CN109697575A - Data processing method and system based on evaluation result - Google Patents
Data processing method and system based on evaluation result Download PDFInfo
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- CN109697575A CN109697575A CN201910005586.3A CN201910005586A CN109697575A CN 109697575 A CN109697575 A CN 109697575A CN 201910005586 A CN201910005586 A CN 201910005586A CN 109697575 A CN109697575 A CN 109697575A
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Abstract
The problem of disclosure provides a kind of data processing method and system based on evaluation result, is related to the communications field, is able to solve the reason of evaluation object can not obtain deviation between existing evaluation result and expectations result and corresponding optimisation strategy.The specific technical proposal is:, according to evaluation baseline database, determining the difference data of objective appraisal object as a result, when the two result is inconsistent by the existing credit appraisal result of assay object and the expected credit appraisal of evaluation object；According to the difference data of objective appraisal object and evaluation data, objective optimization path policy is generated.The present invention is used for evaluation object assay result.
Description
Technical field
This disclosure relates to field of communication technology, more particularly to data processing method and system based on evaluation result.
Background technique
As national strength promotes the establishment of social credit system, credit appraisal business is also constantly developing.At present in public affairs
Service field, financial field, the credit appraisal of every profession and trade field are being widely used altogether, with being evaluated object to credit
The gradually reinforcement of the attention degree of evaluation.In the prior art, evaluation object credit appraisal is according to rating model to evaluation object
Data targetization processing.However, evaluation object can not accurately know existing evaluation knot since evaluation model is in model of black box
Between fruit and expectations result the reason of deviation, more importantly credit result optimizing strategy can not be obtained；It increases point
Analyse the cost of labor appraised through discussion.
Summary of the invention
The embodiment of the present disclosure provides a kind of data processing method and system, and existing comment can not be obtained by being able to solve evaluation object
Between valence result and expectations result the reason of deviation and the problem of corresponding optimisation strategy.
The technical solution is as follows:
According to the first aspect of the embodiments of the present disclosure, a kind of data processing method based on evaluation result, this method are provided
Include:
The evaluation result and expectations for obtaining objective appraisal object are as a result, evaluation result is based on evaluation model to evaluation
What the evaluation data of object generated；
When evaluation result does not meet expectations result, according to evaluation baseline database, objective appraisal object is determined
Difference data；
According to the difference data of objective appraisal object and evaluation data, objective optimization path policy, path optimizing plan are generated
Slightly, refer to that the evaluation result of objective appraisal object meets the path optimizing strategy of expectations result.
In one embodiment, this method obtain objective appraisal object evaluation result and expectations result before,
Further include:
It obtains user's logon information and carries out authentication process；
After user's logon information passes through authentication process, the basic data and credit data of user are obtained；
According to basic data and credit data, the evaluation data of target user are generated.
In one embodiment, this method is when obtaining the evaluation result of objective appraisal object, further includes:
Indexing processing is carried out to the evaluation data of objective appraisal object, indexing processing refers to through polymerization, logic point
Analysis, data calculate, and will evaluate at least a kind of process for being changed into index from data in data；
And according to processing result and default value strategy, the corresponding review number of evaluation data of objective appraisal object is determined
Value generates the corresponding evaluation result of evaluation data of objective appraisal object.
In one embodiment, this method determines the difference of objective appraisal object according to user credit rating database
Data, comprising:
According to evaluation baseline database, the default corresponding default base-line data of evaluation result is determined；Evaluate base-line data packet
It includes, evaluates the hierarchical categories and graded index data of base-line data；
Default base-line data is parsed, determines the corresponding target classification rank of evaluation result, and corresponding with category level
Target gap value；
According to target classification rank and target gap value, the difference data of objective appraisal object is determined.
In one embodiment, this method exists, and according to evaluation baseline database, determines that default evaluation result is corresponding default
Base-line data, comprising:
Acquisition credit appraisal database, user credit rating database, including, classification information, the review number of evaluation object
According to and evaluation object evaluation result；
According to user credit rating database, after sorting out principle processing, affiliated same category of evaluation object is obtained
And corresponding achievement data, and parameter data, it determines the corresponding index base-line data of classification, generates evaluation base-line data
Library.
In one embodiment, this method exists, and according to classification information and evaluation result, generates credit appraisal database；
Based on default value strategy, the corresponding subclassification information of classification information is determined；
The corresponding evaluation result of subclassification information is obtained, credit appraisal database is generated.
