Data set construction method and device and electronic equipment

Abstract

The invention provides a data set construction method and device and electronic device.The data set construction method comprises the steps that task decomposition is conducted on input information according to environment information corresponding to the input information, and task planning information corresponding to the input information is obtained; according to the task planning information and a search result corresponding to the input information, track data generation operation is carried out on the input information in a target application program of the electronic equipment, and track data corresponding to the input information is obtained; step-by-step evaluation is carried out on the trajectory data, and evaluation information corresponding to the trajectory data is obtained; and under the condition that the evaluation information corresponding to the trajectory data meets the information requirement, the trajectory data is added to the trajectory data set, so that the problems that the data volume is relatively low and the acquisition accuracy and the acquisition efficiency are relatively low due to the fact that the data set acquisition needs to be manually labeled are solved.

Description

Technical Field

[0001] This application relates to the field of computer technology, and particularly to a method, apparatus, and electronic device for constructing a data set. Background Art

[0002] With the development of science and technology, the development of large language models can open up a possible world for various natural language processing (NLP) tasks, increasing the interest and possibility of researching the future world. However, the training of large language models requires a large amount of data and manual annotation, resulting in a low volume of training data obtained, which cannot meet the model training requirements. Moreover, manual annotation makes it inconvenient to obtain data sets and has low efficiency. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] To this end, the first object of this application is to propose a method for constructing a data set to reduce the poor accuracy of the data set obtained through manual annotation, improve the acquisition efficiency of the data set, obtain trajectory data that meets the data requirements, evaluate the trajectory data at the same time, reduce the error probability of obtaining trajectory data, and improve the accuracy of obtaining trajectory data.

[0005] The second object of this application is to propose a device for constructing a data set.

[0006] The third object of this application is to propose an electronic device.

[0007] The fourth object of this application is to propose a computer-readable storage medium.

[0008] The fifth object of this application is to propose a computer program product.

[0009] To achieve the above object, the first aspect embodiment of this application proposes a method for constructing a data set, which is applied to an electronic device installed with an Android system, and includes the following steps:

[0010] Decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information;

[0011] Perform a trajectory data generation operation on the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information;

[0012] Perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data;

[0013] When the evaluation information corresponding to the trajectory data meets the first information requirement, add the trajectory data to the trajectory data set.

[0014] To achieve the above object, an embodiment of the second aspect of the present application provides a device for constructing a data set, including:

[0015] An information acquisition unit, configured to perform task decomposition on the input information according to the environmental information corresponding to the input information, and obtain the task planning information corresponding to the input information;

[0016] A trajectory data acquisition unit, configured to perform a trajectory data generation operation on the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information;

[0017] The information acquisition unit is further configured to perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data;

[0018] A set acquisition unit, configured to add the trajectory data to the trajectory data set when the evaluation information corresponding to the trajectory data meets the first information requirement.

[0019] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0020] The memory stores computer execution instructions;

[0021] The processor executes the computer execution instructions stored in the memory to implement the method according to any one of the first aspects described above.

[0022] To achieve the above object, an embodiment of the fourth aspect of the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement the method according to any one of the first aspects described above.

[0023] To achieve the above object, an embodiment of the fifth aspect of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the method according to any one of the first aspects described above.

[0024] The method, device, and electronic device for constructing a data set provided by this application decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information; generate trajectory data for the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information; perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data; and add the trajectory data to the trajectory data set when the evaluation information corresponding to the trajectory data meets the first information requirement. This solves the problem that the acquisition of the data set requires manual annotation, resulting in a low data volume and low acquisition accuracy and efficiency. Since the trajectory data can be obtained based on the input information and the search result without manual annotation, the situation where the data volume is small due to the limitation of manual annotation can be reduced, the labor cost can be reduced, the situation where the accuracy of the data set obtained by manual annotation is poor can be reduced, the acquisition efficiency of the data set can be improved. At the same time, the trajectory data can be evaluated, the error probability of obtaining the trajectory data can be reduced, and the accuracy of obtaining the trajectory data can be improved.

