CN111143675A - Knowledge data pushing method and related device - Google Patents
Knowledge data pushing method and related device Download PDFInfo
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Abstract
The application discloses a knowledge data pushing method, which comprises the following steps: calculating the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data; performing difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data; and pushing tax professional knowledge data according to the difference data. The multidimensional evaluation data are calculated through the capability identification model, the investigation dimensionality is increased, and on the basis, the professional knowledge data are pushed according to the difference between the multidimensional evaluation data and the standard data, so that more accurate knowledge data can be pushed, and the pushing efficiency of the knowledge data is improved. The application also discloses a knowledge data pushing device, a server and a computer readable storage medium, which have the beneficial effects.
Description
Technical Field
The application relates to the technical field of computers, in particular to a knowledge data pushing method, a knowledge data pushing device, a server and a computer readable storage medium,
background
Professional assessment is a branch of psychology, and the definition of psychology, which is widely accepted academically, is "objective standard measure of behavioural group". Scientific professional assessment is based on a specific theory, and three conditions need to be met through programming such as questionnaire design, sampling, statistical analysis, normal model establishment and the like. Scientific professional assessment is based on a specific theory, and is programmed by designing questionnaires, sampling, statistical analysis, establishing a normal model and the like, and three conditions are required to be met: effectiveness: and testing the accuracy of the result. Reliability: and testing the stability of the result. And (3) normal mode: each psychological test tested had an original score, which normally had no practical significance unless the score was compared with others. Scientific professional assessment is an objective, standardized questionnaire that is scientific, objective, comparable in function, and not available from other self-learned methods.
Therefore, it is common in the prior art to perform professional evaluation on a professional and then push different technical knowledge data to the evaluator according to the result of the evaluation. Specifically, in the prior art, after the tax staff is evaluated, evaluation data is obtained and processed to obtain an evaluation result. And pushing technical knowledge according to the evaluation result. However, the evaluation result is only performance data. The method has no meaning to the actual operation process of an evaluation person, and also has no more influence. If the assessment personnel still push the technical knowledge corresponding to the stage to the assessment personnel if all the knowledge contents of the stage are mastered by the assessment personnel, meaningless data are sent to the assessment personnel, data transmission waste is caused, and more hardware performance resources are occupied. That is to say, the efficiency of pushing technical knowledge data to an evaluator in the prior art is extremely low.
Therefore, how to improve the efficiency of pushing technical knowledge data to an evaluator is a key issue of attention of those skilled in the art.
Disclosure of Invention
The application aims to provide a knowledge data pushing method, a knowledge data pushing device, a server and a computer readable storage medium.
In order to solve the above technical problem, the present application provides a knowledge data pushing method, including:
calculating the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
performing difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data;
and pushing tax professional knowledge data according to the difference data.
Optionally, the calculating process is performed on the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data, and the method includes:
acquiring capability category data, category dimension data, category competence standard data and dimension standard data in the capability identification model file;
and performing data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain the multidimensional evaluation data.
Optionally, performing difference calculation on the multidimensional evaluation data and the target standard evaluation data to obtain difference data, including:
matching a plurality of target standard evaluation data according to the multidimensional evaluation data to obtain the target standard evaluation data;
and calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity algorithm to obtain the difference data.
Optionally, the pushing of the tax professional knowledge data according to the difference data includes:
matching data in a knowledge base according to the difference data to obtain target tax professional knowledge data;
and pushing the target tax professional knowledge data.
The present application further provides a knowledge data pushing apparatus, including:
the evaluation data acquisition module is used for calculating and processing the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
the difference data calculation module is used for carrying out difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data;
and the knowledge data pushing module is used for pushing the tax professional knowledge data according to the difference data.
Optionally, the evaluation data obtaining module includes:
the model file splitting unit is used for acquiring capability category data, category dimension data, category competence standard data and all dimension standard data in the capability identification model file;
and the multidimensional data processing unit is used for carrying out data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain the multidimensional evaluation data.
Optionally, the difference data calculating module includes:
the standard data matching unit is used for matching a plurality of target standard evaluation data according to the multi-dimensional evaluation data to obtain the target standard evaluation data;
and the similarity calculation unit is used for calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity calculation method to obtain the difference data.
