CAD instruction optimization method and system combined with user behavior analysis

Abstract

The invention relates to the technical field of engineering drawing interaction, and provides a CAD instruction optimization method and system combined with user behavior analysis. The method comprises the following steps: identifying a CAD operation task which is performed by a user and performing scene analysis to generate a CAD task scene; on the basis of a CAD task scene, instruction personalized configuration based on the operation frequency and the operation path is executed, primary optimization of an instruction toolbar is completed, and real-time operation characteristics of a user are continuously monitored; instruction continuity prediction based on the CAD base file is performed based on the real-time operational features to predict a continuity instruction to complete quadratic optimization of the instruction toolbar. According to the method and the device, the technical problems that the adaptability of the instruction toolbar is poor and intelligent optimization is difficult to perform according to operation habits of different users in the use process of a user in an existing CAD system are solved, and the technical effects of realizing personalized configuration and continuous optimization of the instruction toolbar through user behavior analysis, improving CAD operation efficiency and enhancing user experience are realized.

Description

Technical Field

[0001] This application relates to the technical field of engineering drawing interaction, and particularly to a CAD instruction optimization method and system combined with user behavior analysis. Background Art

[0002] Computer-Aided Design (CAD) software, as the core tool for modern engineering design, has seen a continuous increase in its functional complexity with the growth of industry demands. However, the bottleneck problem of interaction efficiency has become increasingly prominent. Traditional CAD systems usually adopt a static instruction toolbar configuration, mechanically stacking hundreds of operation instructions in the interface through fixed classifications (such as drawing, modification, annotation), resulting in users frequently falling into an inefficient cycle of searching for instructions - switching tab pages - verifying functions during cross-stage tasks. Especially in scenarios such as mechanical assembly and architectural drawing, the operation flow of designers often involves alternating execution of multiple instructions. For example, after drawing the basic contour, it is necessary to quickly switch to dimension annotation or constraint addition. The static toolbar cannot perceive the current task stage and operation intention of the user, forcing the operation path to be lengthened. In addition, there are significant differences in the call preferences of instruction sets among users in different professional fields (such as structural engineers and electrical engineers). Novice users rely on the explicit guidance of graphical buttons, while senior users are more inclined to quickly access shortcut keys and frequently used instructions. Existing systems lack the ability to dynamically model user behavior characteristics and are difficult to achieve personalized adaptation. Although some improvement solutions attempt to alleviate the efficiency problem by manually presetting commonly used instruction sets, they do not solve the essential defects such as the interruption of operation continuity and redundant switching across instruction sets. Especially when dealing with complex engineering documents, users still face interaction barriers such as frequent interruption of the operation flow and high accidental touch rates. Against this background, how to achieve dynamic optimization of the instruction toolbar and prediction of operation intention by deeply mining the correlation between user behavior characteristics and task scenarios has become the key breakthrough point for improving the human-computer interaction efficiency of CAD software. Summary of the Invention

[0003] This application provides a CAD instruction optimization method and system combined with user behavior analysis, aiming to solve the technical problem that the existing CAD system has poor adaptability of the instruction toolbar during user use and is difficult to perform intelligent optimization according to different user operation habits.

[0004] In the first aspect disclosed in this application, a CAD instruction optimization method combined with user behavior analysis is provided. The method includes: identifying the CAD operation task that the target user is performing and performing scene analysis to generate a CAD task scene; performing instruction personalization configuration based on operation frequency and operation path based on the CAD task scene to complete the first optimization of the instruction toolbar, and continuously monitoring the real-time operation characteristics of the target user; performing instruction continuity prediction based on the CAD basic file based on the real-time operation characteristics to predict continuous instructions and complete the second optimization of the instruction toolbar.

[0005] Another aspect disclosed in this application provides a CAD instruction optimization system combined with user behavior analysis. The system includes: a scene parsing module: identifying the CAD operation task that the target user is performing and performing scene parsing to generate a CAD task scene; a primary optimization module: performing personalized configuration of instructions based on the operation frequency and operation path based on the CAD task scene, completing the primary optimization of the instruction toolbar, and continuously monitoring the real-time operation characteristics of the target user; a secondary optimization module: performing prediction of instruction continuity based on the CAD basic file based on the real-time operation characteristics to predict continuous instructions and complete the secondary optimization of the instruction toolbar.

