CN112446807A

CN112446807A - Job analysis method and apparatus, terminal device, and computer-readable storage medium

Info

Publication number: CN112446807A
Application number: CN201910800873.3A
Authority: CN
Inventors: 徐杨
Original assignee: Guangdong Genius Technology Co Ltd
Current assignee: Guangdong Genius Technology Co Ltd
Priority date: 2019-08-28
Filing date: 2019-08-28
Publication date: 2021-03-05

Abstract

The invention provides a job analysis method and device, terminal equipment and a computer readable storage medium, wherein the job analysis method comprises the following steps: acquiring recorded operation information; analyzing the operation information according to the learning habits and physiological habits of the user corresponding to the operation information to obtain an operation completion time table, wherein the operation completion time table comprises the completion sequence and time of the operation; and reminding and guiding the user to finish the operation according to the operation finishing schedule. After the user obtains the operation information, the operation completion time table is obtained according to the learning habits and the physiological habits of the user, the user is timely reminded according to the operation completion time table, and the user is helped to complete the operation more efficiently.

Description

Job analysis method and apparatus, terminal device, and computer-readable storage medium

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for analyzing a job, a terminal device, and a computer-readable storage medium.

Background

Under the influence of social environment, family environment and other aspects, the learning pressure of students is getting larger, and the post-school work is an indispensable link in the teaching process and is an important component of daily learning of the students, so that the high-efficiency completion of the post-school work can not only effectively help the students save time, but also help the students to improve the competitiveness to a certain extent.

At present, many teachers and parents are worried that students cannot timely and effectively complete post-school work; in the process of finishing the post-class homework, students often have no way to do work before a large amount of homework, and a large amount of time is wasted in thinking of the sequence of finishing the homework, so that the homework efficiency is influenced, and the habit of dragging is easily developed.

Disclosure of Invention

The invention aims to provide a homework analysis method and device, terminal equipment and a computer readable storage medium, which effectively solve the technical problem that students cannot reasonably and effectively utilize time in finishing homework.

The technical scheme provided by the invention is as follows:

a job analysis method, comprising:

acquiring recorded operation information;

analyzing the operation information according to the learning habits and physiological habits of the user corresponding to the operation information to obtain an operation completion time table, wherein the operation completion time table comprises the completion sequence and time of the operation;

and reminding and guiding the user to finish the operation according to the operation finishing time table.

According to the technical scheme, the job completion time table is generated according to the learning habits and physiological habits of the user, and the user is helped to complete the job more efficiently and timely in a scientific manner.

Further, before the step of obtaining the job information recorded according to the preset rule, the method further comprises:

acquiring operation data and physiological data of a user within a period of time, wherein the operation data comprises subject sequence of completing operation by the user, operation time of each subject, operation sequence of different subject types in each subject and operation time of each subject type, and the physiological data comprises sleep time period of the user, subject time period suitable for a brain of the user and time period corresponding to different subject types in each subject;

and generating learning habits and physiological habits suitable for the user by combining theoretical physiological habits according to the operation data and the physiological data.

In the technical scheme, the learning habit and the physiological habit of the user are obtained through the big data, and the subsequent more accurate generation of the job completion schedule is facilitated.

Further, the job information of the step acquisition record includes:

acquiring an image of job information recorded according to preset rules through a camera device, wherein the preset rules comprise rules recorded by each job and recording rules among a plurality of jobs;

identifying the character information in the image to obtain the operation information in the image; or

The job information of the step acquisition record includes:

the job information is input by a user manually.

In the technical scheme, the acquired job information is acquired in a shooting mode of the camera device or a manual input mode for selection.

Further, in the step of analyzing the operation information according to the learning habits and physiological habits of the user corresponding to the operation information to obtain the operation completion schedule, the method includes:

acquiring a completion deadline corresponding to the operation information, and importance and difficulty of each operation;

analyzing the operation information according to the learning habits, the physiological habits and the importance and the difficulty of each operation of the user to obtain an operation completion time table;

generating a job schedule according to the job completion time table and the limited completion deadline;

in the reminding and guiding the user to complete the job according to the job completion schedule: and reminding and guiding the user to finish the operation according to the operation schedule.

In the technical scheme, the completion time limit corresponding to the operation information, the importance degree and the difficulty degree of each operation are further acquired, a more reasonable operation schedule is convenient to generate, a user is helped to complete the operation scientifically and reasonably, and the efficiency is improved.

