CN111861404A - 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: a behavior category label and a behavior group label; generating a task scheme based on the behavior information, wherein the task scheme at least comprises the following steps: a task execution step and a plurality of data processing tasks; acquiring 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 that a large amount of data needs to be collected at the early stage when data updating is carried out in the related technology, the time cost is high, and the updating efficiency is low.
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 update of data processing tasks (such as model learning and factory machine learning) is performed, a user inputs a user name and a password through a login access module, logs in a data storage module for testing, records a test result, and correspondingly establishes a new test database generated aiming at a test defect, so that the user can quickly find required information, data in the data storage module can be accessed by different user terminals, and data update is completed. However, in the data updating method, a large amount of data accumulation is often required 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 slower, and the working efficiency is reduced.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides a data processing method and device based on an intelligent machine and electronic equipment, and aims to at least solve the technical problems that in the related art, when data updating is carried out, a large amount of data needs to be collected in the early stage, the time cost is high, and the updating efficiency is low.
According to an aspect of the embodiments of the present invention, there is provided a data processing method based on an intelligent machine, including: acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: a behavior category label and a behavior group label; 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; acquiring 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 check is passed.
Optionally, the step of generating a task plan based on the behavior information includes: 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 category tags and the behavior group tags; collecting user information of the user; based on the user information, acquiring learning state data of a user when each data processing task is completed, 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 executing the data processing task on the target object includes: creating a task distribution task; based on the task distribution task, pushing a data processing task to a template object held by a user; recording a 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 each learning subtask completion state on a time axis.
Optionally, the step of generating a task optimization plan based on the evaluation record includes: ranking the evaluation records based on the evaluation weights in the evaluation records to obtain a ranking result; 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 embodiments of the present invention, there is also provided an intelligent machine-based data processing apparatus, including: an obtaining unit, configured to obtain behavior information of a user on a target object, where the behavior information at least includes: a behavior category label and a behavior group label; a first generating unit, configured to generate a task plan based on the behavior information, where the task plan at least includes: a task execution step and a plurality of data processing tasks; the acquisition unit is used for acquiring the task completion state of the data processing task executed on the target object by the user; 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 apparatus further includes: the system comprises an establishing unit, a processing unit and a processing unit, wherein the establishing unit is used for establishing 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 verifying 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, based on the behavior category tag and the behavior group tag, a plurality of data processing tasks corresponding to the user; the second acquisition module is used for acquiring the 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; and 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 comprises: the first creating module is used for creating a task distribution task; 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 each learning subtask completion state 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 a sorting result; the extraction module is used for extracting the 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 embodiments 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 one 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, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned data processing methods based on an intelligent machine.
In the embodiment of the present invention, behavior information of a user on a target object is obtained, where the behavior information at least includes: and generating a task scheme based on the behavior information by using the behavior category label and the behavior group label, wherein the task scheme at least comprises the following steps: the method comprises a task execution step and a plurality of data processing tasks, wherein the task completion state of the data processing tasks executed on a target object by a user is collected, the task completion state of each data processing task is evaluated to obtain an evaluation record, 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 the embodiment, the time cost of task processing can be reduced, the self-learning and continuous updating growth characteristics are achieved, and the task scheme is continuously optimized, so that the system can obtain the task scheme matched with the system in different business stages, a large amount of data does not need to be collected in the early stage, the learning time cost is reduced, the updating efficiency is improved, the enterprise production efficiency is integrally improved for the efficient operation assistance of the enterprise, and the technical problems that in the related technology, when data updating is carried out, a large amount of data needs to be collected in the early stage, the time cost is high, and the updating 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 embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a flow diagram 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 to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or 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 data updating systems and data updating software of data processing tasks (such as model data processing, intelligent processing of factory machines, and generation of task optimization schemes after multidimensional processing of data intelligent analysis, personal capability profiling and the like of the system), for example, the data updating software of intelligent machines. The embodiment of the invention aims at the problem that the data can be imported only by accumulating a large amount of data in the early stage or the analysis capability tends to be more reasonable when the data are accumulated to a certain order of magnitude in the prior art, utilizes the collected user behavior information to generate a task scheme and automatically updates the task scheme, can reduce the time cost and the machine learning growth cost, has self-learning, continuous updating growth, high processing speed and high-efficiency execution, solves a reasonable growth mode, provides assistance for the high-efficiency operation of enterprises, and integrally improves the production efficiency of the enterprises.