In one embodiment, this method exists, and category level corresponds to target gap value, comprising:
According to credit appraisal database, determine that default evaluation result corresponds at least one default subclassification information；
According to evaluation baseline database, at least one corresponding default subbase line of at least one default subclassification information is determined
Data；
Evaluation result obtains at least one sub-goal gap value compared with presetting sub- base-line data successively, and generates target
Gap value.
In one embodiment, this method exists, and according to the difference data of objective appraisal object and evaluation data, generates target
Path optimizing strategy, including,
Default optimisation strategy is obtained, default optimisation strategy refers to, is arranged based on optimization time, difference data and weighted value
The strategy of sequence combination producing；
Based on default optimisation strategy, at least one corresponding optimisation strategy of evaluation data fit expectations result is determined；
Optimisation strategy, which is set, at least one according to difference data grade determines objective optimization path policy.
The data processing method based on evaluation result that the disclosure provides, passes through the existing credit appraisal knot of assay object
Fruit and the expected credit appraisal of evaluation object, according to evaluation baseline database, determine that target is commented as a result, when the two result is inconsistent
The difference data of valence object；According to the difference data of objective appraisal object and evaluation data, objective optimization path policy is generated, is
Evaluation object optimizing evaluation result provides enforceable optimal way, saves human cost, improves the standard of evaluation data
True property.
According to the second aspect of an embodiment of the present disclosure, a kind of data processing system based on evaluation result is provided, comprising: number
According to evaluating apparatus, data analysis set-up, data storage device；
Data evaluation device, the evaluation result and expectations for obtaining objective appraisal object are as a result, evaluation result is
It is generated based on evaluation data of the evaluation model to evaluation object；
When evaluation result does not meet expectations result, data analysis request is sent to data analysis set-up；
Data analysis set-up, for according to data analysis request, the target of acquisition determined according to evaluation baseline database
The difference data of evaluation object；
According to the difference data of objective appraisal object and evaluation data, objective optimization path policy, path optimizing plan are generated
Slightly, refer to that the evaluation result of objective appraisal object meets the path optimizing strategy of expectations result；
Data storage device, for storing evaluation baseline database.
In one embodiment, the system further include: data computing device,
Data computing device is connected with data evaluation device,
Data computing device generates the evaluation of objective appraisal object for the evaluation data of indexing processing evaluation object
The corresponding evaluation result of data, and evaluation result is sent to data evaluation device.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.
Fig. 1 is a kind of flow chart for data processing method based on evaluation result that the embodiment of the present disclosure provides；
Fig. 2 is a kind of structural schematic diagram for data processing system based on evaluation result that the embodiment of the present disclosure provides；
Fig. 3 is a kind of structural representation Fig. 1 for data processing system based on evaluation result that the embodiment of the present disclosure provides.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
Embodiment one
The embodiment of the present disclosure provides a kind of data transmission method, as shown in Figure 1, the data transmission method includes following step
It is rapid:
101, the evaluation result and expectations result of objective appraisal object are obtained.
Evaluation result is generated based on evaluation data of the evaluation model to evaluation object.
In an alternative embodiment, before the evaluation result and expectations result for obtaining objective appraisal object, further includes:
It obtains evaluation object logon information and carries out authentication process；
After evaluation object logon information passes through authentication process, the basic data and credit data of evaluation object are obtained；
According to basic data and credit data, the evaluation data of objective appraisal object are generated.
In an alternative embodiment, the basic data of evaluation object, identity information, financial information, row including evaluation object
The data such as industry classification；The credit data of evaluation object, comprising: business risk information, executive supervision information, behavior of credit information etc.
Data.
In an alternative embodiment, the evaluation data of evaluation object can actively be provided by being evaluated object, can also be passed through
Evaluation side is carrying out data collection after being evaluated Object Authorization.
In an alternative embodiment, the method for the evaluation result of objective appraisal object is obtained, comprising:
Indexing processing is carried out to the evaluation data of objective appraisal object, indexing processing refers to through polymerization, logic
Analysis, data calculate, and will evaluate at least a kind of process for being changed into index from data in data；
And according to processing result and default value strategy, the corresponding review number of evaluation data of objective appraisal object is determined
Value generates the corresponding evaluation result of evaluation data of objective appraisal object.
