CN110119880A - A kind of automatic measure grading method, apparatus, storage medium and terminal device - Google Patents
A kind of automatic measure grading method, apparatus, storage medium and terminal device Download PDFInfo
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- CN110119880A CN110119880A CN201910292585.1A CN201910292585A CN110119880A CN 110119880 A CN110119880 A CN 110119880A CN 201910292585 A CN201910292585 A CN 201910292585A CN 110119880 A CN110119880 A CN 110119880A
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- 238000011156 evaluation Methods 0.000 claims description 38
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- 230000006870 function Effects 0.000 claims description 7
- 238000005516 engineering process Methods 0.000 abstract description 8
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Classifications
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/3332—Query translation
- G06F16/3334—Selection or weighting of terms from queries, including natural language queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/33—Querying
- G06F16/3331—Query processing
- G06F16/334—Query execution
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06311—Scheduling, planning or task assignment for a person or group
- G06Q10/063112—Skill-based matching of a person or a group to a task
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06398—Performance of employee with respect to a job function
Abstract
The present invention relates to field of computer technology more particularly to a kind of automatic measure grading method, apparatus, storage medium and terminal device.The described method includes: obtaining the job information and post information of employee to be graded, post information includes post type and current post level；It is determined according to post type and current post level when time target post level of grading；The ability need information of each ability item corresponding to target post level is obtained, and determines corresponding first keyword of each ability item from each ability need information using term frequency-inverse document frequency TF_IDF matrix, generates the first keyword sequence of each ability item；The second keyword corresponding with each ability item is extracted from the job information of employee to be graded using TF_IDF matrix, generates the second keyword sequence of each ability item；The matching degree between the second keyword sequence of each ability item and corresponding first keyword sequence is calculated, and determines the rating result of employee to be graded according to each matching degree, improves the accuracy and efficiency of rating result.
Description
Technical field
The present invention relates to field of computer technology more particularly to a kind of automatic measure grading method, apparatus, computer-readable storage
Medium and terminal device.
Background technique
With the continuous expansion of scope of the enterprise, the quantity of required employee is consequently increased, and flow of personnel also increasingly frequency
It is numerous, thus the personnel promotion management of enterprise how is effectively carried out, flow of personnel is reduced, reduces the brain drain risk of enterprise, then
It is particularly important.In existing personnel promotion method, employee usually is determined according to the simple result of appraisal of related personnel
Promotion situation, i.e., simply determine the rating result of employee according to whether the result of appraisal meet performance assessment criteria, and when examination refers to
It is this to be determined according only to whether the simple result of appraisal meet performance assessment criteria when mark is arranged relatively simple or is arranged unreasonable
The mode of employee's rating result easily causes grading mistake, to influence efficiency of grading, and significantly reduces rating result
Accuracy.
Summary of the invention
The embodiment of the invention provides a kind of automatic measure grading method, apparatus, computer readable storage medium and terminal device,
The rating result of employee to be graded can be automatically determined, improves grading efficiency, and grading mistake is reduced or avoided, improves grading knot
The accuracy of fruit.
The embodiment of the present invention is in a first aspect, provide a kind of automatic measure grading method, comprising:
The job information and post information of employee to be graded are obtained, the post information includes post type and current post
Level；
It is determined according to the post type and the current post level when time target post level of grading；
The ability need information of each ability item corresponding to the target post level is obtained, and utilizes term frequency-inverse document
Frequency TF_IDF matrix determines corresponding first keyword of each ability item from each ability need information, generates each institute
State the first keyword sequence of ability item；
It is extracted from the job information of the employee to be graded using the TF_IDF matrix corresponding with each ability item
The second keyword, generate the second keyword sequence of each ability item；
Calculate between the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item
With degree, and according to the rating result of the determining employee to be graded of each matching degree.
Second aspect of the embodiment of the present invention provides a kind of automatic measure grading device, comprising:
Data obtaining module, for obtaining the job information and post information of employee to be graded, the post information includes
Post type and current post level；
Target tier determining module, for being determined according to the post type and the current post level when time grading
Target post level；
Ability need obtains module, and the ability need for obtaining each ability item corresponding to the target post level is believed
Breath, and determine that each ability item is corresponding from each ability need information using term frequency-inverse document frequency TF_IDF matrix
The first keyword, generate the first keyword sequence of each ability item；
Keyword extracting module, for being extracted from the job information of the employee to be graded using the TF_IDF matrix
The second keyword corresponding with each ability item, generates the second keyword sequence of each ability item；
Rating result determining module, for calculating the second keyword sequence and the of corresponding ability item of each ability item
Matching degree between one keyword sequence, and according to the rating result of the determining employee to be graded of each matching degree.
The third aspect of the embodiment of the present invention provides a kind of computer readable storage medium, the computer-readable storage
Media storage has computer-readable instruction, realizes when the computer-readable instruction is executed by processor such as aforementioned first aspect institute
The step of stating automatic measure grading method.
Fourth aspect of the embodiment of the present invention, provides a kind of terminal device, including memory, processor and is stored in institute
The computer-readable instruction that can be run in memory and on the processor is stated, the processor executes described computer-readable
Following steps are realized when instruction:
The job information and post information of employee to be graded are obtained, the post information includes post type and current post
Level；
It is determined according to the post type and the current post level when time target post level of grading；
The ability need information of each ability item corresponding to the target post level is obtained, and utilizes term frequency-inverse document
Frequency TF_IDF matrix determines corresponding first keyword of each ability item from each ability need information, generates each institute
State the first keyword sequence of ability item；
It is extracted from the job information of the employee to be graded using the TF_IDF matrix corresponding with each ability item
The second keyword, generate the second keyword sequence of each ability item；
Calculate between the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item
With degree, and according to the rating result of the determining employee to be graded of each matching degree.