The present invention also provides a job analyzing apparatus, including:

the job acquisition module is used for acquiring the recorded job information;

the operation analysis module is connected with the operation acquisition module and used for analyzing the operation information according to the learning habits and physiological habits of the user to obtain an operation completion time table, and the operation completion time table comprises the completion sequence and time of the operation;

and the operation guiding module is connected with the operation analyzing module and used for reminding and guiding the user to finish the operation according to the operation finishing time table.

Further, the job analysis device further includes:

the data acquisition module is used for acquiring the operation data and the physiological data of the user within a period of time, wherein the operation data comprises the subject sequence of the user completing the operation, the operation time of each subject, the operation sequence of different subject types in each subject and the operation time of each subject type, and the physiological data comprises the sleep time period of the user, the time period of the brain suitable for the subject and the time period corresponding to the different subject types in each subject;

and the habit data generating module is respectively connected with the data acquiring module and the operation analyzing module and is used for generating learning habits and physiological habits suitable for the user by combining theoretical physiological habits according to the operation data and the physiological data.

Further, the job acquisition module includes:

the system comprises a camera unit, a processing unit and a processing unit, wherein the camera unit is used for acquiring an image of job information recorded according to a preset rule, and the preset rule comprises a rule recorded by each job and a recording rule among a plurality of jobs;

the character recognition unit is connected with the camera shooting unit and is used for recognizing character information in the image obtained by the camera shooting unit to obtain operation information in the image; or

The operation acquisition module inputs operation information in a manual mode of a user.

Further, the job acquisition module is further configured to acquire a completion deadline corresponding to the job information, and importance and difficulty of each job;

the operation analysis module is also used for analyzing the operation information according to the learning habits, the physiological habits, the importance degrees and the difficulty degrees of all the operations of the user to obtain an operation completion time table and generating an operation schedule according to the operation completion time table and the limited completion time limit;

and the operation guiding module is also used for reminding and guiding the user to finish the operation according to the operation schedule.

The invention also provides a terminal device, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, and is characterized in that the processor realizes the steps of any one of the job analysis methods when running the computer program.

The present invention also provides a computer-readable storage medium storing a computer program which, when executed by a processor, implements the steps of the job analysis method of any one of the above.

In the job analysis method and device, the terminal device and the computer readable storage medium provided by the invention, after the job information is acquired, the job completion time table is obtained according to the learning habits and the physiological habits of the user, and the user is timely reminded according to the job completion time table, so that the user is helped to complete the job more efficiently.

Drawings

The foregoing features, technical features, advantages and implementations of which will be further described in the following detailed description of the preferred embodiments in a clearly understandable manner in conjunction with the accompanying drawings.

FIG. 1 is a flow chart of a first embodiment of a job analysis method of the present invention;

FIG. 2 is a flow chart of a second embodiment of a job analysis method of the present invention;

FIG. 3 is a flow chart of a third embodiment of a job analysis method of the present invention;

FIG. 4 is a flow chart of a fourth embodiment of a job analysis method of the present invention;

FIG. 5 is a schematic configuration diagram of a sixth embodiment of the task analysis apparatus according to the present invention;

FIG. 6 is a schematic configuration diagram of a seventh embodiment of the task analysis apparatus according to the present invention;

fig. 7 is a schematic structural diagram of an embodiment of a terminal device in the present invention.

The reference numbers illustrate:

100-job analysis device, 110-job acquisition module, 120-job analysis module, 130-job guidance module, 140-data acquisition module and 150-habit data generation module.

DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following will illustrate specific embodiments of the present invention with reference to the drawings. It is to be understood that the drawings in the following description are merely exemplary of the invention and that other drawings and embodiments may be devised by those skilled in the art without the use of inventive faculty.

In a first embodiment of the present invention, a job analysis method includes:

s10 acquiring the recorded job information;

s20, analyzing the operation information according to the learning habits and physiological habits of the user corresponding to the operation information to obtain an operation completion time table, wherein the operation completion time table comprises the completion sequence and time of the operation;

s30 reminds and guides the user to complete the job according to the job completion schedule.

In this embodiment, after the job information of the user is acquired, the job completion schedule is generated according to the learning habits and physiological habits of the user, and the user is guided to complete the job in a more scientific and efficient manner according to the job completion schedule.

