, that is to say, there are multiple corresponding initial log sequences. It is necessary to determine which specific initial log sequence the initial log information corresponds to according to the module identifier. In this embodiment, the specific implementation method is as follows:

[0089] Traverse the log sequence library to determine the log sequence identifiers of each log sequence in the log sequence library; compare the log sequence identifiers of each log sequence with the module identifier; select the log sequence with the same identifier as the initial log sequence according to the comparison result.

[0090] Among them, the log sequence can be understood as a preset sequence that corresponds one-to-one with all module identifiers; the log sequence library can be understood as a database storing all log sequences; the log sequence identifier can be understood as the "identity information" of the log sequence, used to distinguish each log sequence and corresponding one-to-one with each module identifier.

[0091] Based on this, all log sequences in the log sequence library are queried to determine the log sequence identifier corresponding to each log sequence. The log sequence identifier is compared with the module identifier of the initial log information to determine the log sequence corresponding to the initial log information, and this log sequence is determined as the initial log sequence.

[0092] For example, traverse the log sequence library to determine the log sequence identifiers of all log sequences in the log sequence library. Compare the obtained log sequence identifiers with the module identifier [a certain equipment] of the initial log information G to determine that the log sequence X is the initial log sequence, denoted as the initial log sequence X.

[0093] In summary, the above method realizes the determination of the corresponding initial log sequence through the module identifier and the log sequence identifier, making the determination process of the initial log sequence accurate.

[0094] Furthermore, since the position of each element in the initial log sequence corresponds to different meanings and the positions between different elements cannot be randomly interchanged, during the process of writing the log content information of the initial log information into the initial log sequence, it cannot be written randomly and needs to be written in a targeted manner. In this embodiment, the specific implementation method is as follows:

[0095] Divide the log content information based on the classification identifier to obtain at least one sub-log content information; determine the writing positions corresponding to each sub-log content information in the initial log sequence based on the classification identifier; write each sub-log content information into the initial log sequence according to the writing positions.

[0096] Among them, the sub-log content information can be understood as the information obtained by combining the log content information with the classification identifier, which contains the specific content of the application update and the relevant information of the specific update type; the writing position can be understood as the position limit for writing the sub-log content information into the initial log sequence. For example, in the initial log sequence, it is stipulated that the writing position of the sub-log content information with the update type of "program logic" is before the sub-log content information of "art resources". It should be noted that the writing position can include determining the specific writing bytes, or different definition methods such as the writing order. Its specific implementation method is determined by the actual usage scenario and is not limited in this embodiment. In addition, the determination process of the writing position of the sub-log content information can be determined based on the storage time of the sub-log content information. For example, for two initial log information x1 and x2, if x1 is received before x2, the sub-log content information divided from x1 can be preferentially written, and the writing position is before the sub-log content information divided from x2; or the writing position can be determined according to the byte length of the sub-log content information. Still for two initial log information x1 and x2, among the sub-log content information divided from x1 and x2, they are written in descending order according to the byte length; or the writing position can be determined by the priority corresponding to different classification identifiers preset. For example, among the sub-log content information divided from two initial log information x1 and x2, the writing order of these sub-log content information is determined according to the corresponding classification identifier. It can be seen that there can be more than one definition method for the writing order of the writing position, and which specific method is adopted is determined by the actual application scenario and is not limited in this embodiment.

[0097] Based on this, the sub-log content information is determined according to the classification identifier and the log content information, and then according to the indication of the classification identifier and the regulations of the initial log sequence, the writing position corresponding to each sub-log content information is determined. According to the obtained writing position, the sub-log content information is written into the corresponding position of the initial log sequence.

