CN113256461A - Online operation approval method, device, server and storage medium - Google Patents
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Abstract
The application provides an online operation correction method, an online operation correction device, a server and a storage medium, and relates to the technical field of operation correction. The method comprises the following steps: receiving a plurality of correction data and target job information sent by a client; carrying out graph fitting on the plurality of correction data to obtain at least one correction graph; calculating the curvature of each correction graph; determining a correction symbol corresponding to each correction graph according to the curvature; and obtaining the evaluation information of the target operation according to the correction symbol. The application can improve the operation correction effect.
Description
Technical Field
The invention relates to the technical field of operation correction, in particular to an online operation correction method, an online operation correction device, a server and a storage medium.
Background
With the rapid development of the internet classroom, more and more teachers arrange online homework for students through software, and the problem that the teachers are inconvenient to carry a large amount of paper homework is avoided.
However, the existing online homework correcting method mainly aims at the objective questions with fixed answers, and judges the correct answer by comparing the answering conditions of the students with the preset answers.
However, in the problem solving process of subjective questions or science homework, the problem solving ideas of different students may not be very same, some problem solving processes are correct, but the result calculation error needs to be deducted, and the right and wrong can not be accurately judged according to the situations, so that the homework correcting effect is poor.
Disclosure of Invention
The present invention is directed to provide a method, an apparatus, a server and a storage medium for online job modification, so as to improve the job modification effect.
In order to achieve the above purpose, the technical solutions adopted in the embodiments of the present application are as follows:
in a first aspect, an embodiment of the present application provides an online job correction method, where the method includes:
receiving a plurality of correction data and target job information sent by a client;
carrying out graph fitting on the plurality of correction data to obtain at least one correction graph;
calculating the curvature of each correction graph;
determining a correction symbol corresponding to each correction graph according to the curvature;
and obtaining the evaluation information of the target operation according to the correction symbol.
Optionally, the performing a graph fitting on the plurality of correction data to obtain at least one correction graph includes:
performing straight line fitting on the plurality of correction data to obtain at least one line correction graph;
the at least one correction graphic comprises: the at least one line modifies the graphic.
Optionally, the determining, according to the curvature, a correction symbol corresponding to the correction pattern includes:
if a first batch modification graph with local maximum curvature exists in the at least one line batch modification graph, determining that the batch modification symbols corresponding to the first batch modification graph are number-matching;
if a single continuous second correction graph with zero curvature exists in the at least one line correction graph, determining that a correction symbol corresponding to the second correction graph is a scribing line;
and if two continuous zero-curvature third correction graphs with intersection points exist in the at least one line correction graph, determining that the correction symbols corresponding to the third correction graphs are wrong numbers.
Optionally, the performing a graph fitting on the plurality of correction data to obtain at least one correction graph includes:
performing circle fitting on the plurality of correction data to obtain at least one circle correction graph;
the at least one correction graphic further comprises: the at least one circle corrects the pattern.
Optionally, the determining, according to the curvature, a correction symbol corresponding to the correction pattern includes:
and if a fourth correction graph with continuous non-zero curvature exists in the at least one round correction graph, determining that a correction symbol corresponding to the fourth correction graph is a circle.
Optionally, before calculating the curvature of each modified graph, the method further includes:
screening the correction graphs meeting preset conditions from the at least one correction graph into effective correction graphs according to the plurality of correction data;
the calculating the curvature of each correction graph comprises the following steps:
and calculating the curvature of the effective correcting graph.
Optionally, the screening, according to the plurality of correction data, a correction pattern that meets a preset condition from the at least one correction pattern as an effective correction pattern includes:
obtaining a fitting value of each correction graph according to each correction graph and data corresponding to each correction graph in the plurality of correction data;
determining the correction graph of which the fitting value is smaller than a preset fitting threshold value in the at least one correction graph as an invalid correction graph;
and determining the correction graph of which the fitting value is greater than or equal to the preset fitting threshold value in the at least one correction graph as the effective correction graph.
In a second aspect, an embodiment of the present application further provides an online work correcting device, where the device includes:
the receiving module is used for receiving a plurality of correction data and target job information sent by the client;
the fitting module is used for performing graph fitting on the plurality of correction data to obtain at least one correction graph;
the curvature calculation module is used for calculating the curvature of each correction graph;
the correction symbol determining module is used for determining the correction symbol corresponding to each correction graph according to the curvature;
and the evaluation information obtaining module is used for obtaining the evaluation information of the target operation according to the correction symbol.
