CN111861404B - Data processing method and device based on intelligent machine and electronic equipment - Google Patents
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Abstract
The invention discloses a data processing method and device based on an intelligent machine and electronic equipment. Wherein the method comprises the following steps: acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: behavior category labels and behavior group labels; generating a task scheme based on the behavior information, wherein the task scheme at least comprises: a task execution step and a plurality of data processing tasks; collecting a task completion state of a user executing a data processing task on a target object; evaluating the task completion state of each data processing task to obtain an evaluation record; and generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme. The invention solves the technical problems of high time cost and low updating efficiency of the prior art that a large amount of data needs to be acquired in the early stage when the data is updated.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a data processing method and device based on an intelligent machine and electronic equipment.
Background
In the related art, when data of a data processing task (e.g., model learning and factory machine learning) is updated, a user inputs a user name and a password through a login access module, logs in a data storage module for testing, then records a testing result, and correspondingly establishes a new testing database as generated aiming at a testing defect, so that the user can quickly find out required information, and data in the data storage module can be accessed by different user terminals to complete data updating. However, in the data updating mode, a large amount of data accumulation is needed in the early stage, the data can be more accurate, the data is imported through the existing data updating system, or the analysis capability tends to be more reasonable when the data is accumulated to a certain order of magnitude, the time cost is higher, a large amount of data storage cost is spent, the data updating speed is lower, and the working efficiency is reduced.
In view of the above problems, no effective solution has been proposed at present.
Disclosure of Invention
The embodiment of the invention provides a data processing method and device based on an intelligent machine and electronic equipment, which at least solve the technical problems that a large amount of data needs to be acquired in the early stage when data is updated in the related technology, so that the time cost is high and the updating efficiency is low.
According to an aspect of an embodiment of the present invention, there is provided a data processing method based on an intelligent machine, including: obtaining behavior information of a user on a target object, wherein the behavior information at least comprises: behavior category labels and behavior group labels; generating a task scheme based on the behavior information, wherein the task scheme at least comprises: a task execution step and a plurality of data processing tasks; collecting a task completion state of a user executing the data processing task on a target object; evaluating the task completion state of each data processing task to obtain an evaluation record; and generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
Optionally, before acquiring the behavior information of the user on the target object, the updating method further includes: establishing a network connection with the target object; collecting login information of a user through the network connection; and checking the login information of the user, and recording the login information of the user when the verification is passed.
Optionally, the step of generating a task solution based on the behavior information includes: analyzing the behavior information to determine a behavior category label and a behavior group label; determining a plurality of data processing tasks corresponding to the user based on the behavior category label and the behavior group label; collecting user information of the user; based on the user information, learning state data of the user when each data processing task is completed is obtained, wherein the learning state data corresponds to a data type; and combining the learning state data to generate the task scheme, wherein the task scheme corresponds to the user type to which the user group belongs.
Optionally, the step of collecting a task completion status of the user performing the data processing task on the target object includes: creating a task distribution task; pushing a data processing task to a template object held by a user based on the task distribution task; recording the task pushing completion state; and acquiring a task completion state of executing the data processing task on the target object through the network connection.
Optionally, the task completion status includes at least one of: task operation mode, task completion progress, task completion time, and various learning subtask completion states on a time axis.
Optionally, the step of generating a task optimization scheme based on the evaluation record includes: sorting the evaluation records based on the evaluation weights in the evaluation records to obtain sorting results; based on the sequencing result, extracting an optimal task scheme in each data processing task; and combining the optimal task schemes in all the data processing tasks to generate a task optimization scheme.
According to another aspect of the embodiment of the present invention, there is also provided a data processing apparatus based on an intelligent machine, including: the system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring behavior information of a user on a target object, and the behavior information at least comprises: behavior category labels and behavior group labels; the first generating unit is configured to generate a task scheme based on the behavior information, where the task scheme at least includes: a task execution step and a plurality of data processing tasks; the acquisition unit is used for acquiring a task completion state of a user for executing the data processing task on the target object; the evaluation unit is used for evaluating the task completion state of each data processing task to obtain an evaluation record; and the second generating unit is used for generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
Optionally, the updating device further includes: the system comprises a building unit, a storage unit and a control unit, wherein the building unit is used for building network connection with a target object before acquiring behavior information of a user on the target object; the first acquisition module is used for acquiring login information of a user through the network connection; and the recording unit is used for checking the login information of the user and recording the login information of the user when the verification is passed.