As can be seen from the above technical solutions, the embodiment of the present invention has the advantage that
In the embodiment of the present invention, when carrying out employee's grading, job information and the post of employee to be graded can be obtained first
Secondly information can be determined when time target post level of grading according to post information, and be obtained corresponding to target post level
The ability need information of each ability item, to be determined from each ability need information using term frequency-inverse document frequency TF_IDF matrix
Corresponding first keyword of each ability item generates the first keyword sequence of each ability item, at the same using TF_IDF matrix from
Extract the second keyword corresponding with each ability item in the job information of employee to be graded to generate each ability item second is crucial
Word sequence, finally can be between the second keyword sequence and the first keyword sequence of corresponding ability item by calculating each ability item
Matching degree determine the matching degree between employee to be graded and target post level, to be automatically determined according to matching degree to be evaluated
The rating result of grade employee.It, can be by analyzing job information and the ability need of employee to be graded comprehensively in the embodiment of the present invention
Matching between information determines the rating result of employee to be graded, i.e., is carried out by the ability item to various dimensions comprehensive
Analysis comprehensively, to accurately determine the rating result of employee to be graded, reduces or avoids grading mistake, improve rating result
Accuracy, and the modification that rating result is repeated and determination are avoided, improve grading efficiency.
Detailed description of the invention
It to describe the technical solutions in the embodiments of the present invention more clearly, below will be to embodiment or description of the prior art
Needed in attached drawing be briefly described, it should be apparent that, the accompanying drawings in the following description is only of the invention some
Embodiment for those of ordinary skill in the art without any creative labor, can also be according to these
Attached drawing obtains other attached drawings.
Fig. 1 is a kind of one embodiment flow chart of automatic measure grading method in the embodiment of the present invention；
Flow diagram of the Fig. 2 for automatic measure grading method a kind of in the embodiment of the present invention under an application scenarios；
Flow diagram of the Fig. 3 for automatic measure grading method a kind of in the embodiment of the present invention under another application scenarios；
Flow diagram of the Fig. 4 for automatic measure grading method a kind of in the embodiment of the present invention under another application scenarios；
Fig. 5 is a kind of one embodiment structure chart of automatic measure grading device in the embodiment of the present invention；
Fig. 6 is a kind of schematic diagram for terminal device that one embodiment of the invention provides.
Specific embodiment
The embodiment of the invention provides a kind of automatic measure grading method, apparatus, computer readable storage medium and terminal device,
For automatically determining the rating result of employee to be graded, grading efficiency is improved, and grading mistake is reduced or avoided, improve grading knot
The accuracy of fruit.
In order to make the invention's purpose, features and advantages of the invention more obvious and easy to understand, below in conjunction with the present invention
Attached drawing in embodiment, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that disclosed below
Embodiment be only a part of the embodiment of the present invention, and not all embodiment.Based on the embodiments of the present invention, this field
Those of ordinary skill's all other embodiment obtained without making creative work, belongs to protection of the present invention
Range.
Referring to Fig. 1, the embodiment of the invention provides a kind of automatic measure grading method, the automatic measure grading method includes:
Step S101, the job information and post information of employee to be graded are obtained, the post information includes post type
With current post level；
The executing subject of the embodiment of the present invention is terminal device, which includes but is not limited to: server, calculating
The equipment such as machine, smart phone and tablet computer.When needing to grade to a certain employee, the member can be inputted in terminal device
The employee can be determined as employee to be graded after receiving identity information by the identity information of work, terminal device, and according to this
Identity information transfers the job information and post information of the employee to be graded from presetting database, wherein the presetting database
In be stored with the routine work information of each employee and the current post type of each employee and current post level, the routine work
Information then may include the professional knowledge that employee is grasped and the Grasping level of each professional knowledge etc..
It is understood that required professional knowledge, post type and the post level grasped of employee can be according to company
Concrete condition determine, such as Internet company, the professional knowledge of required grasp may include Basis of Computer Engineering theory,
Programming language, operating system, middleware Technology, database technology, distributed computing technology, caching technology, architecture technology and network
Agreement etc., post type then can be identified as coding engineer, Architecture Engineer and front end engineer etc., and post level is then
It is primary, intermediate and advanced etc. for being correspondingly arranged.
Step S102, it is determined according to the post type and the current post level when time target post layer of grading
Grade；
It is understood that after getting the post type and current post level after grading employee, then it can basis
The post type of the employee to be graded and current post level determine the target hilllock that the employee to be graded should reach when time grading
Position level.Such as in a certain concrete application, the post type for getting the employee to be graded is front end engineer, corresponding current
Post level is primary, and determines that post level corresponding to the engineer of front end is followed successively by just from low to high as the case may be
When grade-middle rank-is advanced, that is, it can determine that the employee to be graded works as the target post level that time grading should reach for middle rank.
Optionally, described to be determined with the current post level when secondary according to the post type in the embodiment of the present invention
The target post level of grading may include:
Step a, judge whether the employee to be graded meets default grading according to the job information of the employee to be graded
Condition；
If step b, the described employee to be graded meets the default grading condition, according to the post type and described work as
Preceding post level is determined when time target post level of grading.