Optionally, the fitting module is configured to perform linear fitting on the plurality of correction data to obtain at least one line correction graph;
the at least one correction graphic comprises: the at least one line modifies the graphic.
Optionally, the correction symbol determining module includes:
the first batch correction symbol determining unit is used for determining the correction symbols corresponding to the first batch of correction patterns as the number if the first batch correction pattern with the local maximum curvature exists in the at least one line batch correction pattern;
a second correction symbol determining unit, configured to determine, if a single continuous zero-curvature second correction pattern exists in the at least one line correction pattern, that a correction symbol corresponding to the second correction pattern is a scribe line;
and the third correction symbol determining unit is used for determining that the correction symbol corresponding to the third correction pattern is an error number if two continuous zero curvatures and the third correction pattern with an intersection point exist in the at least one line correction pattern.
Optionally, the fitting module is configured to perform circle fitting on the plurality of correction data to obtain at least one circle correction graph;
the at least one correction graphic further comprises: the at least one circle corrects the pattern.
Optionally, the correction symbol determining module further includes:
and the fourth correction symbol determining unit is used for determining that the correction symbol corresponding to the fourth correction pattern is circled if the fourth correction pattern with continuous non-zero curvature exists in the at least one circular correction pattern.
Optionally, before the curvature calculating module, the apparatus further includes:
the screening module is used for screening the correction graphs meeting preset conditions from the at least one correction graph into effective correction graphs according to the plurality of correction data;
and the curvature calculation module is used for calculating the curvature of the effective correcting graph.
Optionally, the screening module includes:
a fitting value calculation unit, configured to obtain a fitting value of each correction graph according to each correction graph and data corresponding to each correction graph in the plurality of correction data;
an invalid correction graph determining unit, configured to determine that a correction graph of which a fitting value is smaller than a preset fitting threshold value in the at least one correction graph is an invalid correction graph;
and the effective correction graph determining unit is used for determining the correction graph of which the fitting value is greater than or equal to the preset fitting threshold value in the at least one correction graph as the effective correction graph.
In a third aspect, an embodiment of the present application further provides a server, including: the system comprises a processor, a storage medium and a bus, wherein the storage medium stores program instructions executable by the processor, when the server runs, the processor and the storage medium communicate through the bus, and the processor executes the program instructions to execute the steps of the online work correcting method.
In a fourth aspect, an embodiment of the present application further provides a computer-readable storage medium, where the storage medium stores a computer program, and the computer program is executed by a processor to perform the steps of the online work correcting method according to any one of the above descriptions.
The beneficial effect of this application is:
the method comprises the steps of receiving a plurality of correction data and target job information sent by a client, carrying out graph fitting on the plurality of correction data to obtain at least one correction graph, calculating the curvature of each correction graph, determining a correction symbol corresponding to each correction graph according to the curvature, and obtaining evaluation information of the target job according to the correction symbol. According to the scheme provided by the application, the correction symbol can be determined according to the curvature of the correction graph fitted by the correction data aiming at objective questions, subjective questions or jobs related to the problem solving process, so that the evaluation information of the jobs is determined, and the evaluation information can be obtained aiming at various types of jobs through the correction data of teachers, so that the correction effect of the jobs is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a schematic structural diagram of an online work correction system according to an embodiment of the present disclosure;
fig. 2 is a schematic flow chart of a first online job modification method according to an embodiment of the present disclosure;
fig. 3 is a flowchart illustrating a second method for online work modification according to an embodiment of the present disclosure;
fig. 4 is a flowchart illustrating a third method for modifying an online job according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an online work correction apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic diagram of a server according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some, but not all, embodiments of the present invention.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. 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 application.
In the description of the present application, it should be noted that if the terms "upper", "lower", etc. are used for indicating the orientation or positional relationship based on the orientation or positional relationship shown in the drawings or the orientation or positional relationship which is usually arranged when the product of the application is used, the description is only for convenience of describing the application and simplifying the description, but the indication or suggestion that the referred device or element must have a specific orientation, be constructed in a specific orientation and operation, and thus, cannot be understood as the limitation of the application.
Furthermore, the terms "first," "second," and the like in the description and in the claims, as well as in the drawings, 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.