[0025] Additional aspects and advantages of this application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The above and / or additional aspects and advantages of this application will become apparent and be readily understood from the following description of the embodiments in conjunction with the drawings, where:

[0027] Figure 1 is a schematic flowchart of a method for constructing a data set provided by an embodiment of this application;

[0028] Figure 2 is a schematic flowchart of a method for constructing a data set provided by an embodiment of this application;

[0029] Figure 3a is an example schematic diagram of a method for constructing a data set provided by an embodiment of this application;

[0030] Figure 3b is an example schematic diagram of a method for constructing a data set provided by an embodiment of this application;

[0031] Figure 3c is an example schematic diagram of a method for constructing a data set provided by an embodiment of this application;

[0032] And Figure 4 is a schematic structural diagram of a device for constructing a data set provided by an embodiment of this application. Detailed implementation manners

[0033] The embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as a limitation to the present application.

[0034] The method and apparatus for constructing a data set according to an embodiment of the present application will be described below with reference to the accompanying drawings.

[0035] Figure 1 It is a schematic flowchart of a method for constructing a data set provided for an embodiment of the present application.

[0036] To address this issue, the embodiments of the present application provide a method for constructing a data set to reduce the poor accuracy of the data set obtained through manual annotation, improve the acquisition efficiency of the data set, obtain trajectory data that meets the data requirements, and at the same time evaluate the trajectory data, reduce the error probability of obtaining trajectory data, and improve the accuracy of obtaining trajectory data. As Figure 1 shown, the method for constructing the data set includes the following steps:

[0037] Step 101: Decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information;

[0038] According to some embodiments, the execution subject of the embodiments of the present application may be, for example, an electronic device. This electronic device does not specifically refer to a certain fixed device, and the name of this electronic device is not limited. This electronic device may also be referred to as a terminal, a mobile device, etc., and this electronic device may also be a robot. For example, when the device identifier of this electronic device changes, this electronic device may also change accordingly. Among them, this electronic device may be, for example, an electronic device installed with an Android system. The type of the Android system in the embodiments of the present application is not limited.

[0039] In some embodiments, the input information may be, for example, the information received during the generation of the data set. The input information may be, for example, text information, language information, or input information received according to the selection control on the electronic device. The embodiments of the present application do not limit this. The input information does not specifically refer to a certain fixed information. For example, when the acquisition method of the input information changes, the input information may also change accordingly. For example, when the acquisition time point corresponding to the input information changes, the input information may also change accordingly. Among them, the acquisition method of the input information is not limited. For example, the input information may be input by clicking through the input method on the electronic device, or may be voice information input through the voice input control.

[0040] In some embodiments, the environment information may be used to indicate, for example, the environment in which the current input information is applied. Among them, the environment information may include, for example, the current application scenario information, the environment where the electronic device is located, and the application scenario of the data set, etc. The environment information does not specifically refer to a certain fixed information. For example, when the input information changes, the environment information may also change accordingly.

[0041] In some embodiments, the task planning information may be, for example, the planning information carried out when obtaining trajectory data according to the input information, that is, the information on how to obtain the trajectory data. The task planning information does not specifically refer to a certain fixed information. For example, when the input information changes, the task planning information may also change accordingly. For example, when the acquisition method of the task planning information changes, the task planning information may also change accordingly.

[0042] In some embodiments, for example, the input information may be task-decomposed according to the environment information corresponding to the input information to obtain the task planning information corresponding to the input information.

[0043] Step 102, perform a trajectory data generation operation on the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information;

[0044] In some embodiments, the search result corresponding to the input information may be, for example, the result obtained by retrieving the input information. The search result does not specifically refer to a certain fixed search. For example, when the search method changes, the search result corresponding to the input information may also change accordingly. For example, when the number of searches changes, the search result corresponding to the input information may also change accordingly. For example, when the database for the search changes, the search result corresponding to the input information may also change accordingly.