For above-mentioned steps a and step b, it is to be understood that acquired job information may be used also in the embodiment of the present invention
To include the personal information such as educational background, the registration time limit, the job performance of the employee to be graded, and employee's grading then may be provided with correspondence
Default grading condition, such as can require that the registration time limit of employee reaches 3 years or more and/or job performance reaches a certain
Given threshold etc., that is to say, that when the registration time limit of employee reaches 3 years or more and/or job performance reaches the setting threshold
When value, which just has the grading qualification for participating in grading, and only when the employee has grading qualification, it just can be to this
Employee carries out grading judgement, i.e., just can determine the employee to be graded when time target post level of grading.Therefore, the present invention is implemented
In example, after getting the job information after grading employee, also it is somebody's turn to do firstly the need of basis in the job information of employee to be graded
The registration time limit, the personal information such as job performance, to determine whether the employee to be graded meets default grading condition, with determine should
Whether employee to be graded has the grading qualification for participating in grading, when determining that being somebody's turn to do employee to be graded meets default grading condition, i.e., really
It should can then be determined calmly according to the post type of the employee to be graded and current post level when the employee that grades has grading qualification
When the target post level of secondary grading, to carry out grading judgement to the employee to be graded.
Step S103, the ability need information of each ability item corresponding to the target post level is obtained, and with word frequency-
Inverse document frequency TF_IDF matrix determines corresponding first keyword of each ability item from each ability need information, raw
At the first keyword sequence of each ability item；
It is understood that ability Xiang Kewei corresponding to the level of post is wanted in all types of posies in the embodiment of the present invention
It asks in the professional knowledge of grasp, such as IT industry, the required Basis of Computer Engineering theory grasped of ability Xiang Kewei coding engineer,
Programming language and operating system etc., and ability need information corresponding to each ability item then can be for required by each professional knowledge
Grasping level etc., for example, primary encoder engineer can require the professions such as theoretical Basis of Computer Engineering, programming language and operating system
Mastery of knowledge degree reaches 60% degree of understanding, and intermediate code engineer can then require Basis of Computer Engineering theory, programming
The Grasping level of the professional knowledges such as language and operating system reaches 80% familiarity, and higher level code engineer can then require
The Grasping levels of the professional knowledges such as Basis of Computer Engineering is theoretical, programming language and operating system reaches 90% or more and is proficient in journey
Degree, etc..Thus, it is determining after the target post level of time grading, then can obtain the required palm of the target post level
The ability needs information such as the Grasping level of the professional knowledge and each professional knowledge held.
It should be noted that the professional knowledge of each single item ability item may include multiple information projects, such as in programming language
It may include three information projects such as Java language, C language and C Plus Plus, thus be determined that the target post level institute is right
After the ability item and the corresponding ability need information of each ability item answered, then using term frequency-inverse document frequency TF_IDF matrix
Corresponding first keyword of each ability item is obtained from each ability need information, it is each to be generated according to the first acquired keyword
Corresponding first keyword sequence of ability item, for example, right from programming language institute using term frequency-inverse document frequency TF_IDF matrix
First keywords such as " Java language is familiar with ", " C language is familiar with ", " C Plus Plus understanding " are extracted in the first ability item answered, and
First keyword sequence corresponding to the first ability item being formed according to the sequence of extraction of each first keyword, such as " Java
Language is familiar with " it is first the first keyword extracted, the first keyword, " C++ that " C language is familiar with " is second extraction
Language understands " when being the first keyword that third is extracted, then the first ability item according to composed by each first keyword
The first keyword sequence can for Java language be familiar with, C language be familiar with, C Plus Plus understand, similarly, in Basis of Computer Engineering
The first corresponding keyword can also be extracted in other ability items such as theoretical and operating system successively to form the ability item institute
Corresponding first keyword sequence.Here, the TF_IDF matrix can be obtained by carrying out text training to ability need information.
Step S104, it is extracted from the job information of the employee to be graded using the TF_IDF matrix and each energy
Corresponding second keyword of power item generates the second keyword sequence of each ability item；
In the embodiment of the present invention, it is being determined that each ability item required by the target post level and each ability item are corresponding
The first keyword sequence after, terminal device can also the ability item according to required by the target post level, utilize TF_
IDF matrix extracts the second keyword relevant to each ability item from the job information of the employee to be graded, and will be extracted
The second keyword out combines the second keyword sequence to form the employee to be graded in each ability item, for example, can be sharp first
Relevant to the first ability item (such as programming language) is extracted from the job information of grading employee with TF_IDF matrix
Two keywords, such as " C Plus Plus understanding ", " Java language is proficient in ", " C language is familiar with " are successively extracted using TF_IDF matrix
Second keyword, and the second keyword can be combined to obtain the first ability item the second keyword sequence C Plus Plus understands,
Java language is proficient in, and C language is familiar with }, and so on, terminal device can utilize work of the TF_IDF matrix from the employee to be graded
The second keyword relevant to other ability items is extracted in information in succession, to form the second crucial word order of other ability items
Column.
Step S105, the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item are calculated
Between matching degree, and determine according to each matching degree the rating result of the employee to be graded.
It is understood that terminal device the first keyword sequence and the second keyword sequence for obtaining each ability item it
Afterwards, then the matching degree between the second keyword sequence of each ability item and corresponding first keyword sequence can be calculated, with root
It determines whether the employee to be graded meets Capability Requirement required by the target post level according to matching degree, determines whether to answer
This carries out post promotion to the employee to be graded, i.e., when determining that the employee to be graded meets energy required by the target post level
When force request, then the employee to be graded can be promoted by its current post level to the target post level；And it should be to when determining
When grading employee does not meet Capability Requirement required by the target post level, then the employee to be graded can not be carried out at promotion
Reason.