According to the embodiment of the invention, comprehensive evaluation and comparison of the learning subtasks can be carried out through intelligently analyzing data according to a time axis, an operation mode, operation feedback and the like, sequencing is carried out according to a plurality of evaluation weights (such as user weights, user group weights and user classification weights), then a task optimization scheme is generated according to a sequencing result, a data combination mode and a user behavior analysis mode are updated through the task optimization scheme, then the 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 iteration updating. The invention is illustrated below with reference to various examples.
Example one
In accordance with an embodiment of the present invention, there is provided an intelligent machine based data processing method embodiment, it is noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
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, the method comprising the steps of:
step S102, acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: a behavior category label and a behavior group label;
step S104, generating a task scheme based on the behavior information, wherein the task scheme at least comprises the following steps: a task execution step and a plurality of data processing tasks;
step S106, collecting the task completion state of the user executing the data processing task on the target object;
step S108, evaluating the task completion state of each data processing task to obtain an evaluation record;
and 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 acquired, wherein the behavior information at least comprises the following steps: and generating a task scheme based on the behavior information by using the behavior category label and the behavior group label, wherein the task scheme at least comprises the following steps: the method comprises a task execution step and a plurality of data processing tasks, wherein the task completion state of the data processing tasks executed on a target object by a user is collected, the task completion state of each data processing task is evaluated to obtain an evaluation record, 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 the embodiment, the time cost of task processing can be reduced, the self-learning and continuous updating growth characteristics are achieved, and the task scheme is continuously optimized, so that the system can obtain the task scheme matched with the system in different business stages, a large amount of data does not need to be collected in the early stage, the learning time cost is reduced, the updating efficiency is improved, the enterprise production efficiency is integrally improved for the efficient operation assistance of the enterprise, and the technical problems that in the related technology, when data updating is carried out, a large amount of data needs to be collected in the early stage, the time cost is high, and the updating efficiency is low are solved.
The embodiment of the invention can be applied to a machine intelligent data processing system and a data application system/data application software, taking 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 and the like), a behavior recording module (collecting behaviors of a user on a target object), an interest and hobby module (analyzing interest categories, hobbies and characteristics of the user), and an analysis and classification module (classifying and analyzing behaviors of the user on the target object); the intelligent learning structure comprises: a basic data module (analyzing the attributes of login information, behavior information and classified data, registering single operation and single data type of the data), a data combination module (combining various data), a matching user type module (matching user approximate category) and a task pushing and distributing module (pushing a data processing task and a task scheme); the analysis optimization structure comprises: 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.
The following will explain the embodiments of the present invention in detail with reference to the above 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 check is passed.
The target object may indicate a terminal (e.g., cell phone, PC, tablet, IPAD, etc.) held by the user, a logged-in APP, a logged-in application software, etc.
And the login module with the user structure is connected with the system through a network, data butt joint is carried out, login information is recorded, then the user information is verified, and the login information is recorded.
Step S102, acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: a behavior category label and a behavior group label.
Hobby analysis is performed on user behaviors, tagging classification of the user behaviors is performed intelligently, and for example, learning directions (for example, a machine operation flow, a machine disassembly flow and the like) performed on the APP by the user are classified.
Step S104, generating a task scheme based on the behavior information, wherein the task scheme at least comprises the following steps: a task execution step and a plurality of data processing tasks.
In the embodiment of the present invention, the step of generating the task scheme based on the behavior information includes: 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 category tags and the behavior group tags; collecting user information of a user; based on the user information, acquiring learning state data of a user when each data processing task is completed, 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: the dynamic change data or the learning growth data in the learning process can determine the scheme of automatic learning and intelligent processing of the intelligent machine through the learning state data.