[0006] One or more technical solutions provided in this application have at least the following technical effects or advantages: The above CAD instruction optimization method combined with user behavior analysis first identifies the CAD operation task that the user is executing, and generates a corresponding CAD task scene through scene parsing. Subsequently, based on the operation frequency and path in the task scene, personalized configuration of the instruction toolbar is performed to achieve the first optimization. This process continuously monitors the real-time operation characteristics of the user to ensure that the toolbar settings always match the user's needs. Then, based on the structure of the CAD basic file and the user's operation characteristics, possible continuous instructions are predicted, thereby further optimizing the toolbar to complete the secondary optimization and improving the user's operation efficiency.

[0007] The above description is only an overview of the technical solutions of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically gives the specific implementation manners of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0009] Figure 1 It is a schematic flowchart of a CAD instruction optimization method combined with user behavior analysis in an embodiment.

[0010] Figure 2 It is an architecture diagram of a CAD instruction optimization system combined with user behavior analysis in an embodiment.

[0011] Description of the reference numerals: scene parsing module 11, primary optimization module 12, secondary optimization module 13. Specific Embodiments

[0012] In an embodiment of the present application, by providing a CAD instruction optimization method and system combined with user behavior analysis, the technical problem that the existing CAD system has poor adaptability of the instruction toolbar during user use and is difficult to perform intelligent optimization according to the operation habits of different users is solved.

[0013] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0014] It should be noted that the terms "including" and "having", and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products, or devices.

[0015] Embodiment 1, as Figure 1 shown, the present application provides a CAD instruction optimization method combined with user behavior analysis, and the method includes: Identifying the CAD operation task that the target user is performing and performing scene analysis to generate a CAD task scene.

[0016] In an embodiment of the present application, when the target user starts the CAD editing software, first analyze the operation behavior of the user, determine the current work content of the target user, and infer the specific CAD task field that the user is engaged in through the analysis of graph features. For example, the engineering drawing drawing scene requires the use of a large number of drawing tools and dimension markings; graphic design focuses on the arrangement and layout of two-dimensional graphics; the mechanical part design scene may involve complex detail processing and three-dimensional modeling; the building three-dimensional modeling scene requires spatial three-dimensional construction and structural analysis; the circuit diagram design scene focuses on the connection of electronic components and the use of electrical symbols. The generation of each task scene aims to provide a personalized tool and operation environment for the user, thereby improving the efficiency and accuracy of CAD operations.

[0017] Furthermore, the present application provides identifying the CAD operation task that the target user is performing and performing scene analysis to generate a CAD task scene, including: When the target user starts the target CAD editing software, read the task creation mode of the target user, including the CAD file import mode or the new file mode; if the task creation mode is the CAD file import mode, read the imported file; perform drawing feature analysis on the imported file to generate the CAD task scenario.

[0018] Preferably, when the target user starts the CAD editing software, first identify and read the task creation mode of the target user to determine the operation type selected by the user. The task creation mode is usually divided into the CAD file import mode or the new file mode. If it is detected that the user has selected the CAD file import mode, the files imported by the user will be read. These files are usually external CAD files and may contain existing design drawings or project files. After reading the imported file, drawing feature analysis will be performed on the file content, that is, analyze and obtain information such as geometric shapes, layer structures, symbols, annotations, dimensions, etc. contained in the file. The purpose of this process is to understand the design elements and structures in the file, extract the key features therein, and then compare these features with the features of the corresponding scenario to determine the current CAD task scenario. Exemplarily, if there are a large number of floor plans, elevation views, building symbols (such as doors, windows, walls, stairs, etc.) and large structures in the drawing, and the dimension units are relatively large (such as meters or centimeters), then the drawing can be classified as an architectural design task scenario; if the drawing contains features such as complex parts, assembly drawings, precise dimension annotations, hole diameters, etc., and the dimension units are relatively small (such as millimeters or micrometers), then the drawing is very likely to belong to the mechanical part design task scenario. If the drawing contains electrical symbols, circuit element connections, wire routing and other elements, and there are usually no obvious physical dimension annotations in the design content, it can be judged as a circuit diagram design task scenario. If the drawing contains multiple 2D plane elements, such as layout drawings, decoration drawings, etc., and there is a large amount of arrangement and alignment information, then the drawing may belong to the plane design scenario. The determined CAD task scenario will be used to adjust the toolbar and operation interface subsequently to make it more suitable for the current design task, thereby providing an optimized operation environment for the user and helping the user to perform subsequent operations more efficiently.