It should be noted that the features of the embodiments of the present application may be combined with each other without conflict.
The online homework correcting method provided by the embodiment of the application is applied to a server with an online homework correcting function, the server is respectively in communication connection with a student client and a teacher client to obtain target homework submitted by the student client, homework correcting is carried out through the teacher client, and the online homework correcting method is executed according to correcting data to obtain evaluation information of the target homework.
Fig. 1 is a schematic structural diagram of an online work correction system according to an embodiment of the present disclosure; as shown in fig. 1, the online work correction system includes: student client 100, teacher client 200 and server 300, server 300 is with student client 100 and teacher client 200 communication connection respectively.
The student completes the target assignment at the student client 100 and clicks to submit the assignment, thereby transmitting the target assignment to the server 300, the server 300 converts the target assignment completed by the student into a picture format to store in the database, and transmits assignment completion status, completion time, and storage address assignment notification information of the target assignment in the database of the student to the teacher client 200.
After receiving the notification information, the teacher client 200 obtains the target job in the picture format from the database, enters a doodle mode, corrects the target job in a standard correction mode, and sends a plurality of correction data to the server 300 after correction is completed, wherein the correction data is associated with the target job.
After receiving the plurality of correction data sent by the teacher client 200, the server 300 executes the online job correction method provided by the embodiment of the present application to obtain the evaluation information of the target job.
After the server 300 completes the online work correction, the evaluation information of the target work is sent to the teacher client 200, the teacher client 200 jumps to a correction evaluation interface, the evaluation information of the server 300 is displayed, the server 300 submits the evaluation information to the server 300 after the confirmation of no error to complete the correction, and the server 300 sends the evaluation information to the student client 100.
The student client 100 and the teacher client 200 may be any electronic device, such as a mobile phone, a tablet computer, and the like, and are not limited herein.
On the basis of the above-mentioned online work correcting system, an embodiment of the present application provides an online work correcting method, which is applied to a server of the above-mentioned online work correcting system, and fig. 2 is a schematic flow diagram of a first online work correcting method provided in the embodiment of the present application, as shown in fig. 2, the method includes:
s100: and receiving a plurality of pieces of correction data and information of the target job sent by the client.
Specifically, the client comprises a student client and a teacher client, the server receives the information of the target homework uploaded by the student client, converts the information of the target homework into a picture format for storage, and sends notification information to the teacher client to remind the teacher client to correct the target homework. And the teacher client corrects the target operation in a doodling mode, and sends a plurality of correction data to the server after correction is completed. And the server respectively receives the target homework information sent by the student client and a plurality of correction data sent by the teacher client.
S200: and carrying out graph fitting on the plurality of correction data to obtain at least one correction graph.
Specifically, since each correction data obtained by a teacher correcting a target job in a doodle mode at a teacher client is a plurality of discrete data points, in order to identify the correction data formed by the plurality of discrete data points, it is necessary to perform pattern fitting on the discrete data points of the plurality of correction data first to obtain a correction pattern corresponding to each correction data.
In an optional implementation manner, before the image fitting is performed on the plurality of correction data, noise reduction preprocessing can be performed on the plurality of correction data, abnormal correction data with excessive interference is eliminated, and the interference of data jitter on the correction image obtained by fitting is reduced.
S300: the curvature of each correction pattern is calculated.
Specifically, the standard modification mode defines the format of the modification pattern, the curvatures of different modification patterns are different, and curvature calculation is performed on at least one modification pattern obtained by fitting in S200 to obtain the curvature of each modification pattern.
S400: and determining the correction symbol corresponding to each correction graph according to the curvature.
Specifically, the server stores a corresponding relationship between the curvature and the correction symbol in advance, and after the curvature of each correction pattern is calculated according to the above S300, the correction symbol corresponding to the curvature is searched and determined from the corresponding relationship, so as to determine the correction symbol corresponding to each correction pattern.
S500: and obtaining the evaluation information of the target operation according to the correction symbol.
Specifically, the evaluation score corresponding to each correction symbol is judged according to a preset evaluation standard, and the evaluation scores corresponding to the plurality of correction symbols are summarized to obtain the evaluation information of the target job.