Analyzing and classifying the behavior category/behavior group of the labeled user, and performing a multi-dimensional one-to-many grouping mode on the user behavior, namely that one user behavior may exist and a plurality of user behaviors are grouped; and simultaneously recording the task growth information and the task completion information of the user, and storing all the 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 record and the storage are carried out.
And step S106, acquiring the task completion state of the data processing task executed on the target object by the user.
Optionally, the step of collecting the task completion status of the data processing task executed by the user on the target object includes: creating a task distribution task; based on the task distribution task, pushing a data processing task to a template object held by a user; recording a task pushing completion state; and acquiring a 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 a user group belongs to bind and record the task scheme into a task completion record of a recording user, completing the pushing of the task scheme (completed by using a pushing and distributing module), creating a pushing and distributing task, and recording the completion condition of the pushing and distributing task; and sending the target object to the user through the network, sending information to inform the analysis optimization module to monitor, sending the task of the task scheme to the target object, monitoring the operation information of the user, and feeding the operation information back to the analysis optimization module to monitor.
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 each learning subtask completion state on a time axis. When the task completion state is collected, intelligently analyzing the task operation mode, completion progress, completion time and completion condition of each subtask on a time axis of a user, and recording and storing; and sending the obtained data of the task completion states to an intelligent evaluation module, carrying out comprehensive evaluation and recording the evaluation weight/level in the user growth scheme according to the completion progress, completion time and completion condition of the subtasks, and then carrying out sequencing, and also carrying out a plurality of evaluation weight records/level records of user categories, evaluation levels/weights in the user group growth scheme, sequencing and the like.
Step S108, evaluating the task completion state of each data processing task to obtain an evaluation record;
and 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: ranking the evaluation records based on the evaluation weight in the evaluation records to obtain a ranking result; 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 the information of a large number of users is acquired by collecting the tasks of a plurality of users, the intelligent optimization module extracts the optimal scheme in each subtask to combine through evaluation records to generate a task optimization scheme, sends the task optimization scheme to the array combination module in the intelligent learning module, performs self-learning and updating, and updates the classification of the users.
In the embodiment of the invention, the behavior information (including operation information and flow) of the user on the target object is collected through the access login operation of the user, then based on the behavior information, generating a task scheme (combining the quantitative tasks of the atomic services of the service modules of the basic data to obtain each data processing task, distributing the data to reach partial target objects through the network), then collecting the task completion state of the user, feeding back the task completion condition to the application system through the network, dynamically evaluating user behaviors, user types, completion conditions, growth levels, recommendation indexes and the like and updating all task records, and then, for users with various behavior types, the mobile phone task completion condition is performed again, the data processing task is continuously optimized, and the users can obtain growth tasks matched with the users in different service stages by intelligently learning, continuously optimizing and adjusting and analyzing different user behaviors.
Example two
Fig. 2 is a schematic diagram of an alternative data processing apparatus based on an intelligent machine according to an embodiment of the present invention, as shown in fig. 2, the updating apparatus 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 at least includes: a behavior category label and a behavior group label;
a first generating unit 23, configured to generate a task plan based on the behavior information, where the task plan at least includes: a task execution step and a plurality of data processing tasks;
an acquisition unit 25 configured to acquire a task completion state of a user performing a data processing task on a target object;
the evaluation unit 27 is used for evaluating the task completion state of each data processing task to obtain an evaluation record;
and 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 data processing apparatus based on the intelligent machine may acquire behavior information of the user on the target object through the acquiring unit 21, where the behavior information at least includes: the behavior category label and the behavior group label are used for generating a task scheme based on the behavior information through the first generating unit 23, wherein the task scheme at least comprises: the task optimization method comprises a task execution step and a plurality of data processing tasks, wherein the task completion state of the data processing tasks executed on a target object by a user is acquired through an acquisition unit 25, the task completion state of each data processing task is evaluated through an evaluation unit 27 to obtain an evaluation record, and a task optimization scheme is generated through a second generation unit 29 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 learning can be reduced, the system has the characteristics of self-learning and continuous growth updating, through continuous optimization of the task scheme, intelligent learning is continuously optimized and adjusted and different user behavior analysis is performed, so that the system can obtain the task scheme matched with the system in different business stages, a large amount of data do not need to be acquired in the early stage, the learning time cost is reduced, the updating efficiency is improved, the high-efficiency operation assistance is provided for an enterprise, the production efficiency of the enterprise is integrally improved, and the technical problems that when data updating is performed in the related art, a large amount of data need to be acquired in the early stage, the time cost is high, and the updating efficiency is low are solved.