The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the task, the time of each task, the sequence of different question types in each subject and the time required by each question type, wherein the task of the operation and the question type corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. For example, in one embodiment, the task items include Chinese, mathematics and English, the question type corresponding to Chinese includes reading comprehension, composition, etc., the question type corresponding to mathematics includes selection question, blank filling question, etc., and the question type corresponding to English includes listening comprehension, reading comprehension, shape completion, blank filling, composition, etc. The subjects completing the operation every day by the user are English, Chinese and mathematics, in the English operation, the completing sequence is complete form filling, reading comprehension, hearing and composition, the time for completing the form filling is 15min (minutes), the time for completing the reading comprehension is 10min, the time for completing the hearing is 40min, and the time for completing the composition is 30 min; in the Chinese work, the work is finished in sequence according to the sequence of the subjects, 20min is needed for finishing reading and understanding, and 1h (hour) is needed for finishing a composition; in the mathematical action, the completion sequence is to fill in the blank, select the question, and the time for filling in the blank is 20min for every 5 questions, and the time for filling in the blank is 25min for every 5 questions.

The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity degree of the brain. For example, the brain at 8-10 am has strict and careful thinking ability, and can take lessons and take notes in class, so that the brain is suitable for overcoming the difficult problem; in the afternoon, except listening to a class, the pen point operation on the same day needs to be quickly and accurately done, and the thinking ability is most agile at 3 pm; the memory of 6-8 points at night is strongest, and the method is suitable for review, induction and note arrangement; one hour before falling asleep, the pillow is suitable for memory and deepens the impression, and particularly, the pillow is reviewed for some objects which are difficult to remember and is not easy to forget. Based on the above, the study time of each subject is reasonably arranged, for example, the contents to be memorized of each subject are reviewed by utilizing the time period after getting up in the morning and one hour before sleeping; the mathematic operation is completed by utilizing the morning time, and the question types which are difficult to work are arranged between 8 and 10 points, and the like. Note that the physiological habit here refers to physiological data studied by scientists, and may be imported by users in advance or may be obtained from large data.

In the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence, and the learning habit of the user is inferior, for example, when the time suitable for completing the mathematical operation in the physiological habit is 7:30-8:30 at night, and the habit of the user is 9:00-10:00 at night, the habit is adjusted according to the physiological habit. When the physiological habit and the learning habit overlap, the learning habit of the user is prioritized and the physiological habit is inferior, for example, when the physiological habit is suitable for reciting the Chinese text and English words in the morning at 6:00-8:00, and the user habit is suitable for reciting the Chinese text in the morning at 6:30-7:30, the time for reciting the Chinese text is limited to 6:30-7:30 in the morning according to the user habit.

A second embodiment of the present invention is an optimized embodiment of the first embodiment, and as shown in fig. 2, the job analysis method includes:

s01, acquiring the operation data and physiological data of the user in a period of time, wherein the operation data comprises the subject sequence of the user completing the operation, the operation time of each subject, the operation sequence of different subject types in each subject and the operation time of each subject type, and the physiological data comprises the sleep time period of the user, the time period of the brain suitable for the subject type and the time period corresponding to the different subject types in each subject;

s02, generating learning habits and physiological habits suitable for the user according to the operation data and the physiological data by combining with the theoretical physiological habits;

s10 acquiring the recorded job information;

In this embodiment, before the work is analyzed, the learning habits and the physiological habits of the user are generated according to the big data, and specifically, the work data and the physiological data of the user within a period of time are obtained, where the work data includes a subject sequence in which the user completes work each day within the period of time, a work time of each subject, a work sequence of different subject types in each subject, and a work time of each subject type, and the physiological data includes a sleep period of the user, a period in which the brain is suitable for performing the subject, and a period corresponding to the different subject types in each subject. The user's job data is manually input by the user and physiological data (scientifically-compliant data developed by scientists) is manually imported by the user or acquired from the internet.

For a general student, the learning habit is staged, and is often inseparable from the learning content, the learning habit is set according to the learning stage of the user according to the time period of the homework data, for example, the learning stage is set to be half a month, 1 month or even longer, the homework data and the physiological data are gradually updated along with the progress of the process, new homework data and physiological data are continuously added, and the learning habit and the physiological habit are optimized. If the initial operation data is half a month, after the learning habit of the user is generated, the work and rest information is analyzed according to the learning habit and the physiological habit to obtain an operation completion time table, and in the process of guiding the user to complete the operation according to the operation completion time table, the operation completion condition is led into new operation data to generate new learning habit, and the operation is circulated until the user enters a new learning stage. In addition, even if a new learning phase is entered, the learning habits and physiological habits generated previously can be used as a reference.