In an alternative embodiment, indexing processing is carried out to the evaluation data of objective appraisal object, comprising: according to evaluation pair
The evaluation data classification of elephant carries out indexing processing, and e.g., the evaluation data one type of evaluation object is punishment information, then right
The punishment quantity answered handles the achievement data that the punishment information obtains by way of polymerization.
In an alternative embodiment, value strategy is preset, refers to, converts achievement data to the process of index score value；Including
The value strategy of threshold interval data determines corresponding index score value that is, in the section of preset maximum value and predetermined minimum,
Such as in achievement data between 80 to 90, which is 2 points.
In an alternative embodiment, different classification is corresponded to according in objective appraisal subject evaluation data, at least one can be obtained
A figure of merit；The evaluation data for handling at least one figure of merit generation objective appraisal object according to default evaluation model are corresponding
Evaluation result, wherein default evaluation model is according at least one index value, according to specified algorithm/function building
At being used to indicate the corresponding evaluation result of evaluation data of objective appraisal object.For example, obtaining the review number of objective appraisal object
According to later, indexing processing be include A index, B index, three Xiang Zhibiao of C index, according to default value strategy, A, B, C tri- refer to
Marking corresponding index value is 3,3,2；According to preset model, i.e. corresponding relationship between achievement data and evaluation result,
Determine that the evaluation result of the objective appraisal object is good.
102, when evaluation result does not meet expectations result, according to evaluation baseline database, objective appraisal pair is determined
The difference data of elephant.
In an alternative embodiment, according to evaluation object credit appraisal database, the difference data of objective appraisal object is determined,
Include:
According to evaluation baseline database, the default corresponding default base-line data of evaluation result is determined；Evaluate base-line data packet
It includes, evaluates the hierarchical categories and graded index data of base-line data；
Default base-line data is parsed, by the gap between evaluation object credit appraisal data and default base-line data, really
Determine the corresponding target classification rank of evaluation result, and the target gap value and target of graded index data corresponding with category level
Gap item；
According to target classification rank and target gap value, the difference data of objective appraisal object is determined.
In an alternative embodiment, the method that category level corresponds to target gap value is determined, comprising:
According to credit appraisal database, determine that default evaluation result corresponds at least one default subclassification information；
According to evaluation baseline database, at least one corresponding default subbase line of at least one default subclassification information is determined
Data, including preset sub- hierarchical categories and preset sub- graded index data；
Evaluation result obtains at least one sub-goal gap value compared with presetting sub- base-line data successively, and generates target
Gap value, comprising: obtain the corresponding evaluation user data index of sub- hierarchical categories；Successively compare to preset and be preset under sub- hierarchical categories
The gap of sub- graded index data and evaluation user's achievement data.
In an alternative embodiment, the corresponding target classification rank of evaluation result, and classification corresponding with category level are determined
Implementation method of the goal discrepancy of achievement data away from item include:
Comparative evaluation result and default base-line data；When evaluation result is to reach the mean value of default base-line data, and
Target gap value below is the first gap item at the lower limit value of default base-line data and the half of mean value；And it successively determines
Gap item.
Specific example is enumerated herein to be illustrated, the evaluation result of objective appraisal object be it is good, objective appraisal object
Default evaluation result is outstanding；
According to default value strategy and evaluation baseline database, corresponding classification class when default evaluation result is outstanding is obtained
Not and graded index data: in this example, default evaluation result when being outstanding corresponding default subclassification information be first classify,
Graded index data include A index, B index, specifically, wherein the corresponding index value of A index is 4 achievement data threshold intervals
Between 80 to 90；The corresponding index value of B index is 5, and achievement data exists, between 90 to 100；
According to A index, B index in above-mentioned A index, the evaluation data of B index selection target user, specifically, wherein A
It is 75 that the corresponding index value of index, which is 3 achievement datas,；The corresponding index value of B index is 4, achievement data 85；
Therefore it is found that if evaluation object is want Evaluation: Current result being optimized for default evaluation knot from good after comparative analysis
When fruit is outstanding；It needs that A index is corresponded to achievement data and is optimized for preset 80 from current 75 in the case where first is classified；B index pair
Answering achievement data is that 85 currently are optimized for 90.
The data processing method based on evaluation result that the disclosure provides, it is default by obtaining evaluation baseline database acquisition
The corresponding default base-line data of evaluation result, and gap between Evaluation: Current result and default evaluation result is analyzed, the mesh of generation
The difference data for marking evaluation object, e.g., under hierarchical categories corresponds to the gap of graded index data；Specify that evaluation object optimizes plan
Slightly.