Optionally, the updating apparatus 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 verifying 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 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; 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 user information, wherein the learning state data correspond to a data type; and 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 collecting unit includes: the first creating module is used for creating a task distribution task; the first pushing module is used for pushing the data processing task to the template object held by the 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 the data processing task executed 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 each learning subtask completion state on a time axis.
In an embodiment of the present invention, the second generation unit includes: the sorting module is used for sorting the evaluation records based on the evaluation weights in the evaluation records to obtain a sorting result; the extraction module is used for extracting the 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 above-mentioned data processing device based on an intelligent machine may further include a processor and a memory, the above-mentioned obtaining unit 21, the first generating unit 23, the collecting unit 25, the evaluating unit 27, the second generating unit 29, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to implement the corresponding functions.
The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory. The kernel can be set to be one or more, and the task optimization scheme is generated based on the evaluation record by adjusting the kernel parameters, wherein the task optimization scheme is used for updating 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), and the memory includes at least one memory chip.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including: a processor; and a memory for storing executable instructions for the processor; wherein the processor is configured to perform any of the above-described intelligent machine-based data processing methods via execution of executable instructions.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program, and when the computer program runs, the apparatus where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned data processing methods based on an intelligent machine.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on a data processing device: acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: a behavior category label and a behavior group label; generating a task scheme based on the behavior information, wherein the task scheme at least comprises the following steps: a task execution step and a plurality of data processing tasks; acquiring 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 above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute 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), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A data processing method based on an intelligent machine is characterized by comprising the following steps:
acquiring behavior information of a user on a target object, wherein the behavior information at least comprises: a behavior category label and a behavior group label;
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;
acquiring 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.
2. The method of claim 1, wherein before obtaining the behavior information of the user on the target object, the updating 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 check is passed.
3. The method of claim 1, wherein the step of generating a task plan based on the behavior information comprises:
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 category tags and the behavior group tags;
collecting user information of the user;
based on the user information, acquiring learning state data of a user when each data processing task is completed, 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.
4. 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;
based on the task distribution task, pushing a data processing task to a template object held by a user;
recording a task pushing completion state;
and acquiring a task completion state of executing the data processing task on the target object through network connection.
5. The method of claim 1, wherein the task completion status comprises at least one of: task operation mode, task completion progress, task completion time and each learning subtask completion state on a time axis.
6. The method of claim 1, wherein the step of generating a task optimization plan based on the evaluation record comprises:
ranking the evaluation records based on the evaluation weights in the evaluation records to obtain a ranking result;
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.
7. An intelligent machine-based data processing apparatus, comprising:
an obtaining unit, configured to obtain behavior information of a user on a target object, where the behavior information at least includes: a behavior category label and a behavior group label;
a first generating unit, configured to generate a task plan based on the behavior information, where the task plan at least includes: a task execution step and a plurality of data processing tasks;
the acquisition unit is used for acquiring the task completion state of the data processing task executed on the target object by the user;
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.
8. The updating apparatus according to claim 7, wherein the updating apparatus further comprises:
the system comprises an establishing unit, a processing unit and a processing unit, wherein the establishing unit is used for establishing 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 verifying the login information of the user and recording the login information of the user when the verification is passed.
9. 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 of claims 1 to 6 via execution of the executable instructions.
10. A computer-readable storage medium, comprising a stored computer program, wherein when the computer program runs, the computer-readable storage medium controls a device to execute the intelligent machine-based data processing method according to any one of claims 1 to 6.
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