[0098] Continuing with the above example, based on the classification identifier "Program Logic" of the initial log information G, the log content information "The function of Equipment A has been newly added, enabling the use of Equipment A in the mecha combat mode." is classified to obtain the sub-log content information "Program Logic: The function of Equipment A has been newly added, enabling the use of Equipment A in the mecha combat mode." Subsequently, based on the classification identifier "Program Logic" and the initial log sequence, it is determined that the write position of the sub-log content information corresponding to the classification identifier "Program Logic" is at the very front of the initial log sequence. It should be noted that if there is sub-log content information corresponding to the same classification identifier in the initial log sequence, the new sub-log content information can be written before or after the sub-log content information with the same classification identifier, as long as it is adjacent to the sub-log content information with the same classification identifier, rather than being cross-written with sub-log content information with different classification identifiers. The specific writing method is determined by the actual usage scenario and is not limited in this embodiment. In addition, it should also be noted that there may be a situation in the initial log information where there is more than one classification identifier. For example, it includes "Program Logic" and "Art Resources", and the corresponding log content information is "The function of Equipment A has been newly added, enabling the use of Equipment A in the mecha combat mode; The style B of Equipment A has been newly added, enabling the function of changing styles during the use of Equipment A." In this case, after the business operation task selects the module identifier, the classification identifier is selected twice consecutively to generate the corresponding template; in this case, based on these two classification identifiers and the log content information, two sub-log content information can be generated: "Program Logic: The function of Equipment A has been newly added, enabling the use of Equipment A in the mecha combat mode." and "Art Resources: The style B of Equipment A has been newly added, enabling the function of changing styles during the use of Equipment A." The specific number of classification identifiers included in the log generation method is limited by the actual implementation scenario and is not limited in this embodiment.

[0099] In summary, through this method, the relevant content in the log content information is stored at the corresponding position in the initial log sequence, and this standardized approach simplifies the subsequent processing of this information.

[0100] Step S108: When the initial log sequence meets the preset log conversion conditions, generate the target log information corresponding to the initial log sequence through the log processing model.

[0101] Specifically, after determining the initial log sequence and writing the relevant part of the log content information into the initial log sequence, the target log information can be created based on this.

[0102] Among them, the log conversion condition can be understood as a preset precondition for the generation process of target log information. It should be noted that the log conversion condition can be a preset time, or the number of sub-log content information written in the initial log sequence, etc. Its specific setting method is determined by the actual usage scenario, and this embodiment does not limit it. The log processing model can be understood as a neural network model that has been trained to meet the preset conversion effect. It involves natural language processing technology. By converting one technical language to obtain another spoken language, it realizes the conversion from the initial log information for R & D personnel to the target log information for users. In addition, since the target log information is for users, in order to give users a better immersive experience, the target log information will inevitably apply the language in the application environment of the relevant software. To simplify the training process, the application environment can also be captured as a relevant parameter in the neural network training process and added to the training; in this case, for the log processing models obtained in different application environments, even when processing the same initial log information, the converted target log information is different. For example, if the initial log information is "The character adds a new appearance", the target log information obtained in one environment is "The mecha can use the load form during combat", and the target log information obtained in another environment is "Carry out the Halloween event and add Halloween sets"; the target log information can be understood as the log information after conversion and is the log information for users.

[0103] Based on this, when the preset log conversion condition is met, the generation of the target log can be carried out. Based on the obtained initial log sequence, the information in it is processed, and finally, through the processing of the log processing model, the target log information for users is obtained.

[0104] Furthermore, the input of the neural network model is implemented in vector form. In this embodiment, the specific implementation method for generating the target log information based on the log processing model is as follows:

[0105] Read the log content information to be processed and the corresponding classification identifier to be processed in the initial log sequence; construct the information vector corresponding to the log content information to be processed and the identifier vector corresponding to the classification identifier to be processed; fuse the information vector and the identifier vector, and input the fused log vector to be processed into the log processing model for processing to obtain the target log information.

[0106] Among them, the log content information to be processed can be understood as a set of sub-log content information with the same classification identifier; the classification identifier to be processed can be understood as the classification identifier corresponding to the log content information to be processed.

[0107] Based on this, determine the sub-log content information of the same classification identifier that needs to be converted in the initial log sequence as the log content information to be processed, and determine this classification identifier as the classification identifier to be processed; construct a corresponding information vector based on the obtained log content information to be processed, and construct a corresponding identifier vector based on the classification identifier to be processed; then fuse the obtained information vector and identifier vector to obtain the log vector to be processed, and input the log vector to be processed into the log processing model for processing. After the processing is completed, the target log information is obtained.