Based on the method, after the operation information of the user is acquired, the operation completion time table is generated according to the learning habit and the physical exercise habit of the user, and the user is guided to complete the operation in a more scientific and efficient mode according to the operation completion time table. The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the operation subjects, the time of each subject, the sequence of different subject types in each subject and the time required by each subject type, wherein the operation subjects and the subject types corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity degree of the brain.

A third embodiment of the present invention is an optimized embodiment of the first embodiment, and as shown in fig. 3, the job analysis method includes:

s11, acquiring an image of the job information recorded according to preset rules through the camera device, wherein the preset rules comprise rules recorded by each job and recording rules among a plurality of jobs;

s12 identifying the character information in the image to obtain the operation information;

In this embodiment, after recording a job according to a certain rule, the user uses the image capturing device to capture the job, so as to extract job information according to the text information in the image recognition. Before the camera device is started, whether a user sits in front of a table or not is detected, if yes, the camera device is started, and shooting preparation is made. In order to extract the job information more accurately, the user records the job information according to preset rules, where the preset rules include rules for recording each job and recording rules among a plurality of jobs, for example, each job record includes: subject + content + predicted completion time, the content including job type (textbook, exercise book, test paper, etc.), number of pages, number of questions, question type, etc.; the recording rule among the plurality of jobs may be that the plurality of jobs are separated by semicolons, that the plurality of jobs are separated by paragraphs, and the like, and is not particularly limited herein, and may be limited according to actual conditions, and may be easily identified. In other examples, the user may enter the job information manually. And in each job record, a user sets the predicted completion time according to actual conditions and the predicted completion time is used as a reference of a subsequent job completion time table.

After the operation information of the user is acquired, an operation completion time table is generated according to the learning habits and physiological habits of the user, and the user is guided to complete the operation in a more scientific and efficient manner according to the operation completion time table. The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the operation subjects, the time of each subject, the sequence of different subject types in each subject and the time required by each subject type, wherein the operation subjects and the subject types corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity degree of the brain.

In the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence, and the learning habit of the user is inferior, for example, when the time suitable for completing the mathematical operation in the physiological habit is 7:30-8:30 at night, and the habit of the user is 9:00-10:00 at night, the habit is adjusted according to the physiological habit. When the physiological habit and the learning habit overlap, the learning habit of the user is prioritized and the physiological habit is inferior, for example, when the physiological habit is suitable for reciting the Chinese text and English words in the morning at 6:00-8:00, and the user habit is suitable for reciting the Chinese text in the morning at 6:30-7:30, the time for reciting the Chinese text is limited to 6:30-7:30 in the morning according to the user habit. For the completion time of each operation, besides the learning habit and the physiological habit, the predicted completion time set by the user is also referred, for example, for the mathematical operation, the time for completing the operation according to the learning habit is 30min, the predicted completion time set by the user is 50min, the time for continuously performing the data operation by the user in the physiological habit is 1h, and the time for completing the operation is limited to be 30-50min in the operation completion time table. On the contrary, if the duration of the data operation by the user in the physiological habit is 1h, the duration of the data operation according to the learning habit is 80min, and the expected completion duration set by the user is 100min, the duration of the data operation is limited to 1h in the operation completion schedule, and then the data operation is switched to other subjects according to the physiological habit, and the unfinished mathematical operation is arranged after the other data operation is completed.

A fourth embodiment of the present invention is an optimized embodiment of the first embodiment, and as shown in fig. 4, the job analysis method includes:

s10 acquiring the recorded job information;

s21, acquiring the completion deadline corresponding to the operation information, and the importance degree and difficulty degree of each operation;

s22, analyzing the operation information according to the learning habit, the physiological habit, the importance degree and the difficulty degree of each operation of the user to obtain an operation completion time table;

s23 generating a job schedule according to the job completion schedule and the limited completion deadline;

s30 prompts and guides the user to complete the job according to the job schedule.