Optionally, the first generating unit includes: the first analysis module is used for analyzing the behavior information and determining a behavior category label and a behavior group label; a first determining module, configured to determine a plurality of data processing tasks corresponding to the user based on the behavior category label and the behavior group label; the second acquisition module is used for acquiring user information of the user; the first acquisition module is used for acquiring learning state data of a user when each data processing task is completed based on the user information, wherein the learning state data corresponds to a data type; the first generation module is used for combining the learning state data to generate the task scheme, wherein the task scheme corresponds to the user type to which the user group belongs.
Optionally, the acquisition unit includes: the first creating module is used for creating task distribution tasks; the first pushing module is used for pushing the data processing task to a template object held by a user based on the task distribution task; the first recording module is used for recording the task pushing completion state; and the third acquisition module is used for acquiring the task completion state of executing the data processing task on the target object through network connection.
Optionally, the task completion status includes at least one of: task operation mode, task completion progress, task completion time, and various learning subtask completion states on a time axis.
Optionally, the second generating unit includes: the sorting module is used for sorting the evaluation records based on the evaluation weights in the evaluation records to obtain sorting results; the extraction module is used for extracting an optimal task scheme in each data processing task based on the sequencing result; and the combination module is used for combining the optimal task schemes in all the data processing tasks to generate a task optimization scheme.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform the intelligent machine-based data processing method of any of the above via execution of the executable instructions.
According to another aspect of the embodiment of the present invention, there is also provided a computer readable storage medium, where the computer readable storage medium includes a stored computer program, where when the computer program runs, the device where the computer readable storage medium is controlled to execute the data processing method based on the intelligent machine according to any one of the foregoing.
In the embodiment of the invention, the behavior information of the user on the target object is obtained, wherein the behavior information at least comprises: the behavior category labels and the behavior group labels generate task schemes based on the behavior information, wherein the task schemes at least comprise: the task execution step and the plurality of data processing tasks, the task completion state of the data processing tasks executed by the user on the target object is collected, the task completion state of each data processing task is evaluated, an evaluation record is obtained, and a task optimization scheme is generated based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme. In this embodiment, the time cost of task processing can be reduced, the self-learning and continuous update growth characteristics are provided, and the task scheme is continuously optimized, so that the system can obtain the task scheme matched with the task scheme in different business stages, a large amount of data is not required to be acquired in the early stage, the learning time cost is reduced, the update efficiency is improved, the efficient operation assistance of an enterprise is improved, the production efficiency of the enterprise is integrally improved, and the technical problems that a large amount of data is required to be acquired in the early stage when the data is updated in the related art are solved, the time cost is high, and the update efficiency is low are solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
FIG. 1 is a flow chart of an alternative intelligent machine-based data processing method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of an alternative intelligent machine-based data processing apparatus according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art will better understand the present invention, a technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The embodiment of the invention can be applied to a data updating system and data updating software of a data processing task (for example, model data processing, intelligent processing of a factory machine, generating a task optimization scheme after multidimensional processing such as intelligent data analysis and individual capacity gear establishment through a system), for example, the data updating system and the data updating software are applied to data application software of an intelligent machine. Aiming at the problems that a large amount of data is required to be accumulated in the early stage to conduct data import in the prior art or analysis capability tends to be more reasonable when the data is accumulated to a certain order of magnitude, the embodiment of the invention utilizes the collected user behavior information to generate a task scheme and automatically update the task scheme, can reduce time cost and reduce the cost of machine learning growth, has self-learning and continuous updating growth, has high processing speed and high efficiency, solves the problem of reasonable growth mode, helps the efficient operation of enterprises, and integrally improves the production efficiency of the enterprises.
According to the embodiment of the invention, the learning subtask comprehensive evaluation and comparison can be performed through intelligent analysis of data according to a time axis, an operation mode, operation feedback and the like, the sorting is recorded according to a plurality of evaluation weights (for example, user weights, user group weights and user classification weights), then a task optimization scheme is generated according to a sorting result, a data combination mode and a user behavior analysis mode are updated through the task optimization scheme, then a task scheme and a data processing task are continuously optimized again, a new task scheme is initiated, and the data updating efficiency is improved through continuous iterative updating. The invention is described below in connection with various embodiments.