[0108] Following the above example, in the initial log sequence, determine the classification identifier "program logic" as the classification identifier to be processed, and the corresponding "Program logic: A new function of equipment A is added, and the use of equipment A in the mecha combat mode is realized." as the log content information to be processed. Based on these two, construct the information vector m and the identifier vector n, fuse the information vector m and the identifier vector n to obtain the log vector q to be processed, and input the log vector q to be processed into the log processing model C for processing to obtain the processed target log information "In the mecha mode, J mecha can equip a lightsaber during the preparation process.", where the lightsaber corresponds to equipment A.

[0109] In summary, through the above method, the professional log content of relevant technical personnel can be automatically converted into the target log content for users, reducing the reading burden of users and enhancing the immersion of users.

[0110] Furthermore, the initial log sequence may also include relevant information stored previously. In this case, in order to generate the target log information, in this embodiment, the specific implementation method is as follows:

[0111] Select all the log content information in the initial log sequence as the log content information to be processed; and select all the classification identifiers in the initial log sequence as the classification identifiers to be processed; or, determine the log content information in the initial log sequence that does not contain the selected identifier as the log content information to be processed; select the classification identifier corresponding to the log content information that does not contain the selected identifier as the classification identifier to be processed.

[0112] Among them, the selected identifier can be understood as an identifier for marking the already selected log content information.

[0113] Based on this, when it is possible that the initial log sequence may also include relevant information stored previously, there are two methods to determine the log content information to be processed and the classification identifier to be processed. One is to select all the log content information in the initial log sequence as the log content information to be processed, and determine the corresponding classification identifier as the classification identifier to be processed; another way is to only select the newly added log content information as the log content information to be processed, and determine the corresponding classification identifier as the classification identifier to be processed. It should be noted that after the implementation of the second method, the selected log content information and classification identifier need to be added with a selection identifier to ensure the distinction between the log content information and classification identifier in the subsequent process of the log content information to be processed and the classification identifier to be processed.

[0114] Continuing with the above example, in the initial log sequence, in addition to the newly written log content information "Added function of Equipment A, enabling the use of Equipment A in the mecha combat mode" with the classification identifier of "Program Logic", it also includes the existing log content information "Added function of Equipment B, enabling the use of Equipment B in the mecha combat mode", and its corresponding classification identifier is "Program Logic". At this time, both can be selected as the log content information to be processed, and "Program Logic" is the classification identifier to be processed; another way is to determine the selection identifier for both, and select the log content information "Added function of Equipment A, enabling the use of Equipment A in the mecha combat mode" that does not contain the selection identifier as the log content information to be processed, and the corresponding "Program Logic" as the classification identifier to be processed. After selection, add the selection identifier to this log content information and classification identifier.

[0115] In summary, by determining the log content information to be processed and the classification identifier to be processed through the above two methods, selecting all can achieve a comprehensive description of the updated target log content, while the other way is incremental addition, which reduces the system's resource utilization and speeds up the processing efficiency.

[0116] Furthermore, the training process of the log processing model is specifically implemented as follows in this embodiment:

[0117] Obtain the initial sample log information, the sample classification identifier corresponding to the initial sample log information, and the target sample log information; input the initial sample log information and the sample classification identifier into the initial log processing model for processing to obtain the predicted log information corresponding to the initial sample log information; adjust the parameters of the initial log processing model according to the target sample log information and the predicted log information until a log processing model that meets the training stop condition is obtained.

[0118] Among them, the initial sample log information can be understood as the initial log information serving as the training sample; similarly, the sample classification identifier can be understood as the classification identifier corresponding to the training sample, and the target sample log information can be understood as the transformed target sample information corresponding to the initial sample log information; the initial log processing model can be understood as the log processing model that has been pre-trained; the predicted log information can be understood as the target log information obtained by processing the initial sample log information and the sample classification identifier through the initial log processing model.

[0119] Based on this, using the initial sample information and the sample classification identifier as the input of the initial log processing model, after being processed by the initial log processing model, the predicted log information is obtained. By comparing the differences between the predicted log information and the target sample log information, the initial log processing model can be continuously tuned to obtain a log processing model that meets the processing requirements.