In an alternative embodiment, according to evaluation baseline database, the default corresponding default base-line data of evaluation result is determined,
Include:
Acquisition credit appraisal database, evaluation object credit appraisal database, including, the classification information of evaluation object is commented
The evaluation result of valence mumber evidence and evaluation object；
According to evaluation object credit appraisal database, after sorting out principle processing, affiliated same category of evaluation is obtained
Object and corresponding achievement data, and parameter data determine the corresponding index base-line data of classification, generate evaluation baseline number
According to library.
Sort out principle, including carrying out classification according to user preset classifying rules and carrying out according to the classification information of evaluation object
Classification.
In an alternative embodiment, according to evaluation object credit appraisal database, after sorting out principle processing, belonging to acquisition
Of a sort evaluation object and corresponding achievement data, and parameter data
In an alternative embodiment, the corresponding index base-line data of classification is determined, including, according to assessment grade and evaluation object
Further refinement index baseline generates for classification.Such as evaluation object is enterprise, we can set according to scope of the enterprise and divide at this time
Class, such as large-scale, medium-sized, small-sized, wherein setting medium-scale software industry private enterprise, rating level is BBB, the base of a certain index
The threshold interval of line number evidence includes: lower limit value, average value, upper limit value.If an evaluation index baseline and opinion rating, enterprise
Type is unrelated, be arranged such index be common index, not continue refine index baseline only set a general baseline.
In an alternative embodiment, the generation for evaluating baseline database includes by generating after big data cloud computing；By big
The index baseline that the mode of data cloud computing obtains can customize different index baselines based on different industries, so as to be use
Family provides more accurate data analysis result.
In an alternative embodiment, credit appraisal database is obtained, including；
Based on default value strategy, the corresponding subclassification information of classification information is determined；
The corresponding evaluation result of subclassification information is obtained, credit appraisal database is generated.
103, according to the difference data of objective appraisal object and evaluation data, objective optimization path policy is generated.
Path optimizing strategy refers to that the evaluation result of objective appraisal object meets the path optimizing plan of expectations result
Slightly.
In an alternative embodiment, according to the difference data of objective appraisal object and evaluation data, objective optimization path is generated
Strategy, including,
Default optimisation strategy is obtained, which refers to, carries out based on optimization time, difference data and weighted value
The strategy of sequence combination producing；
Based on the default optimisation strategy, at least one corresponding optimization plan of evaluation data fit expectations result is determined
Slightly；
Optimisation strategy, which is set, at least one according to the difference data grade determines objective optimization path policy.
In an alternative embodiment, default optimisation strategy includes that according to the optimization time be improvement period t, difference data is poor
It is influence degree away from item grade l and weighted value, is ranked up the strategy of combination producing；And the improvement period and gap etc. can be set
Grade is optimization item, determines path length, influence degree is weighted value, i.e. the premise of optimisation strategy, which is to ensure that, reaches optimization mesh
Mark may achieve client's expectation.
In an alternative embodiment, path optimizing does not optimize all indexs, find most suitable index into
Row emphasis optimization, therefore the disclosure uses ergodic algorithm, the principle of traversal be it is most short according to the improvement period, gap item grade is the
One, weight is higher is preferentially calculated, constantly progress permutation and combination.
In an alternative embodiment, it is determined that after optimizing index, optimizing index is reversely veritified to the data cases after index, according to
According to the promotion amplitude of index value, the credit data that analysis indexes are handled generates optimisation strategy, and according to optimisation strategy and use
Family credit data generates data analysis report.
The data processing method based on evaluation result that the embodiment of the present disclosure provides, passes through the existing credit of assay object
Evaluation result and the expected credit appraisal of evaluation object, according to evaluation baseline database, determine as a result, when the two result is inconsistent
The difference data of objective appraisal object；According to the difference data of objective appraisal object and evaluation data, objective optimization path is generated
Strategy.
The data processing method based on evaluation result that the embodiment of the present disclosure provides can guarantee that evaluation model is privately owned
Property, i.e., not in the case where assessed object Exposure Assessment model, the evaluation baseline database of Utilization assessment result constructs baseline, leads to
The evaluation information of analysis evaluation object and the gap data of expected results are crossed, optimisation strategy is generated, is evaluation object optimizing evaluation
As a result enforceable optimal way is provided, human cost is saved, improves the accuracy of evaluation data.
