CN110348706A - Patent subsidizes method, apparatus, storage medium and processor - Google Patents
Patent subsidizes method, apparatus, storage medium and processor Download PDFInfo
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- CN110348706A CN110348706A CN201910557263.5A CN201910557263A CN110348706A CN 110348706 A CN110348706 A CN 110348706A CN 201910557263 A CN201910557263 A CN 201910557263A CN 110348706 A CN110348706 A CN 110348706A
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- 238000000034 method Methods 0.000 title claims abstract description 45
- 238000011156 evaluation Methods 0.000 claims abstract description 51
- 238000012549 training Methods 0.000 claims description 25
- 238000010801 machine learning Methods 0.000 claims description 5
- 230000008901 benefit Effects 0.000 claims description 4
- 238000005516 engineering process Methods 0.000 abstract description 10
- 238000013475 authorization Methods 0.000 description 10
- 230000008569 process Effects 0.000 description 8
- 238000011161 development Methods 0.000 description 5
- 241001269238 Data Species 0.000 description 3
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- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
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- 238000012552 review Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
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- 238000010586 diagram Methods 0.000 description 2
- 230000004069 differentiation Effects 0.000 description 2
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Abstract
The invention discloses a kind of patents to subsidize method, apparatus, storage medium and processor.Wherein, this method comprises: obtaining patent subsidizes the granted patent data for declaring object；According at least two assessment models, multiple point value of evaluation of granted patent data are predicted；Mean value according to multiple point value of evaluation is as a result, determine the corresponding subsidy rank of granted patent data；Based on rank is subsidized, the grubstake of granted patent data is generated.The present invention, which solves, carries out patent subsidy using single ration standard in the related technology, caused by the technical issues of can not embodying the attention and guidance to high value patent.
Description
Technical field
The present invention relates to patents to subsidize management domain, subsidizes method, apparatus in particular to a kind of patent, storage is situated between
Matter and processor.
Background technique
With the continuous improvement of various circles of society's creativity consciousness, intellectual property is increasingly taken seriously, each department, each correlation
Department also proposes a series of patent Project Subsidization Policies in succession.In the related art, the authorization subsidy of patent is all wrapped in subsidies at different levels
The project contained, various regions subsidy amount at different levels is also not quite similar, but is all made of equal mode and is subsidized, and such as every 5000
Member is subsidized by unified ration standard without exception regardless of patent value degree, and this method can not achieve differential money
It helps, the attention and guidance to high value patent can not be embodied.
For above-mentioned problem, currently no effective solution has been proposed.
Summary of the invention
The embodiment of the invention provides a kind of patents to subsidize method, apparatus, storage medium and processor, at least to solve phase
Patent subsidy is carried out using single ration standard in the technology of pass, caused by can not embody attention and guidance to high value patent
The technical issues of.
According to an aspect of an embodiment of the present invention, a kind of patent subsidy method is provided, comprising: obtain patent and subsidize Shen
Report the granted patent data of object；According at least two assessment models, multiple point value of evaluation of the granted patent data are predicted；
Mean value according to the multiple point value of evaluation is as a result, determine the corresponding subsidy rank of the granted patent data；Based on the money
Rank is helped, the grubstake of the granted patent data is generated.
Optionally, the granted patent data that object is declared in the subsidy of acquisition patent comprise determining that object is declared in patent subsidy
Applying type, wherein the applying type includes at least following one: enterprise, public institution, individual；Shen is subsidized according to patent
The applying type of object is reported, granted patent data corresponding with the applying type are matched.
Optionally, according at least two assessment models, predict the patent data multiple point value of evaluation include: will be described
Granted patent data are separately input into few two assessment models, export point value of evaluation by least two assessment models, wherein
Each described assessment models is to be obtained by machine learning training, the multiple groups training data using multiple groups training data
In every group of data include: granted patent data and the corresponding point value of evaluation of the granted patent data.
Optionally, granted patent data include patent content data, wherein the patent content data include it is following at least
One of: claim, specification, appearance patent image.