In this embodiment, after the job information of the user is acquired, the completion time limit corresponding to the job information, the importance degree and the difficulty degree of each job are further acquired, the job information is analyzed according to the learning habit, the physiological habit, the importance degree and the difficulty degree of each job to obtain a job completion time table, a job schedule is further generated according to the job completion time table and the limited completion time limit, and the user is guided to complete the job in a more scientific and efficient manner according to the job schedule.

The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the task, the time of each task, the sequence of different question types in each subject and the time required by each question type, wherein the task of the operation and the question type corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity jump degree of the brain. In the generation of the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence, and the learning habit of the user is inferior, for example, when the time suitable for completing the mathematical operation in the physiological habit is 7:30-8:30 at night, and the habit of the user is 9:00-10:00 at night, the operation completion time table is adjusted according to the physiological habit. When the physiological habit and the learning habit overlap, the learning habit of the user is prioritized and the physiological habit is inferior, for example, when the physiological habit is suitable for reciting the Chinese text and English words in the morning at 6:00-8:00, and the user habit is suitable for reciting the Chinese text in the morning at 6:30-7:30, the time for reciting the Chinese text is limited to 6:30-7:30 in the morning according to the user habit.

The completion time limit is the time limit for the user to complete each operation in the work and rest information. The importance degree is the priority of completion of each operation, for example, the operation subjects comprise Chinese, politics and mathematics, and the subject priority is limited to mathematics, Chinese and politics; for another example, the math operation includes 3 items, which are post-school exercises, exercise books and test papers, respectively, and the priority order is defined as the test paper, the exercise book and the post-school exercises; for another example, the mathematics exercise includes post-class exercise questions, exercise books and test paper, and the language exercise includes exercise books and test paper, and the priority order is limited to mathematics test paper, language exercise book, mathematics exercise book, post-class exercise questions, and the like. It is noted that, in order to generate a more scientific job completion schedule in combination with the physiological habit, the importance level should be less when arranging the importance levels, such as two levels: must be completed and selected to facilitate scheduling in accordance with physiological habits in jobs of equal priority. The difficulty level is the difficulty level of completing each operation, so that the time in the operation schedule can be adjusted according to the difficulty level of each operation. When the completion time of the operation is limited, a reference time can be preferentially limited for each operation, and the adjustment is carried out by combining the difficulty level, for example, the difficulty level is the first level, and the time is increased by 30% on the basis of the reference time; the difficulty level is the second level, the time is increased by 10% on the basis of the reference time, and the like.

The job completion schedule is different from the job schedule in that the job completion schedule is generated based on job information, learning habits of users, physiological habits, importance and difficulty of each job, and includes a schedule for completing each job in the job information. However, in practical applications, the time of the user is limited, especially the time of the working day at night is more precious, and a more accurate planning is needed, so that the working schedule is generated according to the working completion schedule and the limited completion deadline, specifically, for some optional working, if the time is not enough, the optional working can be selectively abandoned (referring to the option of selecting and abandoning physiological habits); if the operation with high importance degree cannot be completed on time, the operation with high difficulty degree is selectively abandoned according to the difficulty degree, and the operation with high difficulty degree is preferentially completed, so that the user is helped to promote.

A fifth embodiment of the present invention is a preferable embodiment of the second embodiment, and the job analysis method includes:

s10 acquiring the recorded job information;

s23 generating a job schedule according to the job completion schedule and the defined completion deadline;

Based on the above, after the operation information of the user is acquired, the completion period corresponding to the operation information, the importance degree and the difficulty degree of each operation are further acquired, then the operation information is analyzed according to the learning habit, the physical learning habit, the importance degree and the difficulty degree of each operation of the user to obtain an operation completion time table, an operation schedule is further generated according to the operation completion time table and the limited completion period, and the user is guided to complete the operation in a more scientific and efficient manner according to the operation schedule.

A sixth embodiment of the present invention, a job analyzing apparatus 100, as shown in fig. 5, includes:

a job acquisition module 110 for acquiring recorded job information;

the job analysis module 120 connected to the job acquisition module 110 is configured to analyze the job information according to the learning habits and physiological habits of the user to obtain a job completion schedule, where the job completion schedule includes a completion sequence and a completion time of the job;

and a job guiding module 130 connected to the job analyzing module 120, for reminding and guiding the user to complete the job according to the job completion schedule.

In this embodiment, after the job obtaining module 110 obtains the job information of the user, the job analyzing module 120 generates a job completion schedule according to the learning habits and physiological habits of the user, and the job guiding module 130 guides the user to complete the job in a more scientific and efficient manner according to the job completion schedule.