Embodiment two
Based on the data processing method based on evaluation result that the corresponding embodiment of above-mentioned Fig. 1 provides, another reality of the disclosure
It applies example and a kind of data processing system based on evaluation result is provided.Referring to shown in Fig. 2, data transmission system provided in this embodiment
20, comprising: data evaluation device 201, data analysis set-up 202, data storage device 203；
Data evaluation device 201, the evaluation result and expectations for obtaining objective appraisal object are as a result, the evaluation
The result is that generated based on evaluation data of the evaluation model to evaluation object；
When the evaluation result does not meet the expectations result, sends data analysis request to the data and analyze
Device.
In an alternative embodiment, the self-service analysis request of self-appraisal client is received；According to the data of request, to evaluation index base
Line database server-side extracts base-line data and carries out gap analysis；Path selection is optimized according to gap analysis result, and with
Evaluation score value calculates server-side and interacts, and verifies path viability, optimizes after generating path optimizing to self-appraisal client push
As a result.
Data analysis set-up 202, for according to the data analysis request, acquisition according to evaluation baseline database, really
The difference data of the fixed objective appraisal object；
According to the difference data of the objective appraisal object and the evaluation data, objective optimization path policy, institute are generated
Path optimizing strategy is stated, refers to that the evaluation result of the objective appraisal object meets the path optimizing plan of the expectations result
Slightly；
Data storage device 203, for storing evaluation baseline database and credit appraisal database.
User credit rating database, including, the classification information of evaluation object, evaluation data and the evaluation object are commented
Valence result；Baseline database is evaluated, after sorting out principle processing, is obtained affiliated same according to user credit rating database
A kind of other evaluation object and corresponding achievement data, and parameter data, determine the corresponding index base-line data of classification, raw
At evaluation baseline database.
In an alternative embodiment, data storage device 203, for storing credit appraisal basic data and evaluation index at different levels
Base-line data；The acquisition baseline database request of data analysis set-up 202 is received, and sends and comments to data analysis set-up 202
The corresponding base-line data of valence result.
As shown in figure 3, in an alternative embodiment, a kind of data processing system 20 based on evaluation result, further includes: data
Computing device 204,
Data computing device 204 is connected with the data evaluation device 201,
Data computing device 204 handles the evaluation data of the evaluation object for indexing, generates the objective appraisal
The corresponding evaluation result of evaluation data of object, and the evaluation result is sent to data evaluation device.
In an alternative embodiment, data computing device 204 is for receiving evaluation object in the credit appraisal of client typing
Data, and by after the processing of credit appraisal data targetization, indication information is generated, and start evaluation model and carry out score value or grade
It calculates.And result is sent to data evaluation device 201.
In an alternative embodiment, data computing device 204 for receiving data analytical equipment 202 send according to optimization plan
The simulated metrics information slightly generated carries out model calculating.And result is sent to data evaluation device 201.
The data processing system based on evaluation result that the embodiment of the present disclosure provides, passes through the existing credit of assay object
Evaluation result and the expected credit appraisal of evaluation object, according to evaluation baseline database, determine as a result, when the two result is inconsistent
The difference data of objective appraisal object；According to the difference data of the objective appraisal object and the evaluation data, target is generated
Path optimizing strategy.
Based on the data processing method based on evaluation result described in the corresponding embodiment of above-mentioned Fig. 1 and Fig. 2, this public affairs
It opens embodiment and a kind of computer readable storage medium is also provided, for example, non-transitorycomputer readable storage medium can be only
Read memory (English: Read Only Memory, ROM), random access memory (English: Random Access Memory,
RAM), CD-ROM, tape, floppy disk and optical data storage devices etc..It is stored with computer instruction on the storage medium, for executing
Data processing method based on evaluation result described in the corresponding embodiment of above-mentioned Fig. 1 and Fig. 2, details are not described herein again.
Those skilled in the art will readily occur to its of the disclosure after considering specification and practicing disclosure disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claim is pointed out.
Claims (10)
1. a kind of data processing method based on evaluation result, which is characterized in that the described method includes:
The evaluation result and expectations for obtaining objective appraisal object are as a result, the evaluation result is based on evaluation model to evaluation
The evaluation data of object generate；
When the evaluation result does not meet the expectations result, according to evaluation baseline database, determine that the target is commented
The difference data of valence object；
According to the difference data of the objective appraisal object and the evaluation data, objective optimization path policy is generated, it is described excellent
Change path policy, refers to that the evaluation result of the objective appraisal object meets the path optimizing strategy of the expectations result.