Optionally, according to the mean value of the multiple point value of evaluation as a result, determining the corresponding subsidy of the granted patent data
Rank includes: to obtain the default corresponding relationship subsidized between rank and score value section；Determine the mean value of the multiple point value of evaluation
As a result the score value section belonging to；According to the corresponding relationship, determine that score value section belonging to the mean value result is corresponding default
Subsidy rank is the corresponding subsidy rank of the granted patent data.
According to another aspect of an embodiment of the present invention, a kind of patent subsidy device is additionally provided, comprising: obtain module, use
The granted patent data for declaring object are subsidized in acquisition patent；Prediction module, for predicting institute according at least two assessment models
State multiple point value of evaluation of granted patent data；Determining module, for the mean value according to the multiple point value of evaluation as a result, determining
The corresponding subsidy rank of the granted patent data；Generation module generates the granted patent for being based on the subsidy rank
The grubstake of data.
Optionally, the prediction module includes: that the patent data is separately input into few two assessment models, by least
Two assessment models export point value of evaluation, wherein each described assessment models is to pass through machine using multiple groups training data
Device learning training show that every group of data in the multiple groups training data include: that granted patent data and the authorization are special
The corresponding point value of evaluation of sharp data.
Optionally, the determining module includes: acquiring unit, for obtaining default subsidize between rank and score value section
Corresponding relationship；First determination unit, for determining score value section belonging to the mean value result of the multiple point value of evaluation；Second really
Order member, for determining the corresponding default subsidy rank in score value section belonging to the mean value result according to the corresponding relationship
For the corresponding subsidy rank of the granted patent data.
According to another aspect of an embodiment of the present invention, a kind of storage medium is additionally provided, the storage medium includes storage
Program, wherein described program operation when control the storage medium where equipment execute it is any one of above-mentioned described in
Patent subsidizes method.
According to another aspect of an embodiment of the present invention, a kind of processor is additionally provided, the processor is used to run program,
Wherein, described program run when execute it is any one of above-mentioned described in patent subsidize method.
In embodiments of the present invention, the granted patent data for declaring object are subsidized using acquisition patent；According at least two
Assessment models predict multiple point value of evaluation of the granted patent data；Mean value according to the multiple point value of evaluation is as a result, really
Determine the corresponding subsidy rank of the granted patent data；Based on the subsidy rank, the subsidy of the granted patent data is generated
The mode of gold subsidizes patent the granted patent data forecast assessment score value for declaring object by multiple assessment models, thus really
Surely rank is subsidized, has achieved the purpose that be subsidized according to different subsidy ranks using different grubstakes, to realize
To the technical effect of the differential subsidy of granted patent, and then solves and carried out specially using single ration standard in the related technology
Benefit is subsidized, caused by the technical issues of can not embodying the attention and guidance to high value patent.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present invention, constitutes part of this application, this hair
Bright illustrative embodiments and their description are used to explain the present invention, and are not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the flow chart that patent according to an embodiment of the present invention subsidizes method；
Fig. 2 is the flow chart that patent according to the preferred embodiment of the invention subsidizes method；
Fig. 3 is the structural schematic diagram that patent according to an embodiment of the present invention subsidizes device.
Specific embodiment
In order to enable those skilled in the art to better understand the solution of the present invention, below in conjunction in the embodiment of the present invention
Attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is only
The embodiment of a part of the invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill people
The model that the present invention protects all should belong in member's every other embodiment obtained without making creative work
It encloses.
It should be noted that description and claims of this specification and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.
It should be understood that the data used in this way are interchangeable under appropriate circumstances, so as to implementation of the invention described herein
Example can be performed in other sequences than those illustrated or described herein.In addition, term " includes " and " having " and
Their any deformation, it is intended that cover it is non-exclusive include, for example, containing the process of a series of steps or units, side
Method, system, product or equipment those of are not necessarily limited to be clearly listed step or unit, but may include being not clearly listed
Or other step or units intrinsic for these process, methods, product or equipment.
According to embodiments of the present invention, a kind of embodiment of patent subsidy method is provided, it should be noted that in attached drawing
The step of process illustrates can execute in a computer system such as a set of computer executable instructions, although also,
Logical order is shown in flow chart, but in some cases, it can be to be different from shown by sequence execution herein or retouch
The step of stating.