Optionally, the knowledge data pushing module includes:
the knowledge data matching unit is used for matching data in a knowledge base according to the difference data to obtain target tax professional knowledge data;
and the knowledge data pushing unit is used for pushing the target tax professional knowledge data.
The present application further provides a server, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the knowledge data pushing method as described above when executing the computer program.
The present application also provides a computer readable storage medium having stored thereon a computer program which, when being executed by a processor, realizes the steps of the knowledge data pushing method as described above.
The knowledge data pushing method provided by the application comprises the following steps: calculating the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data; performing difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data; and pushing tax professional knowledge data according to the difference data.
The tax ability evaluation data are calculated through the ability recognition model file to obtain multidimensional evaluation data, the tax ability evaluation data are not only simply graded and calculated, the referential performance of the evaluation data is improved, the multidimensional evaluation data and the target standard evaluation data are further subjected to difference calculation to obtain difference data, namely the difference between the current evaluation ability and the standard ability is judged, and finally tax professional knowledge data pushing is carried out according to the difference, namely the knowledge pushing is carried out aiming at the standard ability, the pushed professional knowledge can be used, the effect of knowledge pushing is equivalently improved, the waste of performance resources is avoided, and the efficiency of knowledge data pushing is improved.
The application also provides a knowledge data pushing device, a server and a computer readable storage medium, which have the beneficial effects, and are not described herein again.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a flowchart of a knowledge data pushing method further provided in the embodiments of the present application;
fig. 2 is a schematic structural diagram of a knowledge data pushing apparatus according to an embodiment of the present application.
Detailed Description
The core of the application is to provide a knowledge data pushing method, a knowledge data pushing device, a server and a computer readable storage medium, multidimensional evaluation data are calculated through a capability identification model, investigation dimensionality is increased, professional knowledge data pushing is carried out according to the difference between the multidimensional evaluation data and standard data on the basis, more accurate knowledge data can be pushed, and the knowledge data pushing efficiency is improved.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In the prior art, after tax staff are evaluated, evaluation data is obtained and processed to obtain an evaluation result. And pushing technical knowledge according to the evaluation result. However, the evaluation result is only performance data. The method has no meaning to the actual operation process of an evaluation person, and also has no more influence. If the assessment personnel still push the technical knowledge corresponding to the stage to the assessment personnel if all the knowledge contents of the stage are mastered by the assessment personnel, meaningless data are sent to the assessment personnel, data transmission waste is caused, and more hardware performance resources are occupied. That is to say, the efficiency of pushing technical knowledge data to an evaluator in the prior art is extremely low.
In order to solve the problems, the application provides a knowledge data pushing method, the tax ability evaluation data is calculated through an ability recognition model file to obtain multi-dimensional evaluation data, the tax ability evaluation data is not only simply subjected to scoring calculation, the referability of the evaluation data is improved, the multi-dimensional evaluation data and target standard evaluation data are further subjected to difference calculation to obtain difference data, namely, the difference between the current evaluation ability and the standard ability is judged, and finally, tax professional knowledge data is pushed according to the difference, namely, knowledge pushing is carried out according to the standard ability, pushed professional knowledge can be used, so that the effect of knowledge pushing is improved, waste of performance resources is avoided, and the efficiency of knowledge data pushing is improved.
Referring to fig. 1, fig. 1 is a flowchart of a knowledge data pushing method according to an embodiment of the present application.
In this embodiment, the method may include:
s101, calculating the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
the method comprises the steps of calculating and processing received tax ability evaluation data according to an ability identification model file to obtain multidimensional evaluation data.
In the prior art, generally, after an evaluation operation is performed on an evaluation person, obtaining tax ability evaluation data generally includes comparing the data with standard answers to obtain a score of each selected question, and then calculating a complete score of the tax ability evaluation data. Therefore, in the prior art, the tax ability evaluation data is processed to obtain single scoring data. Since professional ability is composed of different basic qualities, there is no way to determine the most needed professional knowledge data by only a single score.
In the step, the tax ability evaluation data is calculated through the ability recognition model file, and the ability values of different dimensions can be recognized in the ability recognition model file. Therefore, multidimensional evaluation data can be obtained finally in the step.