[0120] In summary, through the above log processing model training method, the obtained log processing model can process the initial log information to obtain the log processing information that meets the requirements.

[0121] Furthermore, after the application has been updated multiple times, the content of the application itself has changed significantly, or when processing the function update of the application with a relatively low application frequency, it may occur that the target log information does not meet the expectations. At this time, it is necessary to further correct the target log information. In this embodiment, the specific implementation method is as follows:

[0122] Send the target log information to the audit node and receive the update request feedback by the audit node for the target log information; update the target log information according to the update request to obtain the log information to be published; perform the publishing process on the log information to be published according to the preset publishing policy.

[0123] Among them, the audit node can be understood as the relevant auditors, audit departments, etc. before sending the target log information; the update request can be understood as the content for the audit node to make corresponding modifications to the target log information; the log information to be published can be understood as the modified target log information.

[0124] Based on this, send the target log information to the audit node. The audit node audits the target log information and then sends an update request containing its own audit suggestions. Update the target log information according to the update request to obtain the log information to be published, and publish this log information to be published according to the preset publishing policy for users to view.

[0125] Continuing with the above example, the target log information "In the mecha mode, the J mecha can equip a lightsaber during the preparation process." is sent to the reviewer. The reviewer conducts a review and sends an update request. Based on this update request, the target log information is modified to obtain the log information to be published "In the mecha mode, for balance mechanism, the J mecha can equip a lightsaber during the preparation process.", and then this log information to be published is published according to the preset publishing strategy.

[0126] In summary, through the review of the review node, it is ensured that the published log information is more in line with expectations, and the situation where the log processing model produces log information that does not meet expectations due to not matching the application program that has been updated multiple times is reduced.

[0127] Furthermore, after the application program is updated multiple times, when the log processing model does not match the current application program, the log processing model needs to be updated. In this embodiment, the specific implementation method is as follows:

[0128] Adjust the parameters of the log processing model according to the log information to be published and the target log information, and update the log processing model.

[0129] Among them, by adjusting the parameters of the log processing model with the log information to be published obtained by modifying the review node and the target log information obtained by the log processing model, the update of the log processing model can be achieved.

[0130] In summary, by updating the log processing model in the above manner, the log processing model can match the application program after multiple updates, strengthening its applicable width.

[0131] In addition, Figure 2 is a schematic diagram of the operation interface of a log generation method provided by an embodiment of the present application. It can be seen that there are limitations in the operation interface during the reception of the selected initial log information, including but not limited to start and end times, senders. Then there is also a setting window for preset log conversion conditions, including but not limited to manual trigger and timed trigger; finally, there are also settings including application environment, log generation, variable setting, upload, and other related contents.

[0132] The log generation method provided by the present application realizes the automatic generation and typesetting of updated logs by receiving initial log information, then obtaining the log content information related to the initial log information, as well as the module identifier and classification identifier, determining the initial log sequence related to the log content information according to the module identifier, and dividing and writing the log content information into the relevant positions of the initial log sequence according to the classification identifier. Finally, when the initial log sequence meets the preset log conversion conditions, the method of generating the target log information corresponding to the initial log sequence through the log processing model enhances communication, saves workload, and improves the efficiency of log generation.

[0133] The following combines the attached Figure 3 Taking the log update method provided by this application for the navigation software application as an example, the log update method will be further described. Among them, Figure 3 FIG. shows a processing flow chart of a log update method applied to a navigation software provided by an embodiment of the present application, which specifically includes the following steps:

[0134] Step S302: Receive a log update request.

[0135] Specifically, after a certain navigation software is updated in version, the enterprise of the navigation software needs to generate a corresponding version update log. Based on this requirement, relevant business personnel send a log update request, and the server receives this log update request.

[0136] Step S304: In response to the log update request, scan the log submission record to obtain log time information.

[0137] Specifically, according to the log update request, scan the log update record of the enterprise's proprietary R & D platform to obtain the log information A submitted after the last version update.

[0138] Step S306: Read the initial log information based on the log submission record and the log time information.

[0139] Specifically, determine the initial log information S as the log information A. It should be noted that the log information A is input by the developers of this navigation software in the log collection interface of the enterprise's proprietary R & D platform.