Example 1
According to an embodiment of the present invention, there is provided an embodiment of a data processing method based on a smart machine, it should be noted that the steps illustrated in the flowcharts of the drawings may be performed in a computer system such as a set of computer executable instructions, and that although a logical order is illustrated in the flowcharts, in some cases the steps illustrated or described may be performed in an order different from that herein.
FIG. 1 is a flow chart of an alternative intelligent machine-based data processing method according to an embodiment of the present invention, as shown in FIG. 1, comprising the steps of:
step S102, behavior information of a user on a target object is obtained, wherein the behavior information at least comprises: behavior category labels and behavior group labels;
step S104, generating a task scheme based on the behavior information, wherein the task scheme at least comprises: a task execution step and a plurality of data processing tasks;
step S106, collecting a task completion state of a user executing a data processing task on a target object;
step S108, evaluating the task completion state of each data processing task to obtain an evaluation record;
step S110, generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
Through the steps, the behavior information of the user on the target object can be obtained, wherein the behavior information at least comprises: the behavior category labels and the behavior group labels generate task schemes based on the behavior information, wherein the task schemes at least comprise: the task execution step and the plurality of data processing tasks, the task completion state of the data processing tasks executed by the user on the target object is collected, the task completion state of each data processing task is evaluated, an evaluation record is obtained, and a task optimization scheme is generated based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme. In this embodiment, the time cost of task processing can be reduced, the self-learning and continuous update growth characteristics are provided, and the task scheme is continuously optimized, so that the system can obtain the task scheme matched with the task scheme in different business stages, a large amount of data is not required to be acquired in the early stage, the learning time cost is reduced, the update efficiency is improved, the efficient operation assistance of an enterprise is improved, the production efficiency of the enterprise is integrally improved, and the technical problems that a large amount of data is required to be acquired in the early stage when the data is updated in the related art are solved, the time cost is high, and the update efficiency is low are solved.
The embodiment of the invention can be applied to a machine intelligent data processing system, a data application system/data application software, and takes the data processing system as an example, the data processing system can update data, and the data processing system comprises: user structure, intelligent learning structure and analysis optimization structure, wherein, user structure includes: a login module (recording login information, such as user account, password, gender, etc.), a behavior recording module (collecting the behavior of the user on the target object), an interest and hobby module (analyzing the interest category, hobbies and characteristics of the user), and an analysis and categorization module (categorizing and analyzing the behavior of the user on the target object); the intelligent learning structure comprises: basic data module (analyzing login information, behavior information, classifying data attribute, registering single operation and single data type of data), data combination module (combining various data), matching user type module (matching user general category), task push distribution module (data processing task and task scheme push); the analysis optimizing structure comprises the following steps: the system comprises a user task information feedback module, an intelligent analysis module, an evaluation module (for evaluating the weight of each task scheme) and an intelligent optimization module (for generating the task optimization scheme). The data application system establishes a network connection with a terminal held by a user in advance.
Embodiments of the present invention will be described in detail with reference to the following steps.
Optionally, before acquiring the behavior information of the user on the target object, the updating method further includes: establishing network connection with a target object; collecting login information of a user through network connection; and checking the login information of the user, and recording the login information of the user when the verification is passed.
The target object may indicate a terminal held by the user (e.g., cell phone, PC, tablet, IPAD, etc.), a logged-in APP, a logged-in application software, etc.
The login module of the user structure is connected with the system through a network to perform data butt joint, record login information, check the user information and record the login information.
Step S102, behavior information of a user on a target object is obtained, wherein the behavior information at least comprises: behavior category labels and behavior group labels.
User behavior is subjected to preference analysis, labeling and classifying of the user behavior are intelligently performed, and for example, learning directions (for example, machine operation flow, machine disassembly flow and the like) of the user on the APP are classified.
Step S104, generating a task scheme based on the behavior information, wherein the task scheme at least comprises: task execution steps and a plurality of data processing tasks.
In the embodiment of the invention, the step of generating the task scheme based on the behavior information comprises the following steps: analyzing the behavior information and determining a behavior category label and a behavior group label; determining a plurality of data processing tasks corresponding to the user based on the behavior class labels and the behavior group labels; collecting user information of a user; based on the user information, learning state data of the user when each data processing task is completed is obtained, wherein the learning state data corresponds to a data type; and combining the learning state data to generate a task scheme, wherein the task scheme corresponds to the user type to which the user group belongs.