According to the online job correction method provided by the embodiment of the application, the plurality of correction data and the information of the target job sent by the client are received, the plurality of correction data are subjected to pattern fitting to obtain at least one correction pattern, the curvature of each correction pattern is calculated, the correction symbol corresponding to each correction pattern is determined according to the curvature, and the evaluation information of the target job is obtained according to the correction symbol. By the method, the correcting symbol can be determined according to the curvature of the correcting graph fitted by the correcting data aiming at objective questions, subjective questions or jobs related to the problem solving process, so that the evaluation information of the jobs is determined, and the evaluation information can be obtained for various types of jobs through the correcting data of teachers, so that the correcting effect of the jobs is improved.
In a possible implementation manner, the S200 includes:
performing straight line fitting on a plurality of correction data to obtain at least one line correction graph, wherein the at least one line correction graph comprises: at least one line modifies the pattern.
Specifically, a first preset fitting method is adopted to perform straight line fitting on the correction data formed by a plurality of discrete data points to obtain at least one line correction graph, and the curvature of each line correction graph is calculated.
For example, the first predetermined fitting method may be a least squares method.
In another possible implementation manner, the S200 includes:
performing circle fitting on the plurality of correction data to obtain at least one circle correction graph; the at least one correction graphic further comprises: at least one circle corrects the pattern.
Specifically, a first preset fitting method or a second preset fitting method is adopted to perform circle fitting on batch modification data formed by a plurality of discrete data points to obtain at least one circle batch modification graph, and the curvature of each circle batch modification graph is calculated.
For example, the second preset fitting method may be a polygon fitting function approxplolydp in OpenCV.
After performing straight line fitting on the plurality of correction data to obtain at least one line correction graph, the step S400 includes:
and if the first batch of correction graphs with local maximum curvature exist in the at least one line batch of correction graphs, determining that the correction symbols corresponding to the first batch of correction graphs are the number pairs.
Specifically, the curvature is a rotation rate of a tangential direction angle of a certain point on the curve to the arc length, and for a straight line, the rotation rate of the tangential direction angle of each point to the arc length is zero, but for a broken line, the rotation rate of the tangential direction angle of an intersection point on the broken line to the arc length is locally maximum relative to the rotation rates of other points on the broken line. And calculating the curvature of each line correction graph, wherein if a broken line with the local maximum curvature exists in one line correction graph, the line correction graph is the first correction graph, and the corresponding correction symbol is a code.
And if a single continuous second correction graph with zero curvature exists in the at least one line correction graph, determining that the correction symbol corresponding to the second correction graph is a scribing line.
Specifically, for the straight lines, the rotation rate of the tangential direction angle of each point to the arc length is zero, the curvature is calculated for each line correction graph, if a straight line with continuous zero curvature exists in one line correction graph, the line correction graph is the second correction graph, and the corresponding correction symbol is a scribe line, for example, an underline.
And if two continuous zero-curvature third correction graphs with intersection points exist in at least one line correction graph, determining that the correction symbols corresponding to the third correction graphs are wrong numbers.
Specifically, the curvature of each line correction graph is calculated, and if two continuous zero-curvature straight lines exist in one line correction graph and the two continuous zero-curvature straight lines have an intersection, the line correction graph is a third correction graph, and the corresponding correction symbol is an error number.
After performing circle fitting on the plurality of correction data to obtain at least one circle correction pattern, the step S400 includes:
and if a fourth correction graph with continuous non-zero curvature exists in the at least one circular correction graph, determining that a correction symbol corresponding to the fourth correction graph is a circle.
Specifically, the curvature is calculated for each circle correction figure, and if an arc line with continuous non-zero curvature exists in one circle correction figure, the circle correction figure is a fourth correction figure, and the corresponding correction symbol is a circle.
In an optional embodiment, a preset evaluation criterion specifies an adding score or a subtracting score corresponding to each correction symbol, after the correction symbol corresponding to the correction pattern is determined according to the curvature, the score corresponding to each correction symbol is determined according to the preset evaluation criterion, the adding score or the subtracting score of the target job is counted according to the adding score or the subtracting score, and then the grade of the target job is determined according to the grade of the score.
For example, a number may correspond to plus five, an underline may correspond to plus two, a wrong number may correspond to minus five, a circle may correspond to minus two, and the rank of the target job may be, for example, excellent, good, passing, or failing.