[0140] Step S308: Parse the initial log information to obtain log content information and module identifiers and classification identifiers associated with the log content information.

[0141] Specifically, the initial log information S is parsed to obtain the log content information "The search function is added, and the shopping malls around the searched map target point are realized", as well as the module identifier [Search] and the classification identifier "Program".

[0142] Step S310: Traverse the log sequence library to determine the log sequence identifiers of each log sequence in the log sequence library.

[0143] Step S312: Compare the log sequence identifiers of each log sequence with the module identifier.

[0144] Step S314: Select the log sequence with the same identifier as the initial log sequence according to the comparison result.

[0145] Specifically, select the log sequence with the log sequence identifier [Search] as the initial log sequence.

[0146] Step S316: Divide the log content information based on the classification identifier to obtain at least one sub-log content information.

[0147] Specifically, divide the log content information based on the classification identifier "Program" to obtain the sub-log content information "Program: Added a search function to implement searching for shopping malls around the map target point".

[0148] Step S318: Determine the writing positions corresponding to each sub-log content information in the initial log sequence based on the classification identifier.

[0149] Specifically, determine that the writing position of the sub-log content information "Program: Added a search function to implement searching for shopping malls around the map target point" in the initial log sequence is at the end based on the classification identifier "Program".

[0150] Step S320: Write each sub-log content information into the initial log sequence according to the writing position.

[0151] Step S322: Determine the log content information in the initial log sequence that does not contain the selection identifier as the log content information to be processed.

[0152] Specifically, determine that the log content information "Added a search function to implement searching for shopping malls around the map target point" that does not contain the selection identifier is the log content information to be processed.

[0153] Step S324: Select the classification identifier corresponding to the log content information that does not contain the selection identifier as the classification identifier to be processed.

[0154] Specifically, determine that the classification identifier "Program" is the classification identifier to be processed.

[0155] Step S326: When the initial log sequence meets the preset log conversion condition, generate the target log information corresponding to the initial log sequence through the log processing model.

[0156] Specifically, the preset log conversion condition is that 12 hours after receiving the log update request, after 12 hours, generate the target log information "Added a search function to search for shopping malls near the destination" through the log processing model.

[0157] Step S328: Send the target log information to the audit node and receive the update request feedback by the audit node for the target log information.

[0158] Specifically, send the target log information "The search function has been added, and shopping malls near the destination can be searched" to the reviewer. After the reviewer conducts the review, the update request feedback by the reviewer for the target log information.

[0159] Step S330: Update the target log information according to the update request to obtain the log information to be published.

[0160] Specifically, update the target log information according to the update request to obtain the log information to be published "One-click search for shopping malls near the destination".

[0161] Step S332: Perform a publishing process on the log information to be published according to a preset publishing policy.

[0162] Step S334: Adjust the parameters of the log processing model according to the log information to be published and the target log information, and update the log processing model.

[0163] The log generation method provided by this application, by receiving the initial log information, then obtaining the log content information related to the initial log information, as well as the module identifier and classification identifier, determining the initial log sequence related to the log content information according to the module identifier, and dividing and writing the log content information into the relevant positions of the initial log sequence according to the classification identifier. Finally, when the initial log sequence meets the preset log conversion conditions, the method of generating the target log information corresponding to the initial log sequence through the log processing model realizes the automated generation and typesetting of updated logs, enhances communication, saves workload, and improves the efficiency of log generation.

[0164] Corresponding to the above method embodiment, this application also provides a log update device embodiment. Figure 4 The structure diagram of a log update device provided by an embodiment of this application is shown. As Figure 4 shown, the device includes:

[0165] A receiving module 402, configured to receive initial log information;

[0166] An analysis module 404, configured to analyze the initial log information to obtain log content information and a module identifier and a classification identifier associated with the log content information;

[0167] A writing module 406, configured to determine an initial log sequence according to the module identifier, and write the log content information divided according to the classification identifier into the initial log sequence;

[0168] A generation module 408, configured to generate target log information corresponding to the initial log sequence through a log processing model when the initial log sequence meets a preset log conversion condition.