The multi-dimensional evaluation data can evaluate the abilities of evaluation personnel in different dimensions, and the evaluation reliability is higher. Therefore, accurate professional knowledge data can be given for different dimensional capability differences.
Optionally, this step may include:
acquiring capability category data, category dimension data, category competence standard data and dimension standard data in the capability identification model file;
and performing data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain multi-dimensional evaluation data.
Therefore, in the alternative, the process of acquiring the multidimensional evaluation data is mainly explained. The model file can be found to comprise capability category data, category dimension data, category competence standard data and dimension standard data through capability identification, the capability of the model file is divided into different categories through the data, and each category has different dimensions.
S102, carrying out difference calculation on the multidimensional evaluation data and the target standard evaluation data to obtain difference data;
on the basis of S101, the step aims to perform difference calculation between the multidimensional evaluation data and the target standard evaluation data to obtain difference data. I.e. how much the difference between the ability to acquire the assessor and the standard ability is. The calculation of the corresponding difference data in the step is mainly to push accurate professional knowledge data according to the difference data in the next step.
Optionally, this step may include:
step 1, matching a plurality of target standard evaluation data according to the multidimensional evaluation data to obtain target standard evaluation data;
and 2, calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity algorithm to obtain difference data.
Therefore, in the alternative scheme, the multi-dimensional evaluation data is mainly subjected to standard matching to obtain target standard evaluation data. And finally, calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity calculation method to obtain similarity data, and taking the similarity data as difference data. The greater the similarity data, the smaller the difference data, and vice versa.
And S103, pushing tax professional knowledge data according to the difference data.
On the basis of S102, the step aims to carry out tax professional knowledge data pushing according to the difference data. On the basis of acquiring difference data, namely determining the difference between the appraiser and the standard, the tax professional knowledge data is pushed according to the difference.
Specifically, the step may include:
matching data in the knowledge base according to the difference data to obtain target tax professional knowledge data;
and pushing the target tax professional knowledge data.
Therefore, in the alternative scheme, data matching is mainly performed in a knowledge base according to the difference data to obtain target tax professional knowledge data, and then the tax professional knowledge data is pushed. The accuracy and the efficiency of knowledge data push are improved.
In summary, in the embodiment, the tax ability evaluation data is calculated through the ability identification model file to obtain the multidimensional evaluation data, rather than simply scoring the tax ability evaluation data, so that the referential of the evaluation data is improved, the multidimensional evaluation data is further subjected to difference calculation with the target standard evaluation data to obtain difference data, namely, the difference between the current evaluation ability and the standard ability is judged, and finally, tax professional knowledge data is pushed according to the difference, namely, knowledge pushing is performed according to the standard ability, pushed professional knowledge can be used, which is equivalent to improving the effect of knowledge pushing, avoiding wasting performance resources and improving the efficiency of knowledge data pushing.
The knowledge data pushing method provided by the present application is further described below by another specific embodiment.
In this embodiment, the method is applied to the process of evaluating the professional ability of the tax staff and pushing professional knowledge data. The method can comprise the following steps:
step 1, setting a capability category.
The method mainly comprises the following steps of setting capability categories according to the current industry standard: tax clerk, primary tax accountant, middle tax accountant, tax manager, tax master;
and 2, setting dimensions of each category.
Setting by taking a tax specialist as an example: policy understanding, tax planning, risk management, tax management, reporting practice, invoice management, tax-related accounting and the like, and setting the weight of each dimension in the capacity category.
And 3, setting each capability category competence standard.
Taking the tax specialist as an example, setting the total score below 60 points as a poor understanding, 60-80 points as a understanding and 80-100 points as a grasp.
And 4, setting standards of all dimensions.
Taking a tax specialist as an example, setting standard scores of 7 dimensions of policy understanding, tax planning, risk management, tax management, declaration practice, invoice management and tax-related accounting, and forming a standard radar map by using the standard scores.
And 5, generating a competence model radar map according to the evaluation result.
And according to the personnel involved in the evaluation, calculating to obtain the total score of the evaluation personnel and the dimension evaluation of each model according to a preset calculation rule.
And 6, calculating the similarity between the actual evaluation result and the capability standard.