[0019] Further, after reading the task creation mode of the target user provided by the present application, it further includes: If the task creation mode is the new file mode, read the custom template; perform drawing feature statistics under the similar template based on the custom template to generate the CAD task scenario.

[0020] Optionally, after the user selects the new file mode, a preset custom template will be read. The custom template usually includes the standard drawing structure, common graphic elements, symbol library, layer configuration, dimensioning, etc. set by the user in advance. Subsequently, the geometric shapes, layer structures, symbols, annotations, dimensions, and other drawing features included in the custom template are parsed, and then these drawing features are matched with the typical templates of each task scenario. The number of times each drawing feature appears in this typical template is counted, and then compared with the preset minimum number of drawing features of each typical template to find the most similar typical template as the similar template of the custom template. The task scenario corresponding to the similar template is used as the current CAD task scenario of the user. Generally speaking, by this way of determining the task scenario, tools and operation environments that more meet the user's design requirements can be provided for the user, enabling them to quickly adapt to and efficiently complete design tasks, and improving work efficiency.

[0021] Perform instruction personalization configuration based on operation frequency and operation path based on the CAD task scenario, complete the first optimization of the instruction toolbar, and continuously monitor the real-time operation characteristics of the target user.

[0022] In one embodiment, after generating the CAD task scenario, start performing instruction personalization configuration based on operation frequency and operation path to optimize the layout of the instruction toolbar. Specifically, according to the user's historical operation habits in the current task scenario, analyze the possible operation paths and frequently used commands, so as to count the most commonly used instructions of the user, such as drawing commands, modification commands, or specific function commands. Subsequently, based on the possible operation paths of the user, analyze the operation steps and sequences relied on by the user when completing the task, and optimize the command arrangement in the toolbar for these operation steps. For commands that the user often switches, these commands will be preferentially displayed to reduce the time and operation complexity for the user to find instructions. In addition, the real-time operation characteristics of the user will be continuously monitored, and the operation data of the user will be updated in real time. As the user's operations change, the toolbar configuration will be automatically adjusted according to the new operation trends to ensure that the toolbar always conforms to the user's work habits and needs, further improving the operation efficiency. This personalized instruction configuration can ensure that the toolbar always provides the most suitable functions and commands for the user in different task scenarios, improving the efficiency and convenience of the workflow.

[0023] Furthermore, the present application provides instruction personalization configuration based on operation frequency and operation path based on the CAD task scenario, completing the first optimization of the instruction toolbar, including: Collect the historical mapping operation records of the target user based on the CAD task scenario; predict the operation path for the CAD task scenario based on the historical mapping operation records to generate a predicted operation path; perform a descending analysis of the operation frequency of any instruction for each operation stage in the predicted operation path based on the historical mapping operation records to generate a primary toolbar optimization plan for each operation stage; and complete the primary optimization of the instruction toolbar with the primary toolbar optimization plans for each operation stage.

[0024] Preferably, first obtain the historical operation log of the target user. This historical operation log includes various operations performed by the user in past CAD tasks, such as drawing commands, modification commands, view adjustments, etc. Filter the historical operation log using the determined CAD task scenario to obtain the user's operation behavior, operation time sequence, and tools used each time in this CAD task scenario, and then store these data in sequence to obtain the historical mapping operation records of the target user for subsequent analysis and optimization. Subsequently, based on the historical mapping operation records, predict the operation path of the user. The operation path refers to the sequence of operation steps when the user executes a task. For example, when the user is drawing a certain structure, they may first draw the basic shape, then perform dimensioning, and finally add decorative lines, etc. During the prediction process, the operation paths in the historical mapping operation records are statistically analyzed to determine the number of occurrences of each operation path, and the operation path with the most occurrences is used as the prediction result this time and output in the form of a predicted operation path. After that, in the predicted operation path, perform an operation frequency analysis on the instructions executed in each operation stage, count the instructions commonly used by the user in each stage, and sort them according to the usage frequency. For example, a certain operation stage may frequently use the trim command, while another stage may more commonly use the fill command. By arranging the frequencies of these operations in descending order, find the most commonly used instructions in each stage. Then, according to the descending analysis of the instruction frequencies in each operation stage, generate a primary toolbar optimization plan for each stage. These optimization plans will, according to the operation frequency, preferentially place the most commonly used instructions in prominent positions on the toolbar to ensure that the user can quickly access the commonly used commands when executing each operation stage. Finally, according to the generated primary toolbar optimization plans for each operation stage, optimize the configuration of the instruction toolbar, that is, dynamically adjust the positions of the buttons corresponding to each instruction in the instruction toolbar so that the user can complete the task more efficiently throughout the design process, meet the user's work requirements and operation habits, and thus improve work efficiency.