[0169] In an optional embodiment, the receiving module 402 may further be configured to:

[0170] Receive a log update request; scan the log submission record in response to the log update request to obtain log time information; read the initial log information based on the log submission record and the log time information.

[0171] In an optional embodiment, the writing module 406 may further be configured to:

[0172] Traverse the log sequence library to determine the log sequence identifiers of each log sequence in the log sequence library; compare the log sequence identifiers of each log sequence with the module identifier; select the log sequence with the same identifier as the initial log sequence according to the comparison result.

[0173] In an optional embodiment, the writing module 406 may further be configured to:

[0174] Divide the log content information based on the classification identifier to obtain at least one sub-log content information; determine the writing position corresponding to each sub-log content information in the initial log sequence based on the classification identifier; write each sub-log content information into the initial log sequence according to the writing position.

[0175] In an optional embodiment, the generation module 408 may further be configured to:

[0176] Read the to-be-processed log content information and the corresponding to-be-processed classification identifier in the initial log sequence; construct an information vector corresponding to the to-be-processed log content information and an identifier vector corresponding to the to-be-processed classification identifier; fuse the information vector and the identifier vector, and input the fused to-be-processed log vector into the log processing model for processing to obtain the target log information.

[0177] In an optional embodiment, the generation module 408 may further be configured to:

[0178] Select all the log content information in the initial log sequence as the to-be-processed log content information; and select all the classification identifiers in the initial log sequence as the to-be-processed classification identifiers; or, determine the log content information in the initial log sequence that does not contain the selected identifier as the to-be-processed log content information; select the classification identifier corresponding to the log content information that does not contain the selected identifier as the to-be-processed classification identifier.

[0179] In an alternative embodiment, the initial log information is input and generated by an operation and maintenance operator through a log collection interface in the client, and uploaded by the client; wherein, the log collection interface includes a module identifier selection sub-interface and a classification identifier selection sub-interface; the initial log information input by the operation and maintenance operator is collected through the module identifier selection sub-interface and the classification identifier selection sub-interface.

[0180] In an alternative embodiment, the generating module 408 may further be configured to:

[0181] Obtain initial sample log information, as well as the sample classification identifier and target sample log information corresponding to the initial sample log information; input the initial sample log information and the sample classification identifier into an initial log processing model for processing to obtain the predicted log information corresponding to the initial sample log information; adjust the parameters of the initial log processing model according to the target sample log information and the predicted log information until a log processing model that meets the training stop condition is obtained.

[0182] In an alternative embodiment, the log generating device further includes:

[0183] An auditing module, configured to send the target log information to an auditing node, and receive an update request feedback by the auditing node for the target log information; update the target log information according to the update request to obtain log information to be published; perform a publishing process on the log information to be published according to a preset publishing policy.

[0184] In an alternative embodiment, the log generating device further includes:

[0185] A parameter tuning device, configured to tune the parameters of the log processing model according to the log information to be published and the target log information, and update the log processing model.

[0186] The log generating device provided in this application realizes the automated generation and layout of updated logs by receiving initial log information, then obtaining log content information related to the initial log information, as well as module identifiers and classification identifiers, determining an initial log sequence related to the log content information according to the module identifier, and dividing and writing the log content information into relevant positions of the initial log sequence according to the classification identifier. Finally, when the initial log sequence meets the preset log conversion condition, the target log information corresponding to the initial log sequence is generated by the log processing model, enhancing communication, saving workload, and improving the efficiency of log generation.

[0187] The above is a schematic solution of a log update device according to this embodiment. It should be noted that the technical solution of the log update device and the technical solution of the above log update method belong to the same concept. For the details not described in the technical solution of the log update device, reference can be made to the description of the technical solution of the above log update method. In addition, each component in the device embodiment should be understood as a functional module that must be established to implement each step of the program flow or each step of the method. Each functional module is not an actual functional segmentation or separation limitation. The device claim defined by such a set of functional modules should be understood as mainly implementing the functional module architecture of the solution through the computer program recorded in the specification, rather than understanding as mainly implementing the physical device of the solution through hardware means.

[0188] Figure 5 FIG. shows a structural block diagram of a computing device 500 according to an embodiment of the present application. The components of the computing device 500 include, but are not limited to, a memory 510 and a processor 520. The processor 520 is connected to the memory 510 through a bus 530, and a database 550 is used to store data.