Fig. 1 is the flow chart that patent according to an embodiment of the present invention subsidizes method, as shown in Figure 1, this method includes as follows
Step:
Step S102 obtains patent and subsidizes the granted patent data for declaring object；
Step S104 predicts multiple point value of evaluation of granted patent data according at least two assessment models；
Step S106, the mean value according to multiple point value of evaluation is as a result, determine the corresponding subsidy rank of granted patent data；
Step S108 generates the grubstake of granted patent data based on rank is subsidized.
Through the above steps, it may be implemented to subsidize patent by multiple assessment models the granted patent data for declaring object
Forecast assessment score value has been reached and has been provided according to different subsidy ranks using different grubstakes so that it is determined that subsidizing rank
The purpose helped to realize the technical effect of the differential subsidy to granted patent, and then is solved and is used in the related technology
Single ration standard carries out patent subsidy, caused by the technical issues of can not embodying the attention and guidance to high value patent.
It can basis when the granted patent data of object are declared in acquisition patent subsidy as a kind of optional embodiment
Patent subsidy declares object and obtains declaring the relevant granted patent data of object to this, wherein above-mentioned granted patent data can be with
It is obtained from Patent Publication library.It should be noted that object is declared in patent subsidy can be enterprise, public institution, a
People etc..And it is not unique for obtaining patent to subsidize the approach for the granted patent data for declaring object, for example, both can be from
It obtains, can also be obtained from special patent search website in its internal special patent management system, for example, Chinese knowledge produces
Power net CNIPR (China Intellctual Property Right, referred to as CNIPR) etc..In the specific implementation process,
It is not limited to above-mentioned institute's example way.
As a kind of optional embodiment, granted patent data may include: denomination of invention, abstract, claim, explanation
Book, Figure of description and other public informations etc., wherein other above-mentioned public informations can include but is not limited to application number,
The applying date, applicant and address, inventor, application publication number, data of publication of application etc..In addition, above-mentioned granted patent data
It is further divided into lteral data and image data.
It in order to ensure the accuracy of granted patent data assessment score value, and then is patent as a kind of optional embodiment
Differential subsidy provides effective judgment basis.In a preferred embodiment, it needs to realize prediction using multiple assessment models
Multiple point value of evaluation of granted patent data.Wherein, multiple assessment models can be designed using different algorithms, can also basis
Need to be arranged the weight etc. of different patent datas.
As a kind of optional embodiment, can according to multiple point value of evaluation mean value as a result, determining granted patent data
Corresponding subsidy rank, wherein different mean values is as a result, different subsidy ranks may be corresponded to.For example, 60-70 points of score value model
Enclosing corresponding subsidy rank is level Four, and 70-80 points of the corresponding subsidy rank of score range is three-level, 80-90 points of score value model
Enclosing corresponding subsidy rank is second level, and 90-100 points of the corresponding subsidy rank of score range is that level-one is being embodied certainly
In the process, it can determine score range according to application scenarios difference and subsidize the corresponding relationship of rank, thus in multiple assessments point
The mean value result of value falls into the corresponding subsidy rank of score range.For example, mean value result is 73.5,85,89, corresponding subsidy
Rank is respectively as follows: three-level, second level, second level.Furthermore it is possible to as needed by score range and one or more subsidy rank pair
It should get up, for example, mean value result can be more than or equal to 80 graduation be that can carry out the rank of great number subsidy, and less than 80 graduation
For the rank that can carry out low volume subsidy.No matter determined using which kind of form and subsidize rank, can realize what differentiation was subsidized
Purpose carries out indifference subsidy using unified specified standards compared to the relevant technologies, and this method is by drawing subsidy rank
Point, the attention and guiding function to high value patent can be played.
As a kind of optional embodiment, it is being based on subsidizing rank, in the grubstake for generating granted patent data, for not
Same subsidy rank, is subsidized using differentiation, so that corresponding grubstake is provided, it can be according to the actual bonus amount of money, institute possession
The many factors such as the level of economic development in area and the position in national development strategy, are subsidized.For example, government carries out
Photovoltaic industry, in order to stimulate the development of photovoltaic industry, corresponding grubstake can be more much higher than other industries of same rank.