And evaluating whether the evaluation personnel is close to the current evaluation post according to a preset similarity algorithm, and evaluating competence.
And 7, recommending a learning path similar to the capability model.
Calculating similarity according to knowledge dimensions involved in learning courses and dimensional results of an evaluator, obtaining professional knowledge data according to professional knowledge data needing to be learned under the current capability category, and sequencing the professional knowledge data from small to large according to the course similarity; because the smaller the similarity, the lower the mastery degree of the knowledge dimension. Professional knowledge data of the knowledge dimension needs to be pushed preferentially.
The preset calculation rule includes the following contents. Firstly, setting based on a professional ability standard range, wherein the professional ability standard range is S ═ { S | S ∈ multi-order ability position }, and is
Setting a plurality of dimensions X as { X | X ∈ tax special capability }, and simultaneously setting an evaluation standard W for a single s by identificationsF (w). W is the total evaluation result of the model evaluation, and a single-dimension evaluation standard is set for each dimension
Wherein,
the evaluation data is single-dimensional evaluation data. Reissue to order
Wherein mu is the dimension weight,
is the performance for dimension x. Finally, the process is carried out in a batch,
in summary, in this embodiment, different capability models are set for different levels of posts, each capability model is set with different capability dimensions, and different weight coefficients are set for each dimension, and meanwhile, capability model evaluation, single-dimension evaluation, model dimensions, and dimension permissions are all dynamically configurable. Therefore, a radar map can be obtained through the model so as to intuitively embody the capability values of different dimensions of the tax staff.
Further, in order to embody the gap between the evaluators, the standard evaluation data is defined in the embodiment, which is as follows
I.e. for a given S e S,
setting the dimension capability criterion score, i.e.
The following matrix:
wherein s isi(xi) Is a post siCorresponding professional dimension xiThe standard score of (1).
In addition, the preset similarity calculation method in this embodiment may adopt a cosine similarity matching algorithm, where cosine similarity is also called cosine similarity; and (3) evaluating the similarity by calculating the cosine value of the included angle of the two vectors, wherein the smaller the included angle between the two space vectors is, the more the two vectors are matched, the larger cos theta is, and the cos theta is equal to 1 when the two vectors are completely overlapped.
Assume that the n-dimension generalized formula is as follows:
known for siIf the standard capability is set to
In addition, the result of the appraised person is
Therefore, it is not only easy to use
Substituting into a formula to calculate the difference between the appraised person and the standard.
It can be seen that, in the embodiment, the tax ability evaluation data is calculated through the ability identification model file to obtain the multidimensional evaluation data, rather than simply scoring the tax ability evaluation data, so that the referential property of the evaluation data is improved, the multidimensional evaluation data and the target standard evaluation data are further subjected to difference calculation to obtain difference data, namely, the difference between the current evaluation ability and the standard ability is judged, and finally, tax professional knowledge data is pushed according to the difference, namely, knowledge pushing is performed according to the standard ability, pushed professional knowledge can be used, which is equivalent to improving the effect of knowledge pushing, avoiding wasting performance resources and improving the efficiency of knowledge data pushing.
In the following, a knowledge data pushing apparatus provided by an embodiment of the present application is introduced, and a knowledge data pushing apparatus described below and a knowledge data pushing method described above may be referred to correspondingly.
Referring to fig. 2, fig. 2 is a schematic structural diagram of a knowledge data pushing device according to an embodiment of the present application.
In this embodiment, the apparatus may include:
the evaluation data acquisition module 100 is configured to perform calculation processing on the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
the difference data calculation module 200 is used for performing difference calculation on the multidimensional evaluation data and the target standard evaluation data to obtain difference data;
and the knowledge data pushing module 300 is used for pushing the tax professional knowledge data according to the difference data.
Optionally, the evaluation data obtaining module 100 may include:
the model file splitting unit is used for acquiring capability category data, category dimension data, category competence standard data and all dimension standard data in the capability identification model file;
and the multidimensional data processing unit is used for carrying out data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain multidimensional evaluation data.
Optionally, the difference data calculating module 200 may include:
the standard data matching unit is used for matching a plurality of target standard evaluation data according to the multidimensional evaluation data to obtain target standard evaluation data;
and the similarity calculation unit is used for calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity calculation method to obtain difference data.