[0045] In some embodiments, the target application can be, for example, an application that can perform trajectory data generation operations. The target application is not specifically a certain fixed application. For example, when the input information changes, the target application can also change accordingly. For example, when the program identifier of the target application changes, the target application can also change accordingly.

[0046] In some embodiments, the trajectory data corresponding to the input information can also be referred to as generated data corresponding to the input information, etc. The embodiments of the present application do not limit this. The trajectory data corresponding to the input information is not specifically a certain fixed trajectory data. For example, when the generation operation corresponding to the trajectory data changes, the trajectory data corresponding to the input information can also change accordingly.

[0047] In some embodiments, for example, according to the task planning information and the search result corresponding to the input information, a trajectory data generation operation can be performed on the input information in the target application of the electronic device to obtain the trajectory data corresponding to the input information.

[0048] Step 103: Perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data;

[0049] According to some embodiments, step-by-step evaluation can, for example, perform gradual evaluation on the generated trajectory data. Among them, each step corresponding to the step-by-step evaluation can be the same as or different from the task planning information. That is, it is possible to evaluate each subtask in the task planning information to obtain the evaluation information, or it is also possible to re-perform step-by-step on the trajectory data and evaluate each step to obtain the evaluation information. The embodiments of the present application do not limit this.

[0050] In some embodiments, perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data.

[0051] Step 104: When the evaluation information corresponding to the trajectory data meets the first information requirement, add the trajectory data to the trajectory data set.

[0052] In some embodiments, the information requirement can be used to detect whether the generated trajectory data meets the trajectory data requirement and can be used for subsequent use. The "first" in the first information requirement is used to distinguish it from the remaining information requirements and does not specifically refer to a certain fixed requirement. For example, when the evaluation information changes, the first information requirement can also change accordingly.

[0053] According to some embodiments, a set of trajectory data can be, for example, a collective formed by at least one piece of trajectory data. This set of trajectory data is not specifically a fixed set. For example, when the amount of trajectory data corresponding to the set of trajectory data changes, the set of trajectory data can also change accordingly. For example, when a piece of trajectory data included in the set of trajectory data changes, the set of trajectory data can also change accordingly.

[0054] Among some embodiments, the trajectory data can be added to the set of trajectory data when the evaluation information corresponding to the trajectory data meets the first information requirement.

[0055] The method, device, and electronic device for constructing a data set provided in this application decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information; generate trajectory data for the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information, to obtain the trajectory data corresponding to the input information; perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data; and add the trajectory data to the set of trajectory data when the evaluation information corresponding to the trajectory data meets the first information requirement, which solves the problem that the acquisition of the data set requires manual annotation, resulting in a low data volume and low acquisition accuracy and efficiency. Since the trajectory data can be obtained according to the input information and the search result without manual annotation, the labor cost can be reduced, and the situation where the accuracy of the data set obtained by manual annotation is poor can be reduced. The acquisition efficiency of the data set can be improved. At the same time, the trajectory data can be evaluated, which can reduce the error probability of trajectory data acquisition and improve the accuracy of trajectory data acquisition.

[0056] This embodiment provides another method for constructing a data set. Figure 2 It is a schematic flowchart of a method for constructing a data set provided by an embodiment of this application.

[0057] As Figure 2 shown, the method for constructing this data set can include the following steps:

[0058] Step 201, decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information;

[0059] The related process is as described above and will not be elaborated here.

[0060] Among some embodiments, the manner of task decomposition for the input information is not limited. For example, task decomposition can be performed according to the search results. Among them, the search results can be the ones with the highest similarity to the input information in the database, and this can be done after combined analysis of multiple search results.

[0061] Among some embodiments, environmental information can, for example, serve as the basis for interaction. The environmental information can, for example, include an observation space and an action space. Among them, the observation space can, for example, be Android XML, which can be simplified and attribute details added to determine the element type. Among them, for example, the action space can be defined using Python function calls, and specifically, it can be represented using Python docstrings.