The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the task, the time of each task, the sequence of different question types in each subject and the time required by each question type, wherein the task of the operation and the question type corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity jump degree of the brain. In the generation of the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence, and the learning habit of the user is inferior; when the physiological habit and the learning habit are overlapped, the learning habit of the user is prioritized, and the physiological habit is inferior.

A seventh embodiment of the present invention is a preferable embodiment of the sixth embodiment, and as shown in fig. 6, the job analysis device 100 includes:

a job acquisition module 110 for acquiring recorded job information;

a job guidance module 130 connected to the job analysis module 120, configured to remind and guide the user to complete the job according to the job completion schedule;

the data acquisition module 140 is configured to acquire job data and physiological data of a user within a period of time, where the job data includes a subject sequence in which the user completes a job, a job time of each subject, a job sequence of different subject types in each subject, and a job time of each subject type, and the physiological data includes a sleep period of the user, a period in which a brain is suitable for performing a subject, and a period corresponding to a different subject type in each subject;

and a habit data generating module 150 respectively connected to the data acquiring module 140 and the operation analyzing module 120, and configured to generate a learning habit and a physiological habit suitable for the user according to the operation data and the physiological data and by combining with a theoretical physiological habit.

In this embodiment, before the job analysis, the learning habits and physiological habits of the user are generated according to the big data, specifically, the data obtaining module 140 obtains job data and physiological data of the user within a period of time, where the job data includes a subject sequence in which the user completes the job each day within the period of time, a job time of each subject, a job sequence of different subject types in each subject, and a job time of each subject type, and the physiological data includes a sleep period of the user, a period of time during which the brain is suitable for performing the subject, and a period corresponding to the different subject types in each subject. The user's job data is manually input by the user and physiological data (scientifically-compliant data developed by scientists) is manually imported by the user or acquired from the internet.

Based on this, after the job acquisition module 110 acquires the job information of the user, the job analysis module 120 generates a job completion schedule according to the learning habits and physiological habits of the user, and the job guidance module 130 guides the user to complete the job in a more scientific and efficient manner according to the job completion schedule. The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the operation subjects, the time of each subject, the sequence of different subject types in each subject and the time required by each subject type, wherein the operation subjects and the subject types corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period that the user is suitable for performing the subject and the time period corresponding to different subject types in each subject, i.e. the time period corresponding to the activity degree of the brain. In the generation operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence and the learning habit of the user is inferior; when the physiological habit and the learning habit are overlapped, the learning habit of the user is prioritized, and the physiological habit is inferior.

An eighth embodiment of the present invention is a preferable embodiment of the sixth embodiment, and the job analysis device 100 includes:

a job acquisition module 110 for acquiring recorded job information; the method comprises the following steps:

the system comprises a camera unit, a storage unit and a processing unit, wherein the camera unit is used for acquiring an image of job information recorded according to a preset rule, and the preset rule comprises a rule recorded by each job and a recording rule among a plurality of jobs;

the character recognition unit is connected with the camera shooting unit and used for recognizing character information in the image obtained by the camera shooting unit to obtain operation information in the image;

In this embodiment, after recording the job according to a certain rule, the user uses the image capturing unit to capture the job, and the text recognition unit extracts the job information according to the text information recognized by the image. Before the camera shooting unit is started, whether a user sits in front of a table or not is detected, if yes, the camera shooting unit is started, and shooting preparation is made. In order to facilitate the character recognition unit to extract the job information more accurately, the user records the job information according to preset rules, wherein the preset rules include rules of each job record and recording rules among a plurality of jobs, and if the job record includes: subject + content + predicted completion time, the content including job type (textbook, exercise book, test paper, etc.), number of pages, number of questions, question type, etc.; the recording rule among the plurality of jobs may be that the plurality of jobs are separated by semicolons, that the plurality of jobs are separated by paragraphs, and the like, and is not particularly limited here, and may be limited in accordance with actual circumstances, and may be easily recognized. In other examples, the user may also enter job information manually. And in each job record, a user sets the predicted completion time according to actual conditions, and the predicted completion time is used as a reference of a subsequent job completion time table.