[0025] Furthermore, this application provides a method for performing a descending analysis of the operation frequency of any instruction for each operation stage in the predicted operation path based on the historical mapping operation records to generate a primary toolbar optimization plan for each operation stage, including: Extract the mapping operation records for each operation stage from the historical mapping operation records; based on the mapping operation records for each operation stage, perform the usage frequency statistics and descending order processing of any instruction, and generate the instruction arrangement priorities for each operation stage; generate a primary toolbar optimization plan for each operation stage based on the instruction arrangement priorities for each operation stage.

[0026] Optionally, first extract the specific commands executed by the user at different operation stages of the predicted operation path from the historical mapping operation records. These operation stages can be each step experienced by the user during the task completion process, such as from drawing basic graphics to adding dimension markings, and then to modification and optimization, etc. Different commands and tools will be used in each operation stage, such as lines, circles, dimension markings, trimming, mirroring, etc. By extracting these records stage by stage, the mapping operation records for each operation stage are constructed. After extracting the mapping operation records for each operation stage, perform the usage frequency statistics on the commands within each stage. Specifically, the number of times each command is used in this stage will be counted to generate the usage frequency data for each instruction, and then the usage frequencies of these instructions will be sorted in descending order to determine which commands are the most frequently used in this stage. For example, if the trimming command is used most frequently in a certain stage, it will be ranked at the top, while the commands with lower usage frequencies will be ranked behind. After completing the frequency statistics and descending order processing, generate the arrangement priorities for the instructions in each operation stage based on the usage frequencies of the instructions in each stage. This instruction arrangement priority can ensure that the user can access the most frequently used commands first during work, reducing the time for searching and selecting commands. Finally, generate a personalized toolbar optimization plan for each operation stage based on the instruction arrangement priorities for each operation stage. These plans preferentially place the frequently used commands and tools in the most convenient positions on the toolbar according to the descending order of the operation frequencies, ensuring that the user can quickly call the required commands when performing each operation stage. The optimization plan may include adjusting the command order on the toolbar, merging related commands, or dynamically loading different toolbar configurations according to different operation stages, etc. In summary, this process extracts the commands for each operation stage from the historical mapping operation records, statistically analyzes and sorts the usage frequencies of each command in descending order, generates the priorities of the instructions in each stage, and then generates an optimized toolbar plan for each operation stage based on these priorities, enabling the user to access the frequently used commands more quickly and conveniently during actual operation, thereby improving work efficiency.

[0027] Perform the instruction continuity prediction based on the CAD basic file based on the real-time operation characteristics to predict the continuous instructions and complete the secondary optimization of the instruction toolbar.

[0028] In one embodiment, after monitoring based on real-time operation characteristics, instruction continuity prediction based on a CAD base file is performed. Specifically, first, the instruction sequence in the user's current operation is analyzed to identify the common operation processes and continuous instructions when the user performs a task. For example, during the drawing process, the user may frequently perform a series of operations, such as first drawing lines, then adding dimension annotations, and then performing trimming operations. Based on these operation steps, the instructions that the user may need to execute next are predicted, thereby inferring the operation commands that may be required next, and these instructions are automatically pre-loaded into the toolbar for the user to quickly access. This prediction mechanism makes the toolbar not just a static collection of commands, but can be intelligently and dynamically optimized according to the actual work needs of the user. When the user's next operation is successfully predicted, the toolbar is automatically updated to display the relevant instructions in advance, avoiding the user from frequently switching commands during the operation, improving the operation efficiency, and thus enhancing the user's work efficiency and experience.