Further, determine should when the employee that grades meets the target post level, can also to the employee to be graded into
The matching of the next target post level of row, such as when post level is followed successively by primary-intermediate-advanced-expert's grade from low to high
Deng, and when the target post level be middle rank when, then can determine next target post level be it is advanced, therefore, at determination
When being somebody's turn to do the Capability Requirement required by the employee that grades meets middle rank, it can also further judge that the employee to be graded is in primary
It is no to meet advanced required Capability Requirement, if meet advanced required Capability Requirement, it can also further determine whether
Meet Capability Requirement required by expert's grade, etc., until the employee to be graded does not meet required by a certain target post level
Capability Requirement until, at this time then can by the employee to be graded incongruent target post level previous target post level
It is determined as the promotion rank of the employee to be graded, as met energy required by middle rank in primary employee to be graded of being somebody's turn to do when determining
Force request, and meet advanced required Capability Requirement, but when not meeting Capability Requirement required by expert's grade, then it can determine
The promotion rank of the employee to be graded be it is advanced, can by employee grade by primary promotion to advanced.
It should be noted that can also control certainly the series promoted every time in the embodiment of the present invention, i.e., user can
The series that can be promoted every time is set according to specific needs, such as may be configured as 1 or 2, if if being set as 1, showing
Can only promote level-one every time when the rank for the employee that grades is promoted, therefore, only need whether judge employee to be graded at this time
Capability Requirement required by target post level determined by meeting, does not need for carrying out next target post level again
Match；If if being set as 2, showing carrying out that level-one or two-stage can be promoted every time when the rank for the employee that grades is promoted, because
This, at this time when determining the Capability Requirement required by the employee that grades meets identified target post level, it is also necessary to carry out
The judgement of next target post level determines the promotion rank of employee to be graded with this；When the series that can be promoted is set as other
It, can the rest may be inferred when series.
Further, in the embodiment of the present invention, second keyword sequence for calculating each ability item with to should be able to
Matching degree between first keyword sequence of power item may include:
According to preset matching degree computation model, the second keyword sequence and corresponding ability item of each ability item are calculated
The first keyword sequence between matching degree, the matching degree computation model are as follows:
Wherein, MatchPoint (Interface2, Interface1) is that the second keyword sequence is closed with corresponding first
Matching degree between keyword sequence, KeyWord2jFor the second keyword sequence, KeyWord1iFor the first keyword sequence, ρ
(KeyWord2j,KeyWord1i) it is i-th in j-th of second keywords in the second keyword sequence and the first keyword sequence
The degree of association between first keyword, m are the total number for the second keyword that the second keyword sequence includes, and n is first crucial
The total number for the first keyword for including in word sequence,For maximum value Selection of Function, Quotiety is default system
Number.
In the embodiment of the present invention, terminal device by the first keyword sequence of each ability item and can correspond to ability item respectively
Each second keyword sequence imports in matching degree computation model, corresponding with the target post level each to Ratings User to determine
Matching degree between ability item can indicate that this more meets the target hilllock to Ratings User if the numerical value of the matching degree is bigger
Capability Requirement required by the level of position；Conversely, can be shown that this is more discontented to Ratings User if the numerical value of the matching degree is smaller
Capability Requirement required by the foot target post level.
It is understood that due to each key in the first keyword sequence and the second keyword sequence of each ability item
The order of word is that occur what order determined according in the job information of ability need information and employee to be graded, therefore, phase
The meaning characterized with the keyword of position might not be identical, in the embodiment of the present invention, is determining that the second of each ability item closes
When matching degree between keyword sequence and each keyword in the first keyword sequence of corresponding ability item, it can pass throughFunction from chosen in the first keyword sequence maximum one of the degree of association as in the second keyword sequence
Keyword corresponding to associative key, and the degree of association between two keywords can then pass through the Euclidean distance between two keywords
It indicates, can determine the matching degree between two keyword sequences based on the Euclidean distance between each keyword, for example,
When determining the matching degree between the second keyword sequence A and the first keyword sequence A ', can first by calculate keyword it
Between Euclidean distance come determine in the first keyword sequence A ' with each second keyword most phase in the second keyword sequence A
As the first keyword, and the Euclidean distance between each second keyword and most similar first keyword is obtained, with basis
Acquired each Euclidean distance obtains the matching degree between the second keyword sequence A and the first keyword sequence A ', by upper
The calculation stated can greatly improve the accuracy rate of matching degree numerical value.
It preferably, can as shown in Fig. 2, the rating result for determining the employee to be graded according to each matching degree
To include:
Step S201, the corresponding first default weight of each ability item is obtained；
Step S202, each matching degree and the corresponding first default weight of each ability item are based on, determine it is described to
The first compatible degree graded between employee and the target post level；
Step S203, the rating result of the employee to be graded is determined according to first compatible degree.
For above-mentioned steps S201 to step S203, it is to be understood that terminal device is calculating each second keyword
After matching degree between sequence and corresponding first keyword sequence, i.e., terminal device is determining this to Ratings User and each energy
After matching degree between power item, the corresponding first default weight of available each ability item, and can be according to each first default weight
Each matching degree is weighted, determines that first between the employee to be graded and the target post level agrees with this
Degree specifically can determine that formula determines between the employee to be graded and the target post level according to following compatible degrees
First compatible degree:
Wherein, Compatibility (Target1) is the first compatible degree, QuotietytIt is corresponding for t-th of ability item
First default weight, MatchPointt(Interface2, Interface1) is the second keyword sequence of t-th of ability item
With the matching degree between corresponding first keyword sequence, T is the total number of ability item.
Here, calculating this after the first compatible degree between grading employee and the target post level, then it can basis
First compatible degree determines the rating result of the employee to be graded, if such as first compatible degree be greater than pre-set compatible degree
When threshold value, then show that the employee to be graded meets Capability Requirement required by the target post level, therefore obtain this being waited for
Grading employee promotes to the rating result of the target post level；If it is pre-set that first compatible degree is less than or equal to this
When compatible degree threshold value, then show that the employee to be graded is unsatisfactory for Capability Requirement required by the target post level, therefore obtain
The employee to be graded can not be promoted to the rating result of the target post level.