After the job acquisition module 110 acquires the job information of the user, the job analysis module 120 generates a job completion schedule according to the learning habits and physiological habits of the user, and the job guidance module 130 guides the user to complete the job in a more scientific and efficient manner according to the job completion schedule. The learning habit is the habit of the user to finish the operation at ordinary times, and comprises the sequence of the operation subjects, the time of each subject, the sequence of different subject types in each subject and the time required by each subject type, wherein the operation subjects and the subject types corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the period of time suitable for the user to perform the subject and the period of time corresponding to different subject types in each subject, i.e. the period of time corresponding to the activity degree of the brain.

In the generation of the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit is prioritized, and the learning habit of the user is inferior; when the physiological habit and the learning habit are overlapped, the learning habit of the user is prioritized, and the physiological habit is inferior. For the completion time of each operation, besides the learning habit and the physiological habit, the predicted completion time set by the user is also referred, for example, for the mathematical operation, the time for completing the operation according to the learning habit is 30min, the predicted completion time set by the user is 50min, the time for continuously performing the data operation by the user in the physiological habit is 1h, and the time for completing the operation is limited to be 30-50min in the operation completion time table. On the contrary, if the duration of the data operation by the user in the physiological habit is 1h, the duration of the data operation according to the learning habit is 80min, and the expected completion duration set by the user is 100min, the duration of the data operation is limited to 1h in the operation completion schedule, and then the data operation is switched to other subjects according to the physiological habit, and the unfinished mathematical operation is arranged after the completion of other data operations.

A ninth embodiment of the present invention is a preferable embodiment of the sixth embodiment, and the job analysis device 100 includes:

a job obtaining module 110, configured to obtain recorded job information, and obtain a completion deadline corresponding to the job information, and importance and difficulty of each job;

the job analysis module 120 connected to the job acquisition module 110 is configured to analyze the job information according to the learning habits, the physiological habits of the user, and the importance and difficulty of each job to obtain a job completion time table, and to generate a job schedule according to the job completion time table and a limited completion time limit;

and the job guiding module 130 connected with the job analyzing module 120 is used for reminding and guiding the user to complete the job according to the job schedule.

In this embodiment, after the job obtaining module 110 obtains the job information of the user, the completion time limit, the importance degree and the difficulty degree of each job corresponding to the job information are further obtained, so that the job analyzing module 120 analyzes the job information according to the learning habit, the physiological habit, and the importance degree and the difficulty degree of each job of the user to obtain a job completion time table, and further generates a job schedule according to the job completion time table and the defined completion time limit, and the job guiding module 130 guides the user to complete the job in a more scientific and efficient manner according to the job schedule.

The learning habit is the habit of finishing the operation by the user at ordinary times, and comprises the sequence of the task, the time of each task, the sequence of different question types in each subject and the time required by each question type, wherein the task of the operation and the question type corresponding to each subject are preset by the user and are adjusted according to the actual condition of the user. The physiological habit is specifically the time period suitable for the user to conduct the subject and the time period corresponding to different subject types in each subject, namely the time period corresponding to the activity jump degree of the brain. In the generation of the operation completion time table, when the physiological habit and the learning habit deviate, the physiological habit takes precedence, and the learning habit of the user is inferior; when the physiological habit and the learning habit overlap, the learning habit of the user is prioritized and the physiological habit is inferior

A ninth embodiment of the present invention is a preferable embodiment of the seventh embodiment, and the job analysis device 100 includes:

a job guiding module 130 connected to the job analyzing module 120, configured to remind and guide the user to complete the job according to the job schedule;

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of program modules is illustrated, and in practical applications, the above-described distribution of functions may be performed by different program modules, that is, the internal structure of the apparatus may be divided into different program units or modules to perform all or part of the functions described above. Each program module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one processing unit, and the integrated unit may be implemented in a form of hardware, or may be implemented in a form of software program unit. In addition, the specific names of the program modules are only for convenience of distinguishing from each other and are not used for limiting the protection scope of the present application.

Fig. 7 is a schematic structural diagram of a terminal device provided in an embodiment of the present invention, and as shown, the terminal device 200 includes: a processor 220, a memory 210, and a computer program 211 stored in the memory 210 and executable on the processor 220, such as: and (4) a job analysis program. The steps in each of the above-described embodiments of the job analysis method are implemented when the processor 220 executes the computer program 211, or the functions of each of the modules in each of the above-described embodiments of the job analysis apparatus are implemented when the processor 220 executes the computer program 211.