[0029] Furthermore, the present application provides instruction continuity prediction based on the CAD base file by performing based on the real-time operation characteristics to predict continuous instructions to complete the secondary optimization of the instruction toolbar, including: Perform continuity monitoring of the CAD file structure to generate the CAD base file; based on the CAD base file, perform prediction of the next operation instruction of the real-time operation characteristics to generate the next prediction instruction set; perform real-time update of the instruction toolbar with the next prediction instruction set to complete the secondary optimization of the instruction toolbar.

[0030] Preferably, first, the continuity of the structure of the current CAD file is monitored, and the graphic structure, object relationships, and the user's current operation context in the CAD file are analyzed in real time to ensure that the structure and content of the file are always in a stable and editable state. Through continuous monitoring, a CAD basic file is generated, which contains the core elements of the current design project, such as graphic objects, layer information, dimensions, annotations, etc. data, not only reflecting the current design state, but also recording the user's operation progress and task objectives, providing a basis for subsequent operation prediction. Subsequently, based on real-time operation characteristics (such as the commands the user is executing, the operation steps that have been completed, etc.), drawing position matching and drawing action matching are performed in the CAD basic file, and then the adjacent positioning of the matching results is carried out to predict the operations that the user may perform next. For example, if the user is drawing a rectangle, it may be predicted that the user will add dimension annotations, fill the graphic, or perform other related operations next. The prediction process depends on analyzing historical operation data and the characteristics of the current task, so as to generate a next prediction instruction set, which contains multiple instructions that the user may execute. After that, based on the generated next prediction instruction set, the instruction toolbar is updated in real time, so that the most likely used instructions are preferentially displayed on the toolbar, completing the secondary optimization of the instruction toolbar. For example, if it is predicted that the user will use the trim command next, then the trim instruction will be preferentially placed in a prominent position on the toolbar. This update process is dynamic. As the user's operations continue, the toolbar will automatically adjust according to the new operation characteristics and prediction results to ensure that the toolbar can always meet the user's current design needs, improving the operation efficiency, and thus enhancing the user's work efficiency and experience.

[0031] Further, the present application provides a method for predicting the next operation instruction of the real-time operation feature based on the CAD basic file, generating a next prediction instruction set, including: Performing drawing position matching and drawing action matching of the real-time operation feature in the CAD basic file to generate a matching result; based on the matching result, performing positioning of adjacent drawing positions and actions in the CAD basic file to generate an adjacent matching result; constructing the next prediction instruction set with the adjacent matching result.

[0032] Optionally, first analyze the current real-time operation characteristics of the user, and identify the position information of the graphic elements or objects operated by the current user. For example, the user may be drawing a straight line, a rectangle, or other geometric figures. By checking the content at the corresponding position in the CAD basic file and according to the current operation of the user, match the accurate position of the figure in the file and the corresponding layer as the mapping position matching result. In addition, analyze the type of operation being performed by the user (such as drawing, modifying, annotating, etc.), and match these actions with the corresponding operation behaviors in the CAD basic file. For example, if the user is modifying the size of a certain figure, search for the corresponding dimension annotation in the file and match it with the user's operation action to obtain the mapping action matching result. Subsequently, summarize the obtained mapping position matching result and mapping action matching result to generate a matching result, that is, the relationship between the current operation of the user and the corresponding graphic elements in the file. This result will provide a basis for subsequent operation prediction. After that, based on the matching result, further analyze the adjacent positions of the graphic elements related to the current operation. For example, if the user is currently drawing a rectangle, view the four corner points of the rectangle and the positions of the adjacent graphic elements to identify the adjacent graphic positions related to the current operation. These positions are usually the areas where the user may perform the next operation. In addition to position matching, also analyze the adjacent operations related to the current operation action. For example, if the user is adding a dimension annotation to a certain figure, analyze whether similar annotation operations are required for the adjacent parts of the figure, that is, determine whether the adjacent images are annotated, so as to predict the possible next operation actions. Then, generate an adjacent matching result according to the adjacent relationship between the position and the action. This result reflects the association between the current operation of the user and the nearby graphics and actions, helping the system to more accurately predict the next operation steps of the user. Finally, based on the adjacent matching result, organize the operation instructions involved in the adjacent matching result into a next prediction instruction set. This next prediction instruction set contains a series of operation commands that the user may execute, helping the system to dynamically update the toolbar, preload the most likely to be used commands, and improve the user operation efficiency.