[0062] Step 202, according to the task planning information and the search results corresponding to the input information, perform an operation of generating trajectory data for the input information in the target application of the electronic device, and obtain the trajectory data corresponding to the input information;

[0063] The related process is as described above and will not be elaborated here.

[0064] According to some embodiments, the performing an operation of generating trajectory data for the input information in the target application of the electronic device according to the task planning information and the search results corresponding to the input information, and obtaining the trajectory data corresponding to the input information includes:

[0065] Obtain the target application corresponding to the input information, and obtain the set of historical trajectory data corresponding to the target application in the database;

[0066] Obtain the embedding vector corresponding to the input information;

[0067] According to the embedding vector, obtain the search result with the highest similarity to the embedding vector in the set of historical trajectory data;

[0068] According to the task planning information and the search results corresponding to the input information, display a trajectory generation interface corresponding to the input information in the display device corresponding to the target application of the electronic device;

[0069] Perform an operation of generating trajectory data for the input information, and obtain the trajectory data corresponding to the input information. Therefore, extended search can be performed, leveraging the context learning ability of the large language model for iterative optimization to improve the accuracy of trajectory data acquisition.

[0070] Among them, for example, historical trajectories can be collected, and the embedding vectors corresponding to each historical trajectory can be added to the database. The database can, for example, include historical trajectories corresponding to different application programs. Among them, the historical trajectories corresponding to different application programs can, for example, include trajectories corresponding to different instructions.

[0071] According to some embodiments, when performing an extended search, for example, retrieval can be performed in a set of the same context. For example, historical trajectory data sets corresponding to a target application program can be first obtained from the database. For example, it can be at least one historical trajectory data related to the target application program. That is, the historical trajectory data set can be a database corresponding to the target application program.

[0072] According to some embodiments, the method further includes:

[0073] During the process of performing a trajectory data generation operation on the input information, obtain task progress information corresponding to the task planning information;

[0074] Adjust the task planning information according to the task progress information, and according to the adjusted task planning information, perform a trajectory data generation operation on the input information in the target application program of the electronic device to obtain trajectory data corresponding to the input information. Therefore, the task planning information can be adjusted, and the accuracy and efficiency of obtaining trajectory data can be improved.

[0075] In some embodiments, for example, it can be determined whether each subtask in the task planning information reaches a preset target. The determination process can, for example, include whether an element identifier exists, whether the type is consistent with the preset setting, and whether the subtask is completed. Whether the subtask is completed can, for example, include whether the subtask has a response and whether the response duration is within a preset duration, etc.

[0076] In some embodiments, the task progress information can, for example, be used to indicate the progress during the process of obtaining trajectory data. Among them, the task progress information can, for example, be determined by a feedback operation received on a display device.

[0077] According to some embodiments, during the process of performing a trajectory data generation operation on the input information, obtaining the task progress information corresponding to the task planning information includes:

[0078] During the process of performing a trajectory data generation operation on the input information, obtain response information corresponding to each task planning information in the task planning information;

[0079] According to the response information, obtain the task progress information corresponding to the task planning information.

[0080] According to some embodiments, obtaining the trajectory data corresponding to the input information includes:

[0081] Obtaining a set of sub-trajectory data corresponding to the trajectory data;

[0082] Obtaining the label information corresponding to each sub-trajectory data in the set of sub-trajectory data corresponding to the trajectory data;

[0083] Connecting the set of sub-trajectory data and the label information corresponding to each sub-trajectory data in the order of trajectory data generation to obtain the trajectory data corresponding to the input information.

[0084] In some embodiments, for example, GPT-4o can be used to sample the trajectory of each task, that is, sample the process of generating the trajectory data corresponding to each input information, and the collected information can be recorded. Specifically, for example, it can include the environmental information and operation information corresponding to each sub-task.