The terminal device 200 may be a notebook, a palm computer, a tablet computer, a mobile phone, or the like. The terminal device 200 may include, but is not limited to, a processor 220, a memory 210. Those skilled in the art will appreciate that fig. 6 is merely an example of the terminal device 200, does not constitute a limitation of the terminal device 200, and may include more or less components than those shown, or combine certain components, or different components, such as: terminal device 200 may also include input-output devices, display devices, network access devices, buses, and the like.

The Processor 220 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete gate or transistor logic, discrete hardware components, etc. The general purpose processor 220 may be a microprocessor or the processor may be any conventional processor or the like.

The memory 210 may be an internal storage unit of the terminal device 200, such as: a hard disk or a memory of the terminal device 200. The memory 210 may also be an external storage device of the terminal device 200, such as: a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal device 200. Further, the memory 210 may also include both an internal storage unit of the terminal device 200 and an external storage device. The memory 210 is used to store the computer program 211 and other programs and data required by the terminal device 200. The memory 210 may also be used to temporarily store data that has been output or is to be output.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described or recited in detail in a certain embodiment, reference may be made to the descriptions of other embodiments.

Those of ordinary skill in the art would appreciate that the elements and algorithm steps of the various embodiments described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the technical solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described apparatus/terminal device embodiments are merely illustrative, and for example, a module or a unit may be divided into only one logical function, and an actual implementation may have another division, for example, a plurality of 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 of some interfaces, devices or units, and may be in an electrical, mechanical or other form.

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 network 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 application 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 modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the method according to the embodiments of the present invention may also be implemented by sending instructions to relevant hardware through the computer program 211, where the computer program 211 may be stored in a computer-readable storage medium, and when the computer program 211 is executed by the processor 220, the steps of the method embodiments may be implemented. Wherein the computer program 211 comprises: computer program code which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device capable of carrying the code of computer program 211, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the content of the computer-readable storage medium can be increased or decreased according to the requirements of legislation and patent practice in the jurisdiction, for example: in certain jurisdictions, in accordance with legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunications signals.

It should be noted that the above embodiments can be freely combined as necessary. The foregoing is only a preferred embodiment of this invention and it should be noted that modifications and adaptations may occur to those skilled in the art without departing from the spirit of the invention and should be considered as within the scope of the invention.

Claims

1. A job analysis method, comprising:

acquiring recorded operation information;

2. The job analysis method according to claim 1, further comprising, before the step of acquiring the job information recorded according to the preset rule:

3. The job analysis method according to claim 1 or 2,

the job information of the step acquisition record includes:

acquiring an image of job information recorded according to a preset rule through a camera device, wherein the preset rule comprises a rule recorded by each job and a recording rule among a plurality of jobs;

The job information of the step acquisition record includes:

the job information is input by a user manually.

4. The work analysis method according to claim 1 or 2, wherein the step of analyzing the work information based on the learning habits and physiological habits of the user to obtain the work completion schedule includes:

5. A work analysis apparatus, comprising:

the job acquisition module is used for acquiring the recorded job information;

the operation analysis module is connected with the operation acquisition module and used for analyzing the operation information according to the learning habits and physiological habits of the user corresponding to the operation information to obtain an operation completion time table, and the operation completion time table comprises the completion sequence and time of the operation;

6. The work analysis apparatus according to claim 5, further comprising:

the data acquisition module is used for acquiring the operation data and the physiological data of the user within a period of time, wherein the operation data comprises the subject sequence of the user completing the operation, the operation time of each subject, the operation sequence of different subject types in each subject and the operation time of each subject type, and the physiological data comprises the sleep time period of the user, the period of time when the brain is suitable for performing the subject types and the time period corresponding to the different subject types in each subject;

7. The work analyzing apparatus according to claim 5 or 6,

the operation acquisition module comprises:

8. The work analyzing apparatus according to claim 5 or 6,

the operation acquisition module is also used for acquiring the completion deadline corresponding to the operation information and the importance degree and difficulty degree of each operation;

the operation analysis module is also used for analyzing the operation information according to the learning habits, the physiological habits and the importance and the difficulty of each operation of the user to obtain an operation completion time table and generating an operation schedule according to the operation completion time table and the limited completion time limit;

9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the job analysis method according to any one of claims 1-4 when running the computer program.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the job analysis method according to any one of claims 1 to 4.