[0033] Furthermore, after the secondary optimization of the instruction toolbar is completed, the present application further includes: Based on the historical mapping operation records of the target user, identify the rollback-related instruction pairs with the rollback frequency higher than the preset frequency, where the rollback-related instruction pairs include the instructions executed before the rollback and the instructions executed after the rollback; collect the instruction explanations of each instruction in the rollback-related instruction pair, and when the target user clicks on any instruction in the rollback-related instruction pair, trigger an error verification reminder with the instruction explanation.

[0034] Preferably, first, all rollback (undo) operations are extracted from the historical drawing operation records of the target user, and the number of occurrences of each rollback-associated instruction pair is recorded as the rollback frequency of the rollback-associated instruction pair. Here, the rollback-associated instruction pair includes a command executed before the rollback (i.e., the command to be undone) and a command executed after the rollback (i.e., the new operation after the undo command). By comparing each of these rollback frequencies with a preset frequency, rollback-associated instruction pairs with rollback frequencies exceeding the preset frequency can be identified. For these rollback-associated instruction pairs with high occurrence frequencies, detailed instruction explanations for each instruction are collected. This instruction explanation can include information such as the function description, usage method, and precautions of the instruction. For example, if the rollback instruction is a trimming command, an explanation will be provided for this command, stating the function and usage scenario of the command. Then, the reason for each instruction rollback is also added to this instruction explanation, such as user operation errors, improper command order, or incorrect input parameters, etc. By collecting this information, specific error reasons and correction suggestions can be provided for each rolled-back instruction. When the target user clicks on a rollback-associated instruction in the toolbar, an error verification reminder is automatically activated, that is, a prompt box or pop-up window is displayed to explain the usage method, potential common errors, and how to use the instruction correctly to the user. The reminder can also include options such as whether to withdraw the operation or make corrections, etc., to help the user avoid performing incorrect operations again. This real-time error verification reminder mechanism can effectively reduce the probability of the user repeating rollback operations, help the user identify and correct errors more quickly, and thus improve work efficiency.

[0035] Furthermore, after the secondary optimization of the instruction toolbar provided by the present application is completed, it includes: Based on the historical drawing operation records of the target user, identify the view switching requirements after any operation instruction is executed; when the target user applies the corresponding operation instruction, perform a view switching reminder based on the view switching requirements.

[0036] Preferably, first, based on the historical drawing operation records of the target user, analyze which operation instructions may result in view switching requirements when executed. For example, in the historical drawing operation records, the user frequently uses the stretching command to draw three-dimensional objects, but sometimes fails to switch to a suitable three-dimensional view in a timely manner, which usually leads to inaccurate execution of the stretching operation. By analyzing the user's behavior, it can be identified that when specific operations such as the stretching command are executed, the user needs to switch views, providing an optimization basis for subsequent operations. When it is detected that the user is executing any one of these identified instructions, a prompt box or pop-up window is used to remind the user that a view switch is required for the current operation. For example, it is recommended to switch to the front view to ensure the accuracy of the stretching operation. Through this view switching reminder operation, the accuracy of the user's operations can be ensured, thereby improving the user's work efficiency and experience.

[0037] In summary, the embodiments of the present application at least have the following technical effects: In the embodiments of the present application, first, the CAD operation task being performed by the target user is identified and scene analysis is performed to generate a CAD task scene; subsequently, based on the CAD task scene, instruction personalized configuration based on operation frequency and operation path is performed to complete the first optimization of the instruction toolbar, and the real-time operation characteristics of the target user are continuously monitored; finally, based on the real-time operation characteristics, instruction continuity prediction based on the CAD basic file is performed to predict continuous instructions and complete the second optimization of the instruction toolbar. These technical effects together solve the technical problem that the existing CAD system has poor adaptability of the instruction toolbar during user use and is difficult to perform intelligent optimization according to the operation habits of different users, and achieve the technical effects of realizing personalized configuration and continuous optimization of the instruction toolbar through user behavior analysis, improving CAD operation efficiency and enhancing the user experience.