Optionally, the granted patent data that object is declared in the subsidy of acquisition patent comprise determining that object is declared in patent subsidy
Applying type, wherein applying type includes at least following one: enterprise, public institution, individual；It is declared pair according to patent subsidy
The applying type of elephant matches granted patent data corresponding with applying type.
As a kind of optional embodiment, the applying type matching and this application class for declaring object can be subsidized according to patent
The corresponding granted patent data of type.Wherein, when applying type is enterprise, loom can be organized according to enterprise name, enterprise address
Structure code, date of application etc. obtain granted patent data corresponding with the enterprise；It, can be with when applying type is public institution
According to department belonging to the public institution, address, applicant's title etc. obtains granted patent number corresponding with the public institution
According to；It, can be according to name, home address, identification card number etc., acquisition authorization corresponding with the individual when applying type is personal
Patent data；In the specific implementation process, applying type can be divided according to different application scenarios, but this application type is simultaneously
It is not limited to above-mentioned illustrated content.
Optionally, according at least two assessment models, predict that multiple point value of evaluation of patent data include: by granted patent
Data are separately input into few two assessment models, export point value of evaluation by least two assessment models, wherein each assessment mould
Type is to be obtained by machine learning training, every group of data in multiple groups training data include: to award using multiple groups training data
Weigh patent data and the corresponding point value of evaluation of granted patent data.
It is commented when carrying out point value of evaluation to granted patent data using more than two as a kind of optional embodiment
Model is estimated to realize, wherein each assessment models can be obtained by the identical granted patent data of input by each mould
The point value of evaluation of type output, thus can be according to the corresponding multiple point value of evaluation of same granted patent data, to same authorization
The analysis of patent data progress multi-angle.
As a kind of optional embodiment, when being trained to multiple assessment models, for trained multiple groups training number
It is identical according to can be, it is also possible to different.It is, for example, possible to use based on patent legal state data, marketing data it is more
Group training data multiple assessment models are trained respectively, wherein training after each assessment models in can be by setting
The modes such as different weight proportions are set, for analyzing the corresponding point value of evaluation of granted patent data.Furthermore it is also possible to using using
Based on patent legal state data training one assessment models, based on marketing data training another assessment models, by this two
A assessment models based on different training datas realize the subsequent prediction to the corresponding point value of evaluation of granted patent data.Having
In body implementation process, it is not limited to above-mentioned illustrated embodiment.It should be noted that above-mentioned at least two assessment
Model can also be designed by multiple and different team, using exploitations such as different algorithms.
Optionally, granted patent data include patent content data, wherein the patent content data include it is following at least
One of: claim, specification, appearance patent image.
As a kind of optional embodiment, granted patent is assessed, actually to patent content data, example
Such as, the assessment of claim, specification, appearance patent image etc..Wherein it is possible to be carried out to above-mentioned patent content data crucial special
Levy extraction, semantic analysis etc..For example, the keyword in claim or specification, keyword can be extracted, can also mention
Characteristics of image, the keyword etc. in appearance patent image are taken, by the extraction to above-mentioned key feature, and carries out corresponding language
The processing such as justice analysis, can more accurately reflect the essentiality content of granted patent.
As a kind of optional embodiment, in order to guarantee the accuracy of assessment models prediction, after constructing assessment models, need
The model is trained, the data source of number of ways can be used to improve the predictive ability of assessment models, for example, enterprise
It may include title, address, applicant and the inventor's information etc. of enterprise in data, patent content data include license text
This claims, specification, appearance patent image etc., patent legal state may include apply, accept, first trial qualification,
Substantive examination, announcement, examination reports, authorization, lower card, invalid etc..As an optional embodiment, can be through CNIPR etc.
Obtaining patent data can also be obtained including published patent data, the patent data authorized etc. by information such as application numbers
Take granted patent data, such as applicant, authorization text and other relevant informations.In addition, above-mentioned granted patent data are also
It may include marketing data, review data, invalid data, intellectual property judicial decision data etc., these granted patent data can
With the complementary precision for improving assessment, preferably reflect the value of granted patent, this is no longer going to repeat them.