Wherein the learning state data may include: dynamic change data or learning growth data in the learning process can determine an automatic learning and intelligent processing scheme of the intelligent machine through the learning state data.
Classifying the labeled user by analyzing the behavior category/behavior group, and classifying the user behaviors by a multidimensional one-to-many grouping mode, namely that one user behavior may exist and is grouped with a plurality of user behaviors; and simultaneously recording task growth information and task completion information of the user, and storing all information of the user.
In the embodiment of the invention, the task scheme can be intelligently generated through free combination of the basic data modules, and meanwhile, the task scheme is recorded and stored.
Step S106, collecting the task completion state of the user executing the data processing task on the target object.
Optionally, the step of collecting a task completion status of a user performing a data processing task on the target object includes: creating a task distribution task; pushing a data processing task to a template object held by a user based on a task distribution task; recording the task pushing completion state; and collecting the task completion state of executing the data processing task on the target object through network connection.
Selecting a task scheme of a user type to which the user group belongs to bind and record the task scheme into a task completion record of a recording user, simultaneously completing pushing of the task scheme (completed by a pushing and distributing module), creating a pushing and distributing task, and recording the completion condition of the pushing and distributing task; the method comprises the steps of sending information to a target object of a user through a network, sending information to an analysis optimization module for monitoring, sending a task of a task scheme to the target object, monitoring operation information of the user, and feeding back to the analysis optimization module for monitoring.
In an embodiment of the present invention, the task completion status includes at least one of: task operation mode, task completion progress, task completion time, and various learning subtask completion states on a time axis. When the task completion state is acquired, intelligently analyzing the task operation mode, completion progress, completion time of a user, and the completion condition of each subtask on a time axis, and recording and storing; and sending the obtained data of the task completion states to an intelligent evaluation module, comprehensively evaluating and recording the evaluation weights/grades in the user growth schemes according to the completion progress, the completion time and the completion condition of the subtasks, and then sorting the evaluation weights/grades, and recording a plurality of evaluation weight records/grade records such as the evaluation grades/weights, the sorting and the like in the user group growth schemes.
Step S108, evaluating the task completion state of each data processing task to obtain an evaluation record;
step S110, generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
Optionally, the step of generating the task optimization scheme based on the evaluation record includes: sorting the evaluation records based on the evaluation weights in the evaluation records to obtain sorting results; based on the sequencing result, extracting an optimal task scheme in each data processing task; and combining the optimal task schemes in all the data processing tasks to generate a task optimization scheme.
After collecting the information of a plurality of users from the tasks of a plurality of users, the intelligent optimization module extracts the optimal scheme in each subtask through evaluation records to be combined, generates a task optimization scheme, sends the task optimization scheme to the group combination module in the intelligent learning module to perform self-learning and updating, and simultaneously updates the user classification.
In the embodiment of the invention, through the access login operation of a user, the behavior information (comprising operation information and flow) of the user on a target object is collected, then a task scheme is generated (the atomic business of a business module of basic data is subjected to quantitative task combination to obtain each data processing task and is distributed to a part of target objects through a network), then the task completion state of the user can be collected, the task completion state of the user is fed back to an application system through the network, the dynamic evaluation and the total task record update are carried out on the user behavior, the user type, the completion state, the growth grade, the recommendation index and the like, then the task completion state of the user with various behavior types is carried out again by the mobile phone, the data processing task is continuously optimized, the intelligent learning is continuously optimized and adjusted and analyzed from different user behaviors, and the user obtains the growth task matched with the user in different business stages.
Example two
FIG. 2 is a schematic diagram of an alternative smart machine-based data processing device, as shown in FIG. 2, in accordance with an embodiment of the present invention, the update device may include: an acquisition unit 21, a first generation unit 23, an acquisition unit 25, an evaluation unit 27, a second generation unit 29, wherein,
an obtaining unit 21, configured to obtain behavior information of a user on a target object, where the behavior information includes at least: behavior category labels and behavior group labels;
a first generating unit 23, configured to generate a task scheme based on the behavior information, where the task scheme at least includes: a task execution step and a plurality of data processing tasks;
an acquisition unit 25 for acquiring a task completion status of a user performing a data processing task on a target object;
an evaluation unit 27 for evaluating the task completion status of each data processing task to obtain an evaluation record;
a second generating unit 29, configured to generate a task optimization scheme based on the evaluation record, where the task optimization scheme is used to update the task scheme.