[0085] Step 203, decomposing the trajectory data to obtain a set of sub-trajectory data;

[0086] In some embodiments, the set of sub-trajectory data can be, for example, a collective formed by at least one sub-trajectory data. This set of sub-trajectory data does not specifically refer to a certain fixed set. For example, when the decomposition method of the trajectory data changes, this set of sub-trajectory data can also change accordingly. For example, when the amount of data included in the set of sub-trajectory data changes, this set of sub-trajectory data can also change accordingly.

[0087] In some embodiments, there is no limitation on the decomposition method of the trajectory data. For example, it can be consistent with the task planning information or not. This application embodiment does not make a limitation on this. For example, the trajectory data can be decomposed according to the correlation relationship between each operation.

[0088] In some embodiments, for example, the trajectory data can be decomposed to obtain a set of sub-trajectory data.

[0089] Step 204, using the evaluation methods corresponding to each sub-trajectory data in the set of sub-trajectory data to evaluate each sub-trajectory data, and obtaining the evaluation information corresponding to each trajectory data;

[0090] In some embodiments, different sub-trajectory data can correspond to different evaluation methods. For example, the evaluation method can be determined according to the trajectory information and operation information corresponding to each sub-trajectory. This evaluation method includes but is not limited to whether the sub-trajectory is obtained, whether the identification information of the sub-trajectory meets the identification requirements, whether the acquisition duration corresponding to the sub-trajectory is less than the preset duration, etc.

[0091] According to some embodiments, the evaluation information may be, for example, score information, or may also be the marking data corresponding to each sub-trajectory data. The marking data may be, for example, 0 or 1.

[0092] Among some embodiments, for example, an evaluation method corresponding to each sub-trajectory data in the sub-trajectory data set is adopted to evaluate each sub-trajectory data, and the evaluation information corresponding to each trajectory data is obtained.

[0093] Step 205: Obtain the evaluation information corresponding to the trajectory data according to the evaluation information corresponding to each sub-trajectory data and the trajectory data information corresponding to each sub-trajectory data;

[0094] Among some embodiments, the evaluation information corresponding to the trajectory data may be obtained according to the evaluation information corresponding to each sub-trajectory data and the trajectory data information corresponding to each sub-trajectory data. Among them, the evaluation information corresponding to the trajectory data may be determined according to the weight corresponding to each sub-trajectory data or directly according to the evaluation information corresponding to the sub-trajectory data.

[0095] Step 206: Display the evaluation information corresponding to each trajectory data and the evaluation information corresponding to the trajectory data on a display device;

[0096] Among some embodiments, the evaluation information corresponding to each trajectory data and the evaluation information corresponding to the trajectory data may be displayed on a display device.

[0097] According to some embodiments, in the case where the evaluation data corresponding to the trajectory data does not meet the first information requirement, a prompt information may be sent, the task planning information corresponding to the input information may be adjusted according to the prompt information, and the trajectory data may be regenerated.

[0098] Step 207: Add the trajectory data to the trajectory data set in the case where the evaluation information corresponding to the trajectory data meets the first information requirement.

[0099] In some embodiments, after completing the trajectory generation task corresponding to each input information, steps can be used to evaluate the recorded trajectory. The steps list each sub-goal of the task and the corresponding steps taken to achieve them (where -1 indicates not completed). If each sub-goal has been completed, the task is considered completed and the trajectory is enhanced. For example, for task T and its corresponding sequence S, T contains multiple sub-goals g1, g2,..., gn, each associated with completion steps p1, p2,..., pn (where, if goal gi is not completed, then pi = -1). Let gk be the first uncompleted sub-goal (gn if all sub-goals are completed). We concatenate the sub-goals g1+···+gi from 1 to k-1 and use the subsequence {p1,..., pk-1} as a label to formulate a new trajectory to enhance the trajectory data set.