[0038] Embodiment 2, based on the same inventive concept as the CAD instruction optimization method combining user behavior analysis in the foregoing embodiment, as Figure 2 shown, the present application provides a CAD instruction optimization system combining user behavior analysis, and the system includes: a scene analysis module 11: identifying the CAD operation task being performed by the target user and performing scene analysis to generate a CAD task scene; a first optimization module 12: performing instruction personalized configuration based on operation frequency and operation path based on the CAD task scene to complete the first optimization of the instruction toolbar, and continuously monitoring the real-time operation characteristics of the target user; a second optimization module 13: performing instruction continuity prediction based on the CAD basic file based on the real-time operation characteristics to predict continuous instructions and complete the second optimization of the instruction toolbar.

[0039] Further, the scene analysis module 11 is further configured to execute the following method: When the target user starts the target CAD editing software, read the task creation mode of the target user, including the CAD file import mode or the new file mode; if the task creation mode is the CAD file import mode, read the imported file; perform drawing feature analysis on the imported file to generate the CAD task scene.

[0040] Further, the scene analysis module 11 is further configured to execute the following method: If the task creation mode is the new file mode, read the custom template; perform drawing feature statistics under the similar template based on the custom template to generate the CAD task scene.

[0041] Further, the first optimization module 12 is further configured to execute the following method: Collect the historical mapping operation records of the target user based on the CAD task scenario; predict the operation path for the CAD task scenario based on the historical mapping operation records to generate a predicted operation path; perform a descending analysis of the operation frequency of any instruction for each operation stage in the predicted operation path based on the historical mapping operation records to generate a first toolbar optimization plan for each operation stage; complete the first optimization of the instruction toolbar with the first toolbar optimization plan for each operation stage.

[0042] Further, the first optimization module 12 is also used to execute the following method: Extract the mapping operation records of each operation stage from the historical mapping operation records; perform a statistical count and descending processing of the usage frequency of any instruction based on the mapping operation records of each operation stage to generate the instruction arrangement priority for each operation stage; generate a first toolbar optimization plan for each operation stage with the instruction arrangement priority for each operation stage.

[0043] Further, the second optimization module 13 is also used to execute the following method: Monitor the continuity of the CAD file structure to generate the CAD basic file; based on the CAD basic file, predict the next operation instruction of the real-time operation feature to generate a next predicted instruction set; perform real-time update of the instruction toolbar with the next predicted instruction set to complete the second optimization of the instruction toolbar.

[0044] Further, the second optimization module 13 is also used to execute the following method: Match the mapping position and mapping action of the real-time operation feature in the CAD basic file to generate a matching result; based on the matching result, locate the adjacent mapping position and action in the CAD basic file to generate an adjacent matching result; construct the next predicted instruction set with the adjacent matching result.

[0045] Further, the second optimization module 13 is also used to execute the following method: Based on the historical mapping operation records of the target user, identify the backtracking-related instruction pairs with a backtracking frequency higher than the preset frequency, where the backtracking-related instruction pairs include the instruction executed before backtracking and the instruction executed after backtracking; collect the instruction explanations of each instruction in the backtracking-related instruction pairs, and when the target user clicks on any instruction in the backtracking-related instruction pairs, trigger an error verification reminder with the instruction explanation.

[0046] Further, the second optimization module 13 is also used to execute the following method: Based on the historical mapping operation records of the target user, identify the view switching requirements after the execution of any operation instruction; when the target user applies the corresponding operation instruction, perform a view switching reminder based on the view switching requirements.

[0047] It should be noted that the above-mentioned sequence of embodiments of the present application is only for description and does not represent the superiority or inferiority of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order and continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0048] The above are only the preferred embodiments of the present application and are not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included within the protection scope of the present application.

[0049] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications therein.

Claims

1. CAD instruction optimization method combined with user behavior analysis, characterized in that Including: Identifying the CAD operation task being performed by the target user and performing scenario analysis to generate a CAD task scenario; Performing instruction personalized configuration based on operation frequency and operation path based on the CAD task scenario, completing the first optimization of the instruction toolbar, and continuously monitoring the real-time operation characteristics of the target user; Performing instruction continuity prediction based on the CAD basic file based on the real-time operation characteristics to predict continuous instructions and complete the second optimization of the instruction toolbar.

2. The CAD instruction optimization method combined with user behavior analysis according to claim 1, characterized in that, Identifying the CAD operation task being performed by the target user and performing scenario analysis to generate a CAD task scenario, including: When the target user starts the target CAD editing software, reading the task creation mode of the target user, including the CAD file import mode or the new file mode; If the task creation mode is the CAD file import mode, reading the imported file; Performing drawing feature analysis on the imported file to generate the CAD task scenario.