In embodiments of the present invention, by calculating the matching degree of each ability item, so as to accurately calculate wait grade
Compatible degree between employee and target post level, improves the accuracy of compatible degree calculating, to improve rating result certainly
The dynamic accuracy generated.
Further, as shown in figure 3, in an application scenarios, it is described according to first compatible degree determine it is described to
Grade employee rating result, may include
Step S301, the corresponding default review information of each ability item of employee to be graded described in acquisition；
In the embodiment of the present invention, when carrying out the grading of employee, also settable reviewer, the reviewer can be hilllock
Position type other employees identical with the post type of employee to be graded is somebody's turn to do, wherein the reviewer can be according to the target hilllock
Ability item required by the level of position carries out merit rating to the employee to be graded, and obtains the employee to be graded in each ability item
Default review information, terminal device when the employee that grades grades, then can obtain each reviewer for this to this automatically
The default review information of employee to be graded.
Step S302, it is corresponding that each ability item is extracted from the default review information using the TF_IDF matrix
Keyword is evaluated, the evaluation keyword sequence of each ability item is generated；
It is understood that terminal device is after obtaining each default review information, then using the TF_IDF matrix from
The corresponding evaluation keyword of each ability item is extracted in each default review information, and evaluation corresponding to each ability item is generated with this and is closed
Keyword sequence.
Step S303, the first keyword sequence of the evaluation keyword sequence and corresponding ability item of each ability item is calculated
Between evaluation matching degree；
In the embodiment of the present invention, terminal device can then be counted after obtaining the corresponding evaluation keyword sequence of each ability item
The evaluation matching degree between the evaluation keyword sequence of each ability item and corresponding first keyword sequence is calculated, it such as can be according to above-mentioned
The matching degree computation model, to calculate the evaluation between each evaluation keyword sequence and corresponding first keyword sequence
With degree, i.e. each first keyword sequence and each evaluation keyword sequence can be imported matching degree computation model respectively by terminal device
It is interior, to determine that this waits for the evaluation matching degree between Ratings User each ability item corresponding with the target post level, if the evaluation
The numerical value of matching degree is bigger, then it represents that the degree that the employee to be graded meets Capability Requirement required by the target post level is got over
It is high；Conversely, showing that the employee to be graded meets required by the target post level if the numerical value of the evaluation matching degree is smaller
The degree of Capability Requirement is lower.
Step S304, it is based on each evaluation matching degree and the corresponding first default weight of each ability item, determines institute
State the second compatible degree between employee to be graded and the target post level；
It is understood that terminal device calculate each evaluation keyword sequence and corresponding first keyword sequence it
Between matching degree after, i.e., terminal device is determining that this, can be with after the evaluation matching degree between grading employee and each ability item
Each evaluation matching degree is weighted in the corresponding first default weight of each ability item, determines the employee to be graded with this
With the second compatible degree between the target post level, wherein second compatible degree can be also according to compatible degree described above
Determine that formula is calculated.
Step S305, according to first compatible degree and second compatible degree, the grading of the employee to be graded is determined
As a result.
In the embodiment of the present invention, determine the first compatible degree between the employee to be graded and the target post level and
After second compatible degree, then the rating result of the employee to be graded can be determined according to first compatible degree and second compatible degree,
If such as first compatible degree is greater than pre-set first compatible degree threshold value, and second compatible degree is greater than pre-set the
If two compatible degree threshold values, then it is believed that the employee to be graded meets Capability Requirement required by the target post level, therefore
It obtains the employee to be graded being promoted to the rating result of the target post level；And if first compatible degree is less than or waits
If the first compatible degree threshold value or second compatible degree are less than or equal to the second compatible degree threshold value, then it can recognize
It is unsatisfactory for Capability Requirement required by the target post level for the employee to be graded, therefore obtaining can not be by the employee to be graded
It promotes to the rating result of the target post level.
Preferably, described according to described in the embodiment of the present invention as shown in figure 4, in a concrete application scene
One compatible degree and second compatible degree determine the rating result of the employee to be graded, may include:
Step S401, it obtains the corresponding second default weight of first compatible degree and second compatible degree is corresponding comments
Examine weight；
Step S402, first compatible degree, second compatible degree, the second default weight and the evaluation are based on
Weight determines the third compatible degree between the employee to be graded and the target post level；
Step S403, the rating result of the employee to be graded is determined according to the third compatible degree.
For above-mentioned steps S401 to step S403, it is to be understood that can in advance be the corresponding ability of the first compatible degree
Corresponding second default weight is arranged in self-appraisal, and corresponding evaluation weight can be arranged for the corresponding ability evaluation of the second compatible degree,
Terminal device is obtaining this after the first compatible degree and the second compatible degree between grading employee and the target post level, can obtain
Take the corresponding second default weight of first compatible degree evaluation weight corresponding with second compatible degree, and can be second pre- according to this
If first compatible degree and second compatible degree is weighted in weight and the evaluation weight, determine this wait grade with this
Total compatible degree between employee and the target post level, i.e., third compatible degree described above, so as to according to the third contract
The right rating result to determine the employee to be graded.
In the embodiment of the present invention, when carrying out employee's grading, job information and the post of employee to be graded can be obtained first
Secondly information can be determined when time target post level of grading according to post information, and be obtained corresponding to target post level
The ability need information of each ability item, to be determined from each ability need information using term frequency-inverse document frequency TF_IDF matrix
Corresponding first keyword of each ability item generates the first keyword sequence of each ability item, at the same using TF_IDF matrix from
Extract the second keyword corresponding with each ability item in the job information of employee to be graded to generate each ability item second is crucial
Word sequence, finally can be between the second keyword sequence and the first keyword sequence of corresponding ability item by calculating each ability item
Matching degree determine the matching degree between employee to be graded and target post level, to be automatically determined according to matching degree to be evaluated
The rating result of grade employee.It, can be by analyzing job information and the ability need of employee to be graded comprehensively in the embodiment of the present invention
Matching between information determines the rating result of employee to be graded, i.e., is carried out by the ability item to various dimensions comprehensive
Analysis comprehensively, to accurately determine the rating result of employee to be graded, reduces or avoids grading mistake, improve rating result
Accuracy, and the modification that rating result is repeated and determination are avoided, improve grading efficiency.