[0100] In some embodiments, the construction scheme of the data set can be applied to, for example, tape recorders, telephone contact construction, deleting files, marking maps, creating music playlists, turning off Bluetooth, etc. Among them, Figures 3a to 3c For example, for the construction of the trajectory data set for turning off Bluetooth, the trajectory data generation steps can include:

[0101] Step 1: Open the "Settings" application;

[0102] Step 2: Click on "Connected devices";

[0103] Step 3: Click on "Connection preferences";

[0104] Subark Step 4: Click on "Bluetooth";

[0105] Step 5: Click on the "Bluetooth switch".

[0106] According to some embodiments, the method further includes:

[0107] Training the initial large language model with the data set, and determining that the target large language model is obtained when the training information corresponding to the initial large language model meets the second information requirement.

[0108] In one or related embodiments, the trajectory data is decomposed to obtain a set of sub-trajectory data; an evaluation method corresponding to each sub-trajectory data in the set of sub-trajectory data is used to evaluate each sub-trajectory data to obtain evaluation information corresponding to each trajectory data; according to the evaluation information corresponding to each sub-trajectory data and the trajectory data information corresponding to each sub-trajectory data, the evaluation information corresponding to the trajectory data is obtained; the evaluation information corresponding to each trajectory data and the evaluation information corresponding to the trajectory data are displayed on a display device; when the evaluation information corresponding to the trajectory data meets the first information requirement, the trajectory data is added to the trajectory data set, so that the obtained trajectory data can be self-checked, the wrong operations in the process of obtaining trajectory data can be reduced, and the accuracy of obtaining trajectory data can be improved.

[0109] To implement the above embodiments, the present application also proposes a device for constructing a data set.

[0110] Figure 4 FIG. is a schematic structural diagram of a device for constructing a data set provided by an embodiment of the present application.

[0111] As Figure 4 shown, the device for constructing a data set includes:

[0112] An information acquisition unit 401, configured to decompose the input information according to the environmental information corresponding to the input information to obtain task planning information corresponding to the input information;

[0113] A trajectory data acquisition unit 402, configured to perform a trajectory data generation operation on the input information in a target application program of the electronic device according to the task planning information and the search result corresponding to the input information, to obtain trajectory data corresponding to the input information;

[0114] The information acquisition unit 401 is further configured to perform step-by-step evaluation on the trajectory data to obtain evaluation information corresponding to the trajectory data;

[0115] A set acquisition unit 403, configured to add the trajectory data to a trajectory data set when the evaluation information corresponding to the trajectory data meets the first information requirement.

[0116] According to some embodiments, when the information acquisition unit 401 is configured to perform step-by-step evaluation on the trajectory data to obtain evaluation information corresponding to the trajectory data, it is specifically configured to:

[0117] Decompose the trajectory data to obtain a set of sub-trajectory data;

[0118] Adopt an evaluation method corresponding to each sub-trajectory data in the sub-trajectory data set to evaluate each sub-trajectory data, and obtain the evaluation information corresponding to each trajectory data;

[0119] According to the evaluation information corresponding to each sub-trajectory data and the trajectory data information corresponding to each sub-trajectory data, obtain the evaluation information corresponding to the trajectory data;

[0120] Display the evaluation information corresponding to each trajectory data and the evaluation information corresponding to the trajectory data on a display device.

[0121] According to some embodiments, the trajectory data acquisition unit 402 is configured to perform a trajectory data generation operation on the input information in a target application program of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information, including:

[0122] Obtain a target application program corresponding to the input information, and obtain a historical trajectory data set corresponding to the target application program in a database;

[0123] Obtain an embedding vector corresponding to the input information;

[0124] According to the embedding vector, obtain a search result with the highest similarity to the embedding vector in the historical trajectory data set;

[0125] According to the task planning information and the search result corresponding to the input information, display a trajectory generation interface corresponding to the input information on a display device corresponding to the target application program of the electronic device;

[0126] Perform a trajectory data generation operation on the input information to obtain the trajectory data corresponding to the input information.