2. the method according to claim 1, wherein described in the evaluation result for obtaining objective appraisal object and pre-
Before phase evaluation result, further includes:
It obtains user's logon information and carries out authentication process；
After user's logon information passes through authentication process, the basic data and credit data of user are obtained；
According to the basic data and the credit data, the evaluation data of target user are generated.
3. the method according to claim 1, wherein the evaluation result for obtaining objective appraisal object, comprising:
Indexing processing is carried out to the evaluation data of the objective appraisal object, the indexing processing refers to by polymerizeing, patrolling
Analysis, data calculating are collected, at least a kind of process for being changed into index from data in data will be evaluated；
And according to the processing result and default value strategy, the corresponding evaluation of evaluation data of the objective appraisal object is determined
Numerical value generates the corresponding evaluation result of evaluation data of the objective appraisal object.
4. the method according to claim 1, wherein the difference data of the determination objective appraisal object,
Include:
According to the evaluation baseline database, the corresponding default base-line data of the default evaluation result is determined；The evaluation base
Line number evidence includes the hierarchical categories and graded index data for evaluating base-line data；
Parse the default base-line data, determine the corresponding target classification rank of the evaluation result, and with the classification stage
Not corresponding target gap value；
According to the target classification rank and the target gap value, the difference data of the objective appraisal object is determined.
5. according to the method described in claim 4, it is characterized in that, described according to the evaluation baseline database, determine described in
The default corresponding default base-line data of evaluation result, comprising:
Acquisition credit appraisal database, the user credit rating database, including, classification information, the review number of evaluation object
According to and the evaluation object evaluation result；
According to the user credit rating database, after sorting out principle processing, affiliated same category of evaluation object is obtained
And corresponding achievement data, and the achievement data is calculated, it determines the corresponding index base-line data of the classification, generates evaluation base
Line database.
6. according to the method described in claim 5, it is characterized in that, the acquisition credit appraisal database, comprising:
Based on the default value strategy, the corresponding subclassification information of the classification information is determined；
The corresponding evaluation result of the subclassification information is obtained, the credit appraisal database is generated.
7. according to the method described in claim 4, it is characterized in that, the corresponding target classification grade of the determination evaluation result
Not, and target gap value corresponding with the category level, comprising:
According to the credit appraisal database, determine that the default evaluation result corresponds at least one default subclassification information；
According to the evaluation baseline database, at least one corresponding default son of at least one described default subclassification information is determined
Base-line data；
The evaluation result with it is described preset sub- base-line data successively compared with, obtain at least one sub-goal gap value, and generate
Target gap value.
8. the method according to claim 1, wherein the difference data according to the objective appraisal object and
The evaluation data generate objective optimization path policy, including,
Default optimisation strategy is obtained, the default optimisation strategy refers to, is arranged based on optimization time, difference data and weighted value
The strategy of sequence combination producing；
Based on the default optimisation strategy, determining expectations result described in the evaluation data fit, corresponding at least one is excellent
Change strategy；
According to the difference data grade it is described at least one set optimisation strategy and determine objective optimization path policy.
9. a kind of data processing system based on evaluation result characterized by comprising data evaluation device, data analysis dress
It sets, data storage device；
The data evaluation device, the evaluation result and expectations for obtaining objective appraisal object are as a result, the evaluation is tied
Fruit is generated based on evaluation data of the evaluation model to evaluation object；
When the evaluation result does not meet the expectations result, sends data analysis request to the data and analyze dress
It sets；
The data analysis set-up, is used for, according to the data analysis request, acquisition according to evaluation baseline database, determine
The difference data of the objective appraisal object；
According to the difference data of the objective appraisal object and the evaluation data, objective optimization path policy is generated, it is described excellent
Change path policy, refers to that the evaluation result of the objective appraisal object meets the path optimizing strategy of the expectations result；
Data storage device, for storing evaluation baseline database.
10. system according to claim 9, which is characterized in that further include: data computing device,
The data computing device is connected with the data evaluation device,
The data computing device handles the evaluation data of the evaluation object for indexing, generates the objective appraisal pair
The corresponding evaluation result of evaluation data of elephant, and the evaluation result is sent to data evaluation device.
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