It should be understood that the size of the serial number of each step is not meant that the order of the execution order in above-described embodiment, each process
Execution sequence should be determined by its function and internal logic, the implementation process without coping with the embodiment of the present invention constitutes any limit
It is fixed.
A kind of automatic measure grading method is essentially described above, a kind of automatic measure grading device will be described in detail below.
As shown in figure 5, the embodiment of the invention provides a kind of automatic measure grading device, the automatic measure grading device includes:
Data obtaining module 501, for obtaining the job information and post information of employee to be graded, the post packet
Include post type and current post level；
Target tier determining module 502 is commented for being determined according to the post type and the current post level when secondary
The target post level of grade；
Ability need obtains module 503, and the ability for obtaining each ability item corresponding to the target post level needs
Information is sought, and determines each ability item from each ability need information using term frequency-inverse document frequency TF_IDF matrix
Corresponding first keyword generates the first keyword sequence of each ability item；
Keyword extracting module 504, for using the TF_IDF matrix from the job information of the employee to be graded
Extract the second keyword corresponding with each ability item, the second keyword sequence of each ability item of generation；
Rating result determining module 505, for calculating the second keyword sequence of each ability item and corresponding ability item
The first keyword sequence between matching degree, and determine according to the matching degree rating result of the employee to be graded.
Further, the rating result determining module 505 is specifically used for according to preset matching degree computation model, meter
Calculate the matching degree between the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item, described
With degree computation model are as follows:
Wherein, MatchPoint (Interface2, Interface1) is that the second keyword sequence is closed with corresponding first
Matching degree between keyword sequence, KeyWord2jFor the second keyword sequence, KeyWord1iFor the first keyword sequence, ρ
(KeyWord2j,KeyWord1i) it is i-th in j-th of second keywords in the second keyword sequence and the first keyword sequence
The degree of association between second keyword, m are the total number for the second keyword that the second keyword sequence includes, and n is first crucial
The total number for the first keyword for including in word sequence,For maximum value Selection of Function, Quotiety is default system
Number.
Preferably, the rating result determining module 505 may include:
First Weight Acquisition unit, for obtaining the corresponding first default weight of each ability item；
First compatible degree determination unit, for based on the corresponding first default power of each matching degree and each ability item
Weight determines the first compatible degree between the employee to be graded and the target post level；
Rating result determination unit, for determining the rating result of the employee to be graded according to first compatible degree.
Optionally, the first compatible degree determination unit, specifically for according to following compatible degrees determine formula determine described in
The first compatible degree between employee to be graded and the target post level:
Wherein, Compatibility (Target1) is the first compatible degree, QuotietytIt is corresponding for t-th of ability item
First default weight, MatchPointt(Interface2, Interface1) is the second keyword sequence of t-th of ability item
With the matching degree between corresponding first keyword sequence, T is the total number of ability item.
Further, the rating result determination unit may include:
Review information obtains subelement, for obtaining the corresponding default evaluation of each ability item of the employee to be graded
Information；
It evaluates sequence and generates subelement, for extracting each institute from the default review information using the TF_IDF matrix
The corresponding evaluation keyword of ability item is stated, the evaluation keyword sequence of each ability item is generated；
Matching degree computation subunit is evaluated, for calculating the evaluation keyword sequence of each ability item and corresponding ability item
The first keyword sequence between evaluation matching degree；
Second compatible degree determines subelement, for being based on each evaluation matching degree and each ability item corresponding first
Default weight, determines the second compatible degree between the employee to be graded and the target post level；
Rating result determines subelement, for according to first compatible degree and second compatible degree, determine it is described to
The rating result of grading employee.
Preferably, the rating result determines subelement, may include:
Weight Acquisition sub-unit is evaluated, for obtaining the corresponding second default weight of first compatible degree and described second
The corresponding evaluation weight of compatible degree；
Third compatible degree determines sub-unit, for being based on first compatible degree, second compatible degree, described second in advance
If weight and the evaluation weight, the third compatible degree between the employee to be graded and the target post level is determined；
Rating result determines sub-unit, for determining the grading knot of the employee to be graded according to the third compatible degree
Fruit.
Optionally, the target tier determining module 502 may include:
Condition judgment unit is evaluated, for judging that the employee to be graded is according to the job information of the employee to be graded
It is no to meet default grading condition；
Target tier determination unit, if meeting the default grading condition for the employee to be graded, according to
Post type and the current post level are determined when time target post level of grading.
Fig. 6 is the schematic diagram for the terminal device that one embodiment of the invention provides.As shown in fig. 6, the terminal of the embodiment is set
Standby 6 include: processor 60, memory 61 and are stored in the meter that can be run in the memory 61 and on the processor 60
Calculation machine readable instruction 62, such as automatic measure grading program.The processor 60 is realized when executing the computer-readable instruction 62
State the step in each automatic measure grading embodiment of the method, such as step S101 shown in FIG. 1 to step S105.Alternatively, the place
Reason device 60 realizes the function of each module/unit in above-mentioned each Installation practice when executing the computer-readable instruction 62, such as
Module 501 shown in fig. 5 to module 505 function.