The intelligent machine-based data processing apparatus may acquire behavior information of the user on the target object through the acquisition unit 21, where the behavior information includes at least: the behavior category label and the behavior group label generate a task solution based on the behavior information by the first generating unit 23, wherein the task solution at least includes: the task execution step and the plurality of data processing tasks, the task completion status of the data processing tasks executed by the user on the target object is collected by the collection unit 25, the task completion status of each data processing task is evaluated by the evaluation unit 27, an evaluation record is obtained, and a task optimization scheme is generated by the second generation unit 29 based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme. In the embodiment, the time cost of task learning can be reduced, the self-learning and continuous update growth are realized, the intelligent learning is continuously optimized and adjusted and is analyzed from different user behaviors through continuous optimization of the task scheme, so that the system can acquire the task scheme matched with the task scheme in different business stages, a large amount of data is not required to be acquired in the early stage, the learning time cost is reduced, the update efficiency is improved, the efficient operation assistance of enterprises is realized, and the production efficiency of the enterprises is integrally improved.
Optionally, the updating device further includes: the establishing unit is used for establishing network connection with the target object before acquiring the behavior information of the user on the target object; the first acquisition module is used for acquiring login information of a user through network connection; and the recording unit is used for checking the login information of the user and recording the login information of the user when the verification is passed.
In an embodiment of the present invention, the first generating unit includes: the first analysis module is used for analyzing the behavior information and determining a behavior category label and a behavior group label; the first determining module is used for determining a plurality of data processing tasks corresponding to the user based on the behavior category labels and the behavior group labels; the second acquisition module is used for acquiring user information of a user; the first acquisition module is used for acquiring learning state data of a user when each data processing task is completed based on the user information, wherein the learning state data corresponds to a data type; the first generation module is used for combining the learning state data to generate a task scheme, wherein the task scheme corresponds to the user type to which the user group belongs.
Optionally, the acquisition unit includes: the first creating module is used for creating task distribution tasks; the first pushing module is used for pushing the data processing task to a template object held by a user based on the task distribution task; the first recording module is used for recording the task pushing completion state; and the third acquisition module is used for acquiring the task completion state of executing the data processing task on the target object through network connection.
Alternatively, the task completion status includes at least one of: task operation mode, task completion progress, task completion time, and various learning subtask completion states on a time axis.
In an embodiment of the present invention, the second generating unit includes: the sorting module is used for sorting the evaluation records based on the evaluation weights in the evaluation records to obtain sorting results; the extraction module is used for extracting an optimal task scheme in each data processing task based on the sequencing result; and the combination module is used for combining the optimal task schemes in all the data processing tasks to generate a task optimization scheme.
The smart machine-based data processing apparatus may further include a processor and a memory, wherein the acquisition unit 21, the first generation unit 23, the acquisition unit 25, the evaluation unit 27, the second generation unit 29, and the like are stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches a corresponding program unit from the memory. The kernel may set one or more, and generate a task optimization scheme based on the evaluation record by adjusting the kernel parameters, where the task optimization scheme is used to update the task scheme.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), which includes at least one memory chip.
According to another aspect of the embodiment of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any of the above-described intelligent machine-based data processing methods via execution of the executable instructions.
According to another aspect of the embodiments of the present invention, there is also provided a computer readable storage medium, including a stored computer program, where the computer readable storage medium is controlled to execute any one of the above-mentioned intelligent machine-based data processing methods when the computer program is run.