As a kind of optional embodiment, granted patent data can be business data, patent content data, patent law
Status data, marketing data, review data, invalid data, one in intellectual property judicial decision data, are also possible to multiple
The form combined, can be by above-mentioned granted patent data application in stages such as training, assessments, to ensure that granted patent number
According to content cover more various, in further detail, the standard of further evaluation score value can be improved from the value of multiple angle feed-back patents
True property.
Optionally, according to the mean value of multiple point value of evaluation as a result, determining that the corresponding subsidy rank of granted patent data includes:
Obtain the default corresponding relationship subsidized between rank and score value section；Determine score value belonging to the mean value result of multiple point value of evaluation
Section；According to corresponding relationship, determine that the corresponding default subsidy rank in score value section belonging to mean value result is granted patent data
Corresponding subsidy rank.
As a kind of optional embodiment, the corresponding relationship between above-mentioned subsidy rank and score value section is not unique, can
With flexible setting as needed, for example, 0 yuan can be set by the subsidy rank in 0 to 60 score value section, by 60 to 70 point
The subsidy rank in value section is set as 2000 yuan, sets 3000 yuan for the subsidy rank in 70 to 90 score value section, by 80 to
The subsidy rank in 90 score value section is set as 4000 yuan, and sets the subsidy rank in 90 to 100 score value section to
5000 yuan.It should be noted that boundary's point value between each section, such as: 60,70,80,90 etc., it can according to need setting
Affiliated score value section, and the corresponding subsidy rank in each score value section can be adjusted flexibly.In another example can will be less than 80 points
The subsidy rank in score value section be set as 0 yuan, the subsidy setting in will be greater than or equal to 80 and the score value section less than or equal to 100
It is 5000 yuan.In addition, one or more rank can be divided into about rank is subsidized, wherein subsidize rank and score value section it
Between corresponding relationship be one-to-one, that is, the corresponding score value section of a subsidys rank, multiple subsidy ranks correspondences
Multiple score value sections.By the above method, score value section belonging to the mean value result can be obtained according to mean value result, and then fast
Speed accurately obtains subsidy rank.
The preferred embodiment of the present invention is illustrated below.
Fig. 2 is the flow chart that patent according to the preferred embodiment of the invention subsidizes method, as shown in Fig. 2, the patent is subsidized
Method includes: that user's registration logs in, and patent data push receives, and subsidizes examination & approval, patent subsidizes automatic assessment and patent is subsidized
It provides.
The step in above-mentioned patent subsidy method is further illustrated below:
(1) it is logged in by user's registration, to be used to solve to be registered as when enterprise, public institution or individual declare patent
System user；
User is registered by terminal device, and the registration information of user will be stored in corresponding server, is being infused
It after volume is completed, can be logged in by user, password and identifying code etc., the user is system user at this time, can be by stepping on
Record is inquired, is added and delete operation.
(2) declarer is subsidized using disclosed patent data Auto-matching, the patent data of newest disclosure, authorization is pushed
To user name；
User can obtain patent relevant to the identity information of the user according to the identity information of user after logging in
Data, for example, it may be newest disclosed patent data, can also be the patent data of authorization, these patent datas be with
The user is relevant, and user at this time can be to subsidize declarer, wherein subsidize declarer include: enterprise, it is public institution, a
People etc..
(3) subsidy examination and approval document is automatically generated；
Preliminary classification can be carried out according to the statutory status type of patent data, for example, by the applying date, publication date, awarding
Quan etc. obtains which patent is in authorization, which patent is also in the application stage.For the patent of authorization, and has subsidy
The patent of qualification generates according to these patents and subsidizes examination and approval document.
(4) patent is assessed automatically, is determined and is subsidized rank；
Assessment prediction is carried out for one or more granted patent subsidized in examination and approval document, so that it is determined that each is authorized
The subsidy rank of patent.It should be noted that being assessed automatically before subsidizing dispensing apparatus granted patent, can use
It two sets or covers appraisal procedure more, and to automatic assessment is carried out to granted patent is realized based on big data, wherein is above-mentioned
Big data includes business data, patent data, patent legal state data, marketing data, review data, invalid data, knowledge
Property right judicial decision data etc..