3. The CAD instruction optimization method combining user behavior analysis according to claim 2, wherein, After reading the task creation mode of the target user, it further includes: If the task creation mode is the new file mode, reading the custom template; Performing drawing feature statistics under the similar template based on the custom template to generate the CAD task scenario.

4. The CAD instruction optimization method combining user behavior analysis according to claim 1, characterized in that, Performing instruction personalized configuration based on operation frequency and operation path based on the CAD task scenario, completing the first optimization of the instruction toolbar, including: Collecting the historical drawing operation records of the target user based on the CAD task scenario; Performing prediction of the operation path on the CAD task scenario based on the historical drawing operation records to generate a predicted operation path; Performing descending order analysis of the operation frequency of any instruction for each operation stage in the predicted operation path based on the historical drawing operation records to generate the first toolbar optimization plan for each operation stage; Completing the first optimization of the instruction toolbar with the first toolbar optimization plan for each operation stage.

5. The CAD instruction optimization method combining user behavior analysis according to claim 4, characterized in that, Performing descending order analysis of the operation frequency of any instruction for each operation stage in the predicted operation path based on the historical drawing operation records to generate the first toolbar optimization plan for each operation stage, including: Extracting the drawing operation records of each operation stage from the historical drawing operation records; Performing usage frequency statistics and descending order processing of any instruction based on the drawing operation records of each operation stage to generate the instruction arrangement priority for each operation stage; Generating the first toolbar optimization plan for each operation stage with the instruction arrangement priority for each operation stage.

6. The CAD instruction optimization method combined with user behavior analysis according to claim 1, characterized in that, Performing instruction continuity prediction based on the CAD basic file based on the real-time operation characteristics to predict continuous instructions and complete the second optimization of the instruction toolbar, including: Performing continuity monitoring of the CAD file structure to generate the CAD basic file; Based on the CAD basic file, performing prediction of the next operation instruction of the real-time operation characteristics to generate the next predicted instruction set; Performing real-time update of the instruction toolbar with the next predicted instruction set to complete the second optimization of the instruction toolbar.

7. The CAD instruction optimization method combining user behavior analysis according to claim 6, wherein, Based on the CAD basic file, perform the prediction of the next operation instruction of the real-time operation feature to generate the next prediction instruction set, including: Match the mapping position and mapping action of the real-time operation feature in the CAD basic file to generate a matching result; Based on the matching result, locate the adjacent mapping positions and actions in the CAD basic file to generate an adjacent matching result; Construct the next prediction instruction set with the adjacent matching result.

8. The CAD instruction optimization method combining user behavior analysis according to claim 1, characterized in that After completing the secondary optimization of the instruction toolbar, it further includes: Based on the historical mapping operation records of the target user, identify the rollback-related instruction pairs with a rollback frequency higher than the preset frequency, where the rollback-related instruction pairs include the instruction executed before rollback and the instruction executed after rollback; Collect the instruction explanations of each instruction in the rollback-related instruction pair, and when the target user clicks on any instruction in the rollback-related instruction pair, trigger an error verification reminder with the instruction explanation.

9. The CAD instruction optimization method combining user behavior analysis according to claim 1, characterized in that After completing the secondary optimization of the instruction toolbar, it includes: Based on the historical mapping operation records of the target user, identify the view switching requirements after the execution of any operation instruction; When the target user applies the corresponding operation instruction, perform a view switching reminder based on the view switching requirements.

10. CAD instruction optimization system combined with user behavior analysis, characterized in that, The system is used to execute the CAD instruction optimization method combining user behavior analysis according to any one of claims 1-9, including: Scenario analysis module: Identify the CAD operation task being performed by the target user and perform scenario analysis to generate a CAD task scenario; Primary optimization module: Based on the CAD task scenario, perform instruction personalization configuration based on operation frequency and operation path, complete the primary optimization of the instruction toolbar, and continuously monitor the real-time operation features of the target user; Secondary optimization module: Based on the real-time operation features, perform instruction continuity prediction based on the CAD basic file to complete the secondary optimization of the instruction toolbar with the predicted continuous instructions.

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