[0127] According to some embodiments, the trajectory data acquisition unit 402 is further specifically configured to:

[0128] During the process of performing a trajectory data generation operation on the input information, obtain task progress information corresponding to the task planning information;

[0129] Adjust the task planning information according to the task progress information, and perform a trajectory data generation operation on the input information in the target application program of the electronic device according to the adjusted task planning information, and obtain the trajectory data corresponding to the input information.

[0130] According to some embodiments, when the trajectory data acquisition unit 402 is configured to obtain the task progress information corresponding to the task planning information during the process of performing a trajectory data generation operation on the input information, it is specifically configured to:

[0131] During the process of generating trajectory data for the input information, obtain the response information corresponding to each task planning information in the task planning information;

[0132] According to the response information, obtain the task progress information corresponding to the task planning information.

[0133] According to some embodiments, when the trajectory data acquisition unit 402 is used to acquire the trajectory data corresponding to the input information, it is specifically used for:

[0134] Obtain the set of sub-trajectory data corresponding to the trajectory data;

[0135] Obtain the label information corresponding to each sub-trajectory data in the set of sub-trajectory data corresponding to the trajectory data;

[0136] Connect the set of sub-trajectory data and the label information corresponding to each sub-trajectory data in the order of trajectory data generation to obtain the trajectory data corresponding to the input information.

[0137] According to some embodiments, the set acquisition unit 403 is further specifically used for:

[0138] Train the initial large language model using the data set, and determine that the target large language model is obtained when the training information corresponding to the initial large language model meets the second information requirement.

[0139] It should be noted that the foregoing explanation of the embodiments of the method for constructing the data set also applies to the data set construction device of this embodiment, and will not be repeated here.

[0140] The construction device for the data set provided by this application includes an information acquisition unit, which is used to decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information; a trajectory data acquisition unit, which is used to perform a trajectory data generation operation on the input information in the target application program of the electronic device according to the task planning information and the search result corresponding to the input information to obtain the trajectory data corresponding to the input information; the information acquisition unit is further used to perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data; a set acquisition unit, which is used to add the trajectory data to the trajectory data set when the evaluation information corresponding to the trajectory data meets the first information requirement. This solves the problem that the acquisition of the data set requires manual annotation, resulting in a low data volume, low acquisition accuracy, and low acquisition efficiency. Since the trajectory data can be acquired according to the input information and the search result without manual annotation, the labor cost can be reduced, and the situation where the accuracy of the data set acquired by manual annotation is poor can be reduced. The acquisition efficiency of the data set can be improved. At the same time, the trajectory data can be evaluated, the error probability of trajectory data acquisition can be reduced, and the accuracy of trajectory data acquisition can be improved.

[0141] To implement the above embodiments, this application also proposes an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer execution instructions; the processor executes the computer execution instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0142] To implement the above embodiments, this application also proposes a computer-readable storage medium, in which computer execution instructions are stored, and when the computer execution instructions are executed by a processor, they are used to implement the method provided in the foregoing embodiments.

[0143] To implement the above embodiments, this application also proposes a computer program product, including a computer program, which when executed by a processor, implements the method provided in the foregoing embodiments.

[0144] The collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information involved in this application all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0145] It should be noted that personal information from users should be collected for legal and reasonable purposes and not shared or sold outside of such legal uses. In addition, such collection / sharing should be carried out after obtaining the informed consent of the user, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization including authorizing relevant user information before the user uses the function. In addition, any necessary steps should be taken to safeguard and protect access to such personal information data and ensure that others with access to the personal information data comply with their privacy policies and procedures.

[0146] This application is expected to provide an implementation scheme for users to selectively block the use or access of personal information data. That is, this application is expected to provide hardware and / or software to prevent or block access to such personal information data. Once the personal information data is no longer needed, the risk can be minimized by restricting data collection and deleting the data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of users.

[0147] In the description of the foregoing embodiments, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0148] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this application, the meaning of "a plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0149] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment, or part of code including one or more executable instructions for implementing a customized logic function or process, and the scope of the preferred implementation of this application includes additional implementations, where the functions may be executed in a manner that is not in the order shown or discussed, including in a substantially simultaneous manner or in the reverse order according to the functions involved, which should be understood by those skilled in the art to which the embodiments of this application belong.