Illustratively, the computer-readable instruction 62 can be divided into one or more module/units, one
Or multiple module/units are stored in the memory 61, and are executed by the processor 60, to complete the present invention.Institute
Stating one or more module/units can be the series of computation machine readable instruction section that can complete specific function, the instruction segment
For describing implementation procedure of the computer-readable instruction 62 in the terminal device 6.
The terminal device 6 can be the calculating such as desktop PC, notebook, palm PC and cloud server and set
It is standby.The terminal device may include, but be not limited only to, processor 60, memory 61.It will be understood by those skilled in the art that Fig. 6
The only example of terminal device 6 does not constitute the restriction to terminal device 6, may include than illustrating more or fewer portions
Part perhaps combines certain components or different components, such as the terminal device can also include input-output equipment, net
Network access device, bus etc..
The processor 60 can be central processing unit (Central Processing Unit, CPU), can also be
Other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), ready-made programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
Discrete hardware components etc..General processor can be microprocessor or the processor is also possible to any conventional processor
Deng.
The memory 61 can be the internal storage unit of the terminal device 6, such as the hard disk or interior of terminal device 6
It deposits.The memory 61 is also possible to the External memory equipment of the terminal device 6, such as be equipped on the terminal device 6
Plug-in type hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card dodge
Deposit card (Flash Card) etc..Further, the memory 61 can also both include the storage inside list of the terminal device 6
Member also includes External memory equipment.The memory 61 is for storing the computer-readable instruction and terminal device institute
Other programs and data needed.The memory 61 can be also used for temporarily storing the number that has exported or will export
According to.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of software functional units.
If the integrated unit is realized in the form of SFU software functional unit and sells or use as independent product
When, it can store in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially
The all or part of the part that contributes to existing technology or the technical solution can be in the form of software products in other words
It embodies, which is stored in a storage medium, including some instructions are used so that a computer
Equipment (can be personal computer, server or the network equipment etc.) executes the complete of each embodiment the method for the present invention
Portion or part steps.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (ROM, Read-Only
Memory), random access memory (RAM, Random Access Memory), magnetic or disk etc. are various can store journey
The medium of sequence code.
The above, the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although referring to before
Stating embodiment, invention is explained in detail, those skilled in the art should understand that: it still can be to preceding
Technical solution documented by each embodiment is stated to modify or equivalent replacement of some of the technical features；And these
It modifies or replaces, the spirit and scope for technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution.
Claims (10)
1. a kind of automatic measure grading method characterized by comprising
The job information and post information of employee to be graded are obtained, the post information includes post type and current post layer
Grade；
It is determined according to the post type and the current post level when time target post level of grading；
The ability need information of each ability item corresponding to the target post level is obtained, and utilizes term frequency-inverse document frequency
TF_IDF matrix determines corresponding first keyword of each ability item from each ability need information, generates each energy
First keyword sequence of power item；
Corresponding with each ability item is extracted from the job information of the employee to be graded using the TF_IDF matrix
Two keywords generate the second keyword sequence of each ability item；
The matching degree between the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item is calculated,
And the rating result of the employee to be graded is determined according to each matching degree.
2. automatic measure grading method according to claim 1, which is characterized in that second pass for calculating each ability item
Matching degree between keyword sequence and the first keyword sequence of corresponding ability item, comprising:
According to preset matching degree computation model, calculate each ability item the second keyword sequence and corresponding ability item the
Matching degree between one keyword sequence, the matching degree computation model are as follows:
Wherein, MatchPoint (Interface2, Interface1) is the second keyword sequence and corresponding first keyword
Matching degree between sequence, KeyWord2jFor the second keyword sequence, KeyWord1iFor the first keyword sequence, ρ
(KeyWord2j,KeyWord1i) it is i-th in j-th of second keywords in the second keyword sequence and the first keyword sequence
The degree of association between first keyword, m are the total number for the second keyword that the second keyword sequence includes, and n is first crucial
The total number for the first keyword for including in word sequence,For maximum value Selection of Function, Quotiety is default system
Number.
3. automatic measure grading method according to claim 2, which is characterized in that described according to each matching degree determination
The rating result of employee to be graded, comprising:
Obtain the corresponding first default weight of each ability item；
Based on each matching degree and the corresponding first default weight of each ability item, determine the employee to be graded with it is described
The first compatible degree between target post level；
The rating result of the employee to be graded is determined according to first compatible degree.
4. automatic measure grading method according to claim 3, which is characterized in that described based on each matching degree and each described
The corresponding first default weight of ability item determines that first between the employee to be graded and the target post level agrees with
Degree, comprising:
Determine that formula determines that first between the employee to be graded and the target post level agrees with according to following compatible degrees
Degree:
Wherein, Compatibility (Target1) is the first compatible degree, QuotietytIn advance for t-th of ability item corresponding first
If weight, MatchPointt(Interface2, Interface1) be t-th of ability item the second keyword sequence with it is corresponding
The first keyword sequence between matching degree, T be ability item total number.
5. automatic measure grading method according to claim 3, which is characterized in that described to determine institute according to first compatible degree
The rating result of employee to be graded is stated, including
Obtain the corresponding default review information of each ability item of the employee to be graded；
The corresponding evaluation keyword of each ability item is extracted from the default review information using the TF_IDF matrix, it is raw
At the evaluation keyword sequence of each ability item；
Calculate the evaluation between the evaluation keyword sequence of each ability item and the first keyword sequence of corresponding ability item
With degree；
Based on each evaluation matching degree and the corresponding first default weight of each ability item, determine the employee to be graded with
The second compatible degree between the target post level；
According to first compatible degree and second compatible degree, the rating result of the employee to be graded is determined.