[0189] The computing device 500 further includes an access device 540, and the access device 540 enables the computing device 500 to communicate via one or more networks 560. Examples of these networks include a Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the Internet. The access device 540 may include one or more of any type of wired or wireless network interface (for example, a Network Interface Card (NIC)), such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a Worldwide Interoperability for Microwave Access (Wi-MAX) interface, an Ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a Bluetooth interface, a Near Field Communication (NFC) interface, and so on.

[0190] In an embodiment of the present application, the above components of the computing device 500 and Figure 5 other components not shown in Figure 5 may also be connected to each other, for example, through a bus. It should be understood that

[0191] The computing device 500 can be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., a tablet computer, a personal digital assistant, a laptop computer, a notebook computer, a netbook, etc.), a mobile phone (e.g., a smart phone), a wearable computing device (e.g., a smart watch, smart glasses, etc.) or other types of mobile devices, or a stationary computing device such as a desktop computer or a PC. The computing device 500 can also be a mobile or stationary server.

[0192] Wherein, the processor 520 is configured to execute the following computer-executable instructions:

[0193] Receive initial log information;

[0194] Parse the initial log information to obtain log content information, as well as a module identifier and a classification identifier associated with the log content information;

[0195] Determine an initial log sequence according to the module identifier, and write the log content information divided according to the classification identifier into the initial log sequence;

[0196] When the initial log sequence meets a preset log conversion condition, generate target log information corresponding to the initial log sequence through a log processing model.

[0197] The above is a schematic solution of a computing device in this embodiment. It should be noted that the technical solution of this computing device and the technical solution of the above log update method belong to the same concept. For the details not described in the technical solution of the computing device, reference can be made to the description of the technical solution of the above log update method.

[0198] An embodiment of the present application further provides a computer-readable storage medium, which stores computer instructions, and when the instructions are executed by a processor, they are used for:

[0199] Receive initial log information;

[0200] Parse the initial log information to obtain log content information, as well as a module identifier and a classification identifier associated with the log content information;

[0201] Determine an initial log sequence according to the module identifier, and write the log content information divided according to the classification identifier into the initial log sequence;

[0202] When the initial log sequence meets a preset log conversion condition, generate target log information corresponding to the initial log sequence through a log processing model.

[0203] The above is a schematic solution of a computer-readable storage medium according to this embodiment. It should be noted that the technical solution of this storage medium and the technical solution of the above log update method belong to the same concept. For the details not described in the technical solution of the storage medium, reference can be made to the description of the technical solution of the above log update method.

[0204] An embodiment of the present application further provides a chip, which stores a computer program. When the computer program is executed by the chip, the steps of the log update method are implemented.

[0205] The above describes specific embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0206] The computer instructions include computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc. It should be noted that the content included in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0207] It should be noted that for the foregoing method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the present application is not limited by the described action sequence, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily all essential to the present application.

[0208] In the above embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0209] The preferred embodiments of the present application disclosed above are only used to help illustrate the present application. The alternative embodiments do not describe all the details in detail, nor do they limit the invention to the specific embodiments described. Obviously, many modifications and variations can be made according to the content of the present application. The present application selects and specifically describes these embodiments in order to better explain the principle and practical application of the present application, so that those skilled in the art can well understand and utilize the present application. The present application is only limited by the claims and their full scope and equivalents.

Claims

1. A log generation method, characterized in that, it includes: Receiving initial log information, where the initial log information is the update log generated by updating the application; Parsing the initial log information to obtain log content information, as well as a module identifier and a classification identifier associated with the log content information, where the module identifier is information about the module updated by the application, and the classification identifier is information about the update type of the application update; Determining an initial log sequence according to the module identifier, and writing the log content information divided according to the classification identifier into the initial log sequence, where the initial log sequence is a sequence containing log content information; When the initial log sequence meets the preset log conversion condition, generating target log information corresponding to the initial log sequence through a log processing model, where the target log information is user-oriented log information.