The on-line operation correction method provided by the embodiment of the application obtains at least one line correction graph and/or at least one circle correction graph by respectively performing straight line fitting and circle fitting on a plurality of correction data, and determines that the line correction graphs are respectively aligned, scribed or wrong by performing curvature calculation on the line correction graphs and the circle correction graphs, and the circle correction graphs are circled. By the method, the correction symbols corresponding to the correction graphs fitted by the plurality of correction data can be identified, so that the target operation is evaluated, and the correction effect of the operation is improved.
On the basis of the foregoing embodiment, an embodiment of the present application further provides an online job modification method, and fig. 3 is a flowchart illustrating a second online job modification method provided in the embodiment of the present application, and as shown in fig. 3, before the foregoing S300, the method further includes:
s301: and screening the correction graphs meeting preset conditions from at least one correction graph as effective correction graphs according to the plurality of correction data.
Specifically, when the plurality of correction data are subjected to graph fitting, correction graphs fitted by abnormal data exist, the abnormal data can be data generated by error touch when a teacher performs operation correction at a teacher client, or points generated when correction is completed every time due to correction habits of the teacher, and the correction graphs meeting preset conditions are used as effective correction graphs by screening the correction graphs.
The above S300 includes:
s302: the curvature of the effective correction pattern is calculated.
Specifically, after the at least one correction pattern is screened in S301, curvature calculation is performed on the obtained effective correction pattern, and a specific calculation method is the same as that in S300, and is not described herein again.
According to the online work correcting method provided by the embodiment of the application, the correcting graph meeting the preset condition is screened from at least one correcting graph to be an effective correcting graph according to a plurality of correcting data, and the curvature of the effective correcting graph is calculated. By the method provided by the embodiment of the application, the correction graphs can be screened through the preset conditions, the accuracy that the evaluation information of the target operation is influenced by the invalid curvature obtained through calculation is avoided, and the accuracy and the effect of the on-line operation correction are improved.
On the basis of the foregoing embodiments, an embodiment of the present application further provides an online job modification method, and fig. 4 is a flowchart of a third online job modification method provided in the embodiment of the present application, as shown in fig. 4, where S301 includes:
s301 a: and obtaining a fitting value of each correction graph according to each correction graph and the data corresponding to each correction graph in the plurality of correction data.
Specifically, to ensure the accuracy of the graph fitting result, the correction graph obtained by fitting needs to be compared with the correction data corresponding to the correction graph, and whether the correction graph approaches the corresponding correction data is calculated to obtain the fitting value of each correction graph.
S301 b: and determining the correction graph with the fitting value smaller than a preset fitting threshold value in at least one correction graph as an invalid correction graph.
Specifically, after the fitting value of each correction graph is obtained through calculation, the correction image with the fitting value smaller than the preset fitting threshold value is taken as an invalid correction graph, and is removed from at least one correction graph without calculating the curvature.
S301 c: and determining the correction graph of which the fitting value is greater than or equal to a preset fitting threshold value in at least one correction graph as an effective correction graph.
Specifically, the correction pattern with the fitting value greater than or equal to the preset fitting threshold is used as an effective correction pattern, and the curvature of the effective correction pattern is calculated according to the calculation method of S300.
According to the on-line work correcting method provided by the embodiment of the application, the fitting value of each correcting graph is obtained according to the data corresponding to each correcting graph in each correcting graph and a plurality of correcting data, the correcting graph of which the fitting value is smaller than the preset fitting threshold value in at least one correcting graph is determined to be an invalid correcting graph, and the correcting graph of which the fitting value is larger than or equal to the preset fitting threshold value in at least one correcting graph is determined to be an effective correcting graph. By the method, the correction graph can be screened by calculating the fitting value, the accuracy that invalid curvature influences evaluation information of the target operation is obtained by calculating the fitting graph with the excessively low fitting value is avoided, and the accuracy and the effect of on-line operation correction are improved.
On the basis of the foregoing embodiments, an online work modification apparatus is further provided in the embodiments of the present application, and fig. 5 is a schematic structural diagram of the online work modification apparatus provided in the embodiments of the present application, and as shown in fig. 5, the apparatus includes:
the receiving module 10 is configured to receive a plurality of correction data and target job information sent by a client;
the fitting module 20 is configured to perform graph fitting on the plurality of correction data to obtain at least one correction graph;
a curvature calculating module 30 for calculating the curvature of each correction pattern;
the correction symbol determining module 40 is configured to determine, according to the curvature, a correction symbol corresponding to each correction pattern;
and the evaluation information obtaining module 50 is used for obtaining the evaluation information of the target job according to the correction symbol.