6. automatic measure grading method according to claim 5, which is characterized in that described according to first compatible degree and described
Second compatible degree determines the rating result of the employee to be graded, comprising:
Obtain the corresponding second default weight of first compatible degree and the corresponding evaluation weight of second compatible degree；
Based on first compatible degree, second compatible degree, the second default weight and the evaluation weight, determine described in
Third compatible degree between employee to be graded and the target post level；
The rating result of the employee to be graded is determined according to the third compatible degree.
7. automatic measure grading method according to any one of claim 1 to 6, which is characterized in that described according to the post
Type and the current post level are determined when time target post level of grading, comprising:
Judge whether the employee to be graded meets default grading condition according to the job information of the employee to be graded；
If the employee to be graded meets the default grading condition, according to the post type and the current post level
It determines when time target post level of grading.
8. a kind of automatic measure grading device characterized by comprising
Data obtaining module, for obtaining the job information and post information of employee to be graded, the post information includes post
Type and current post level；
Target tier determining module, for being determined according to the post type and the current post level when time target of grading
Post level；
Ability need obtains module, for obtaining the ability need information of each ability item corresponding to the target post level,
And determine that each ability item is corresponding from according to each ability need information using term frequency-inverse document frequency TF_IDF matrix
The first keyword, generate the first keyword sequence of each ability item；
Keyword extracting module, for being extracted from the job information of the employee to be graded using the TF_IDF matrix and respectively
Corresponding second keyword of the ability item, generates the second keyword sequence of each ability item；
Rating result determining module, the second keyword sequence for calculating each ability item are closed with the first of corresponding ability item
Matching degree between keyword sequence, and according to the rating result of the determining employee to be graded of each matching degree.
9. a kind of computer readable storage medium, the computer-readable recording medium storage has computer-readable instruction, special
Sign is, the automatic measure grading as described in any one of claims 1 to 7 is realized when the computer-readable instruction is executed by processor
The step of method.
10. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer-readable instruction of operation, which is characterized in that the processor realizes following step when executing the computer-readable instruction
It is rapid:
The job information and post information of employee to be graded are obtained, the post information includes post type and current post layer
Grade；
It is determined according to the post type and the current post level when time target post level of grading；
The ability need information of each ability item corresponding to the target post level is obtained, and utilizes term frequency-inverse document frequency
TF_IDF matrix determines corresponding first keyword of each ability item from each ability need information, generates each energy
First keyword sequence of power item；
Corresponding with each ability item is extracted from the job information of the employee to be graded using the TF_IDF matrix
Two keywords generate the second keyword sequence of each ability item；
The matching degree between the second keyword sequence of each ability item and the first keyword sequence of corresponding ability item is calculated,
And the rating result of the employee to be graded is determined according to each matching degree.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112508405A (en) * | 2020-12-07 | 2021-03-16 | 云南电网有限责任公司普洱供电局 | Evaluation method and device for power distribution network operation control, computer equipment and medium |
| CN112541691A (en) * | 2020-12-21 | 2021-03-23 | 合肥和创讯为智能科技有限公司 | AI-based dynamic job qualification assessment method and system |
| CN117726307A (en) * | 2024-02-18 | 2024-03-19 | 成都汇智捷成科技有限公司 | Data management method based on business center |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110307257A1 (en) * | 2010-06-10 | 2011-12-15 | Nice Systems Ltd. | Methods and apparatus for real-time interaction analysis in call centers |
| CN106779373A (en) * | 2016-12-05 | 2017-05-31 | 高娟 | A kind of Post Examination method and system |
| CN107862450A (en) * | 2017-10-31 | 2018-03-30 | 下代互联网重大应用技术（北京）工程研究中心有限公司 | Performance appraisal system and method |
| CN108153781A (en) * | 2016-12-05 | 2018-06-12 | 北京国双科技有限公司 | The method and apparatus for extracting the keyword of business scope |
| CN109376982A (en) * | 2018-09-03 | 2019-02-22 | 中国平安人寿保险股份有限公司 | A kind of choosing method and equipment of target employee |
| CN109598402A (en) * | 2018-10-23 | 2019-04-09 | 平安科技（深圳）有限公司 | Data report generation method, device, computer equipment based on data mining |
-
2019
- 2019-04-12 CN CN201910292585.1A patent/CN110119880A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20110307257A1 (en) * | 2010-06-10 | 2011-12-15 | Nice Systems Ltd. | Methods and apparatus for real-time interaction analysis in call centers |
| CN106779373A (en) * | 2016-12-05 | 2017-05-31 | 高娟 | A kind of Post Examination method and system |
| CN108153781A (en) * | 2016-12-05 | 2018-06-12 | 北京国双科技有限公司 | The method and apparatus for extracting the keyword of business scope |
| CN107862450A (en) * | 2017-10-31 | 2018-03-30 | 下代互联网重大应用技术（北京）工程研究中心有限公司 | Performance appraisal system and method |
| CN109376982A (en) * | 2018-09-03 | 2019-02-22 | 中国平安人寿保险股份有限公司 | A kind of choosing method and equipment of target employee |
| CN109598402A (en) * | 2018-10-23 | 2019-04-09 | 平安科技（深圳）有限公司 | Data report generation method, device, computer equipment based on data mining |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112508405A (en) * | 2020-12-07 | 2021-03-16 | 云南电网有限责任公司普洱供电局 | Evaluation method and device for power distribution network operation control, computer equipment and medium |
| CN112541691A (en) * | 2020-12-21 | 2021-03-23 | 合肥和创讯为智能科技有限公司 | AI-based dynamic job qualification assessment method and system |
| CN117726307A (en) * | 2024-02-18 | 2024-03-19 | 成都汇智捷成科技有限公司 | Data management method based on business center |
| CN117726307B (en) * | 2024-02-18 | 2024-04-30 | 成都汇智捷成科技有限公司 | Data management method based on business center |
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