2. The method according to claim 1, characterized in that, the receiving of the initial log information includes: Receiving a log update request; Scanning the log submission record in response to the log update request to obtain log time information; Reading the initial log information based on the log submission record and the log time information.

3. The method according to claim 1, characterized in that, the determining of the initial log sequence according to the module identifier includes: Traversing the log sequence library to determine the log sequence identifiers of each log sequence in the log sequence library; Comparing the log sequence identifiers of each log sequence with the module identifier; Selecting the log sequence with the same identifier as the initial log sequence according to the comparison result.

4. The method according to claim 1, characterized in that, the writing of the log content information divided according to the classification identifier into the initial log sequence includes: Dividing the log content information based on the classification identifier to obtain at least one sub-log content information; Determining the writing positions corresponding to each sub-log content information in the initial log sequence based on the classification identifier; Writing each sub-log content information into the initial log sequence according to the writing positions.

5. The method according to claim 1, characterized in that, the generating of the target log information corresponding to the initial log sequence through the log processing model includes: Reading the log content information to be processed and the classification identifier to be processed corresponding to the log content information to be processed in the initial log sequence; Constructing an information vector corresponding to the log content information to be processed and an identifier vector corresponding to the classification identifier to be processed; Fusing the information vector and the identifier vector, and inputting the fused log vector to be processed into the log processing model for processing to obtain the target log information.

6. The method according to claim 5, characterized in that, the reading of the log content information to be processed and the classification identifier to be processed corresponding to the log content information to be processed in the initial log sequence includes: Select all the log content information in the initial log sequence as the log content information to be processed; and select all the classification identifiers in the initial log sequence as the classification identifiers to be processed. Or, Determine the log content information in the initial log sequence that does not contain the selected identifier as the log content information to be processed; select the classification identifier corresponding to the log content information that does not contain the selected identifier as the classification identifier to be processed.

7. The method according to claim 1, wherein, The initial log information is generated by a business operator through a log collection interface in a client and uploaded by the client; wherein, the log collection interface includes a module identifier selection sub-interface and a classification identifier selection sub-interface; the initial log information input by the business operator is collected through the module identifier selection sub-interface and the classification identifier selection sub-interface.

8. The method according to claim 1, wherein, The training of the log processing model includes: Obtain initial sample log information, as well as the sample classification identifier and target sample log information corresponding to the initial sample log information; Input the initial sample log information and the sample classification identifier into an initial log processing model for processing to obtain the predicted log information corresponding to the initial sample log information; Adjust the parameters of the initial log processing model according to the target sample log information and the predicted log information until a log processing model that meets the training stop condition is obtained.

9. The method according to claim 1, wherein, After the step of generating the target log information corresponding to the initial log sequence by the log processing model is executed, it further includes: Send the target log information to an audit node and receive an update request feedback by the audit node for the target log information; Update the target log information according to the update request to obtain the log information to be published; Perform a publishing process on the log information to be published according to a preset publishing policy.

10. The method according to claim 9, wherein, After obtaining the log information to be published, it further includes: Adjust the parameters of the log processing model according to the log information to be published and the target log information to update the log processing model.

11. A log generation device, wherein, It includes: A receiving module, configured to receive initial log information, wherein the initial log information is an update log generated by updating an application; A parsing module, configured to parse the initial log information to obtain log content information, as well as a module identifier and a classification identifier associated with the log content information, wherein the module identifier is information about the module updated by the application, and the classification identifier is information about the update type of the application update; A writing module, configured to determine an initial log sequence according to the module identifier and write the log content information divided according to the classification identifier into the initial log sequence, wherein the initial log sequence is a sequence containing log content information; A generation module, configured to generate target log information corresponding to the initial log sequence through a log processing model when the initial log sequence meets a preset log conversion condition, where the target log information is user-oriented log information.

12. A computing device, characterized in that, it includes: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the steps of the log generation method according to any one of claims 1 to 10.

13. A computer-readable storage medium storing computer instructions, characterized in that, when the instructions are executed by a processor, the steps of the log generation method according to any one of claims 1 to 10 are implemented.

14. A computer program product, characterized in that, it includes computer instructions, and when the computer instructions are executed by a processor, the steps of the log generation method according to any one of claims 1 to 10 are implemented.

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