Optionally, the knowledge data pushing module 300 may include:
the knowledge data matching unit is used for matching the data in the knowledge base according to the difference data to obtain target tax professional knowledge data;
and the knowledge data pushing unit is used for pushing the target tax professional knowledge data.
An embodiment of the present application further provides a server, including:
a memory for storing a computer program;
a processor for implementing the steps of the knowledge data pushing method as described in the above embodiments when executing the computer program.
The present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the steps of the knowledge data pushing method according to the above embodiments.
The computer-readable storage medium may include: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The embodiments are described in a progressive manner in the specification, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. 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.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The knowledge data pushing method, the knowledge data pushing device, the server and the computer readable storage medium provided by the present application are described in detail above. The principles and embodiments of the present application are explained herein using specific examples, which are provided only to help understand the method and the core idea of the present application. It should be noted that, for those skilled in the art, it is possible to make several improvements and modifications to the present application without departing from the principle of the present application, and such improvements and modifications also fall within the scope of the claims of the present application.
Claims (10)
1. A knowledge data pushing method is characterized by comprising the following steps:
calculating the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
performing difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data;
and pushing tax professional knowledge data according to the difference data.
2. The knowledge data pushing method of claim 1, wherein the step of performing calculation processing on the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data comprises the following steps:
acquiring capability category data, category dimension data, category competence standard data and dimension standard data in the capability identification model file;
and performing data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain the multidimensional evaluation data.
3. The knowledge data pushing method of claim 1, wherein the difference calculation of the multidimensional evaluation data and the target standard evaluation data to obtain difference data comprises:
matching a plurality of target standard evaluation data according to the multidimensional evaluation data to obtain the target standard evaluation data;
and calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity algorithm to obtain the difference data.
4. The knowledge data pushing method of claim 1, wherein the pushing of tax professional knowledge data according to the difference data comprises:
matching data in a knowledge base according to the difference data to obtain target tax professional knowledge data;
and pushing the target tax professional knowledge data.
5. A knowledge data pushing apparatus, comprising:
the evaluation data acquisition module is used for calculating and processing the received tax ability evaluation data according to the ability identification model file to obtain multidimensional evaluation data;
the difference data calculation module is used for carrying out difference calculation on the multidimensional evaluation data and target standard evaluation data to obtain difference data;
and the knowledge data pushing module is used for pushing the tax professional knowledge data according to the difference data.
6. The knowledge data pushing device according to claim 5, wherein the evaluation data obtaining module comprises:
the model file splitting unit is used for acquiring capability category data, category dimension data, category competence standard data and all dimension standard data in the capability identification model file;
and the multidimensional data processing unit is used for carrying out data processing on the tax ability evaluation data according to the ability category data, the category dimension data, the category competence standard data and the dimension standard data to obtain the multidimensional evaluation data.
7. The knowledge data pushing apparatus of claim 5, wherein the difference data calculation module comprises:
the standard data matching unit is used for matching a plurality of target standard evaluation data according to the multi-dimensional evaluation data to obtain the target standard evaluation data;
and the similarity calculation unit is used for calculating the multidimensional evaluation data and the target standard evaluation data according to a similarity calculation method to obtain the difference data.
8. The knowledge data pushing apparatus according to claim 5, wherein the knowledge data pushing module comprises:
the knowledge data matching unit is used for matching data in a knowledge base according to the difference data to obtain target tax professional knowledge data;
and the knowledge data pushing unit is used for pushing the target tax professional knowledge data.
9. A server, comprising:
a memory for storing a computer program;
a processor for implementing the steps of the knowledge data pushing method as claimed in any one of claims 1 to 4 when executing the computer program.
10. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the knowledge data pushing method according to any one of claims 1 to 4.
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| CN112733928A (en) * | 2021-01-06 | 2021-04-30 | 安徽易测评信息技术有限公司 | Intelligent algorithm for carrying out standardized splitting matching on evaluation standard based on civilized city evaluation project |
| CN112733928B (en) * | 2021-01-06 | 2024-04-02 | 安徽易测评信息技术有限公司 | Intelligent method for carrying out standardized splitting matching on evaluation standards based on civilized city evaluation items |
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Application publication date: 20200512 |