Optionally, the fitting module 20 is configured to perform linear fitting on the plurality of correction data to obtain at least one line correction graph;
the at least one correction graphic comprises: at least one line modifies the pattern.
Optionally, the correction symbol determining module 40 includes:
the first correction symbol determining unit is used for determining correction symbols corresponding to the first correction patterns to be opposite signs if the first correction patterns with local maximum curvatures exist in the at least one line correction pattern;
the second correction symbol determining unit is used for determining that the correction symbol corresponding to the second correction graph is a lineation if the single continuous zero-curvature second correction graph exists in the at least one line correction graph;
and the third correction symbol determining unit is used for determining that the correction symbol corresponding to the third correction pattern is an error number if two continuous zero curvatures and the third correction pattern with an intersection point exist in the at least one line correction pattern.
Optionally, the fitting module 20 is configured to perform circle fitting on the plurality of correction data to obtain at least one circle correction graph;
the at least one correction graphic further comprises: at least one circle corrects the pattern.
Optionally, the correction symbol determining module 40 further includes:
and the fourth correction symbol determining unit is used for determining the correction symbol corresponding to the fourth correction pattern to be a circle if the fourth correction pattern with continuous non-zero curvature exists in the at least one circular correction pattern.
Optionally, before the curvature calculating module 30, the apparatus further includes:
the screening module is used for screening the correction graphs meeting the preset conditions from at least one correction graph into effective correction graphs according to the plurality of correction data;
and a curvature calculating module 30 for calculating the curvature of the effective correction pattern.
Optionally, the screening module includes:
the fitting value calculating unit is used for obtaining a fitting value of each correction graph according to each correction graph and the data corresponding to each correction graph in the plurality of correction data;
the invalid correction graph determining unit is used for determining a correction graph of which the fitting value is smaller than a preset fitting threshold value in at least one correction graph as an invalid correction graph;
and the effective correction graph determining unit is used for determining the correction graph of which the fitting value is greater than or equal to a preset fitting threshold value in at least one correction graph as an effective correction graph.
The above-mentioned apparatus is used for executing the method provided by the foregoing embodiment, and the implementation principle and technical effect are similar, which are not described herein again.
These above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more Application Specific Integrated Circuits (ASICs), or one or more microprocessors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs), among others. For another example, when one of the above modules is implemented in the form of a Processing element scheduler code, the Processing element may be a general-purpose processor, such as a Central Processing Unit (CPU) or other processor capable of calling program code. For another example, these modules may be integrated together and implemented in the form of a System-On-a-Chip (SOC).
Fig. 6 is a schematic diagram of a server provided in an embodiment of the present application, where the server 300 includes: a processor 301, a storage medium 302 and a bus, wherein the storage medium 302 stores program instructions executable by the processor 301, when the server 300 runs, the processor 301 communicates with the storage medium 302 through the bus, and the processor 301 executes the program instructions to execute the above method embodiment. The specific implementation and technical effects are similar, and are not described herein again.
Optionally, the invention also provides a program product, for example a computer-readable storage medium, comprising a program which, when being executed by a processor, is adapted to carry out the above-mentioned method embodiments.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, 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 through some interfaces, devices or units, and may be in an electrical, mechanical 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 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 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, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and shall be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. An online operation batching method, characterized in that the method comprises:
receiving a plurality of correction data and target job information sent by a client;
carrying out graph fitting on the plurality of correction data to obtain at least one correction graph;
calculating the curvature of each correction graph;
determining a correction symbol corresponding to each correction graph according to the curvature;
and obtaining the evaluation information of the target operation according to the correction symbol.
2. The method of claim 1, wherein said graphically fitting said plurality of correction data to obtain at least one of said correction patterns comprises:
performing straight line fitting on the plurality of correction data to obtain at least one line correction graph;
the at least one correction graphic comprises: the at least one line modifies the graphic.
3. The method of claim 2, wherein determining the correction symbol corresponding to the correction graph according to the curvature comprises:
if a first batch modification graph with local maximum curvature exists in the at least one line batch modification graph, determining that the batch modification symbols corresponding to the first batch modification graph are number-matching;
if a single continuous second correction graph with zero curvature exists in the at least one line correction graph, determining that a correction symbol corresponding to the second correction graph is a scribing line;
and if two continuous zero-curvature third correction graphs with intersection points exist in the at least one line correction graph, determining that the correction symbols corresponding to the third correction graphs are wrong numbers.