The present application also provides a computer program product adapted to perform, when executed on a data processing device, a program initialized with the method steps of: acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: behavior category labels and behavior group labels; generating a task scheme based on the behavior information, wherein the task scheme at least comprises: a task execution step and a plurality of data processing tasks; collecting a task completion state of a user executing a data processing task on a target object; evaluating the task completion state of each data processing task to obtain an evaluation record; and generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
In the foregoing embodiments of the present invention, the descriptions of the embodiments are emphasized, and for a portion of this disclosure that is not described in detail in this embodiment, reference is made to the related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed technology content may be implemented in other manners. The above-described embodiments of the apparatus are merely exemplary, and the division of the units, for example, may be a logic function division, and may be implemented in another manner, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some interfaces, units or modules, or may be in electrical or other forms.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (8)
1. A data processing method based on an intelligent machine, comprising:
obtaining behavior information of a user on a target object, wherein the behavior information at least comprises: behavior category labels and behavior group labels;
generating a task scheme based on the behavior information, wherein the task scheme at least comprises: the task executing step and the plurality of data processing tasks, and the step of generating the task scheme comprises the following steps:
analyzing the behavior information to determine a behavior category label and a behavior group label; determining a plurality of data processing tasks corresponding to the user based on the behavior category label and the behavior group label; collecting user information of the user; based on the user information, learning state data of the user when each data processing task is completed is obtained, wherein the learning state data corresponds to a data type, and the learning state data comprises: dynamically changing data or learning growth data in the learning process; combining the learning state data to generate the task scheme, wherein the task scheme corresponds to the user type to which the user group belongs;
collecting a task completion state of a user executing the data processing task on a target object, wherein the task completion state comprises the following steps: task operation mode, task completion progress, task completion time and various learning subtask completion states on a time axis;
and evaluating the task completion state of each data processing task to obtain an evaluation record, wherein the evaluation record comprises: evaluating the weight;
and generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
2. The method of claim 1, wherein prior to obtaining the behavior information of the user on the target object, the data processing method further comprises:
establishing a network connection with the target object;
collecting login information of a user through the network connection;
and checking the login information of the user, and recording the login information of the user when the verification is passed.
3. The method of claim 1, wherein the step of collecting a task completion status of a user performing the data processing task on a target object comprises:
creating a task distribution task;
pushing a data processing task to a template object held by a user based on the task distribution task;
recording the task pushing completion state;
and acquiring a task completion state of executing the data processing task on the target object through network connection.
4. The method of claim 1, wherein the step of generating a task optimization scheme based on the evaluation record comprises:
sorting the evaluation records based on the evaluation weights in the evaluation records to obtain sorting results;
based on the sequencing result, extracting an optimal task scheme in each data processing task;
and combining the optimal task schemes in all the data processing tasks to generate a task optimization scheme.
5. A smart machine-based data processing apparatus, comprising:
the system comprises an acquisition unit, a storage unit and a processing unit, wherein the acquisition unit is used for acquiring behavior information of a user on a target object, and the behavior information at least comprises: behavior category labels and behavior group labels;
the first generating unit is configured to generate a task scheme based on the behavior information, where the task scheme at least includes: a task execution step and a plurality of data processing tasks,
the first generation unit includes: the first analysis module is used for analyzing the behavior information and determining a behavior category label and a behavior group label; a first determining module, configured to determine a plurality of data processing tasks corresponding to the user based on the behavior category label and the behavior group label; the second acquisition module is used for acquiring user information of the user; the first obtaining module is configured to obtain learning state data of a user when each data processing task is completed based on the user information, where the learning state data corresponds to a data type, and the learning state data includes: dynamically changing data or learning growth data in the learning process; the first generation module is used for combining the learning state data to generate the task scheme, wherein the task scheme corresponds to the user type to which the user group belongs;
the acquisition unit is used for acquiring a task completion state of a user executing the data processing task on the target object, and the task completion state comprises: task operation mode, task completion progress, task completion time and various learning subtask completion states on a time axis;
the evaluation unit is used for evaluating the task completion state of each data processing task to obtain an evaluation record, wherein the evaluation record comprises: evaluating the weight;
and the second generating unit is used for generating a task optimization scheme based on the evaluation record, wherein the task optimization scheme is used for updating the task scheme.
6. The data processing apparatus of claim 5, wherein the data processing apparatus further comprises:
the system comprises a building unit, a storage unit and a control unit, wherein the building unit is used for building network connection with a target object before obtaining behavior information of a user on the target object;
the first acquisition module is used for acquiring login information of a user through the network connection;
and the recording unit is used for checking the login information of the user and recording the login information of the user when the verification is passed.
7. An electronic device, comprising:
a processor; and
a memory for storing executable instructions of the processor;
wherein the processor is configured to perform the intelligent machine-based data processing method of any one of claims 1 to 4 via execution of the executable instructions.
8. A computer readable storage medium, characterized in that the computer readable storage medium comprises a stored computer program, wherein the computer program, when run, controls a device in which the computer readable storage medium is located to perform the intelligent machine based data processing method according to any one of claims 1 to 4.
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