[0150] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definitional sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in conjunction with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0151] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0152] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0153] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0154] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for constructing a data set, characterized in that, Applied to an electronic device installed with an Android system, including: Decompose the input information according to the environmental information corresponding to the input information to obtain the task planning information corresponding to the input information; Perform a trajectory data generation operation on the input information in the target application of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information; Perform a step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data; When the evaluation information corresponding to the trajectory data meets the first information requirement, add the trajectory data to the trajectory data set.

2. The method according to claim 1, wherein The performing a step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data includes: Decompose the trajectory data to obtain a set of sub-trajectory data; Adopt the evaluation methods corresponding to the respective sub-trajectory data in the set of sub-trajectory data to evaluate the respective sub-trajectory data, and obtain the evaluation information corresponding to the respective trajectory data; According to the evaluation information corresponding to the respective sub-trajectory data and the trajectory data information corresponding to the respective sub-trajectory data, obtain the evaluation information corresponding to the trajectory data; Display the evaluation information corresponding to the respective trajectory data and the evaluation information corresponding to the trajectory data on a display device.

3. The method according to claim 1, wherein The performing a trajectory data generation operation on the input information in the target application of the electronic device according to the task planning information and the search result corresponding to the input information, and obtaining the trajectory data corresponding to the input information includes: Obtain the target application corresponding to the input information, and obtain a set of historical trajectory data corresponding to the target application in a database; Obtain the embedding vector corresponding to the input information; According to the embedding vector, obtain the search result with the highest similarity to the embedding vector in the set of historical trajectory data; According to the task planning information and the search result corresponding to the input information, display a trajectory generation interface corresponding to the input information on the display device corresponding to the target application of the electronic device; Perform a trajectory data generation operation on the input information to obtain the trajectory data corresponding to the input information.

4. The method according to claim 1, characterized in that The method further includes: During the process of performing a trajectory data generation operation on the input information, obtain the task progress information corresponding to the task planning information; Adjust the task planning information according to the task progress information, and according to the adjusted task planning information, perform a trajectory data generation operation on the input information in the target application of the electronic device, and obtain the trajectory data corresponding to the input information.

5. The method according to claim 4, characterized in that The obtaining the task progress information corresponding to the task planning information during the process of performing a trajectory data generation operation on the input information includes: During the process of performing a trajectory data generation operation on the input information, obtain the response information corresponding to each task planning information in the task planning information; According to the response information, obtain the task progress information corresponding to the task planning information.

6. The method according to claim 1, wherein The obtaining the trajectory data corresponding to the input information includes: Obtain a set of sub-trajectory data corresponding to the trajectory data; Obtain the label information corresponding to each sub-trajectory data in the set of sub-trajectory data corresponding to the trajectory data; Connect the set of sub-trajectory data and the label information corresponding to each sub-trajectory data in the order of trajectory data generation to obtain the trajectory data corresponding to the input information.

7. The method according to claim 1, wherein The method further includes: Train an initial large language model using the data set, and determine that a target large language model is obtained when the training information corresponding to the initial large language model meets the second information requirement.

8. An apparatus for constructing a data set, characterized in that, It includes: An information acquisition unit, configured to decompose the input information according to the environmental information corresponding to the input information, and obtain the task planning information corresponding to the input information; A trajectory data acquisition unit, configured to perform a trajectory data generation operation on the input information in a target application program of the electronic device according to the task planning information and the search result corresponding to the input information, and obtain the trajectory data corresponding to the input information; The information acquisition unit is further configured to perform step-by-step evaluation on the trajectory data to obtain the evaluation information corresponding to the trajectory data; A set acquisition unit, configured to add the trajectory data to the trajectory data set when the evaluation information corresponding to the trajectory data meets the first information requirement.

9. An electronic device, comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-7.

10. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-7.

Images