4. The method of claim 1, wherein said graphically fitting said plurality of correction data to obtain at least one of said correction patterns comprises:
performing circle fitting on the plurality of correction data to obtain at least one circle correction graph;
the at least one correction graphic further comprises: the at least one circle corrects the pattern.
5. The method of claim 4, wherein determining the correction symbol corresponding to the correction graph according to the curvature comprises:
and if a fourth correction graph with continuous non-zero curvature exists in the at least one round correction graph, determining that a correction symbol corresponding to the fourth correction graph is a circle.
6. The method of claim 1, wherein prior to calculating the curvature of each of the wholesale patterns, the method further comprises:
screening the correction graphs meeting preset conditions from the at least one correction graph into effective correction graphs according to the plurality of correction data;
the calculating the curvature of each correction graph comprises the following steps:
and calculating the curvature of the effective correcting graph.
7. The method of claim 6, wherein the screening, from the at least one correction pattern, a correction pattern satisfying a preset condition as a valid correction pattern according to the plurality of correction data comprises:
obtaining a fitting value of each correction graph according to each correction graph and data corresponding to each correction graph in the plurality of correction data;
determining the correction graph of which the fitting value is smaller than a preset fitting threshold value in the at least one correction graph as an invalid correction graph;
and determining the correction graph of which the fitting value is greater than or equal to the preset fitting threshold value in the at least one correction graph as the effective correction graph.
8. An online operation approval apparatus, comprising:
the receiving module is used for receiving a plurality of correction data and target job information sent by the client;
the fitting module is used for performing graph fitting on the plurality of correction data to obtain at least one correction graph;
the curvature calculation module is used for calculating the curvature of each correction graph;
the correction symbol determining module is used for determining the correction symbol corresponding to each correction graph according to the curvature;
and the evaluation information obtaining module is used for obtaining the evaluation information of the target operation according to the correction symbol.
9. A server, comprising: a processor, a storage medium and a bus, the storage medium storing program instructions executable by the processor, the processor and the storage medium communicating via the bus when the server is running, the processor executing the program instructions to perform the steps of the online work wholesale method according to any one of claims 1 to 7.
10. A computer-readable storage medium, having stored thereon a computer program for performing, when executed by a processor, the steps of the method for on-line job modification according to any one of claims 1 to 7.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH07182509A (en) * | 1993-12-24 | 1995-07-21 | Nec Corp | Graphic recognition device |
| US5590220A (en) * | 1992-08-12 | 1996-12-31 | International Business Machines Corporation | Bending point extraction method for optical character recognition system |
| US20050281467A1 (en) * | 2003-01-24 | 2005-12-22 | Stahovich Thomas F | Recognizing multi-stroke symbols |
| US20060062468A1 (en) * | 2004-09-22 | 2006-03-23 | Microsoft Corporation | Analyzing scripts and determining characters in expression recognition |
| CN105653510A (en) * | 2015-12-28 | 2016-06-08 | 智慧方舟科技有限公司 | Electronic homework correction method, device and system |
| CN112287154A (en) * | 2020-10-30 | 2021-01-29 | 北京有竹居网络技术有限公司 | Information statistical method and device, computer equipment and storage medium |
-
2021
- 2021-05-18 CN CN202110543045.3A patent/CN113256461A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US5590220A (en) * | 1992-08-12 | 1996-12-31 | International Business Machines Corporation | Bending point extraction method for optical character recognition system |
| JPH07182509A (en) * | 1993-12-24 | 1995-07-21 | Nec Corp | Graphic recognition device |
| US20050281467A1 (en) * | 2003-01-24 | 2005-12-22 | Stahovich Thomas F | Recognizing multi-stroke symbols |
| US20060062468A1 (en) * | 2004-09-22 | 2006-03-23 | Microsoft Corporation | Analyzing scripts and determining characters in expression recognition |
| CN105653510A (en) * | 2015-12-28 | 2016-06-08 | 智慧方舟科技有限公司 | Electronic homework correction method, device and system |
| CN112287154A (en) * | 2020-10-30 | 2021-01-29 | 北京有竹居网络技术有限公司 | Information statistical method and device, computer equipment and storage medium |
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