(5) batch provides grubstake.
The higher granted patent of rank is subsidized, corresponding grubstake is also higher；The lower granted patent of rank is subsidized, it is corresponding
Grubstake it is relatively low.Wherein, for the standard of grubstake, no according to the level of economic development in each area, policy tendency etc.
Together, there is some difference for the same grubstake for subsidizing rank in different regions, and different for areal are subsidized between rank
It has differences, can more embody the attention and guidance to high value patent in this way, improve innovation ability.
Patent classification may be implemented by the above method not subsidize, break single quota sponsored mode, while can promote
Into technological progress, high value patent is expedited the emergence of.
It in above-mentioned specific implementation process, is illustrated using subsidizing object as enterprise, obtains the enterprise through a variety of ways
Patent information, including the patent that enterprise is in the patent in application stage and has authorized, since enterprise patent quantity is big, for having awarded
The patent application of power is subsidized, and batch processing is needed.It can be according to pre-set condition, such as application number, publication number, grant date
The information such as phase extract the patent authorized from a large amount of patents, have further been authorized according to default subsidy condition from these special
The patent for meeting subsidy condition is filtered out in benefit, is generated and is subsidized examination and approval document.To in the patent in above-mentioned subsidy examination and approval document one by one into
Row assessment, obtains point value of evaluation.Here realize that assessment to patent, can be with for same patent using at least two appraisal procedures
Obtain two and more than two point value of evaluation.Further, subsidize using the point value of evaluation determination of grade.In order to protect
Card subsidizes the reliability and accuracy of grade, can be to multiple point value of evaluation averageds of above-mentioned same patent, this is average
Value can more reflect the subsidy grade of same patent, to match different grubstakes according to determining subsidy ranking score.For example, will money
Helping grade classification is first, second, the third three-level, wherein the patent grubstake of first class is 5000 yuan, and the patent grubstake of second class is 3000
Member, the patent grubstake of third class are 1000 yuan etc., and specific patent subsidizes the matching of grade and grubstake, according to practical application field
Scape determines, it is not limited to above-mentioned illustrated content.
It should be noted that there are certain journeys for the grubstake of the same subsidy rank of different regions in above embodiment
The difference of degree.For example, economically developed District of Shanghai, the money of the same subsidy rank of relatively backward Xinjiang region than economy
Help Jin Yaogao.In addition, for the high technology industry that state key is fostered, according to the tendentiousness of national policy, compared to traditional production
Industry, the same grubstake for subsidizing rank are also different.
This method subsidized according to different patent using classification, compared to traditional single quota sponsored mode,
It is better able to reflect the attention degree to high value patent, promotes the technological progress of society, such sponsored mode can be into one
Step promotes the generation of high value patent, all has certain facilitation for entire society's development.
Fig. 3 is the structural schematic diagram that patent according to an embodiment of the present invention subsidizes device, as shown in figure 3, the patent is subsidized
Device includes: to obtain module 32, prediction module 34, determining module 36 and generation module 38.Below to the patent subsidize device into
Row is described in detail.
Module 32 is obtained, the granted patent data of object are declared for obtaining patent subsidy；Prediction module 34, is connected to
It states and obtains module 32, for predicting multiple point value of evaluation of granted patent data according at least two assessment models；Determining module
36, it is connected to above-mentioned prediction module 34, for the mean value according to multiple point value of evaluation as a result, determining that granted patent data are corresponding
Subsidize rank；Generation module 38 is connected to above-mentioned determining module 36, for generating granted patent data based on rank is subsidized
Grubstake.
Through the foregoing embodiment, it may be implemented to subsidize patent by multiple assessment models the granted patent number for declaring object
It is predicted that point value of evaluation has been reached and has been carried out according to different subsidy ranks using different grubstakes so that it is determined that subsidizing rank
The purpose of subsidy to realize the technical effect of the differential subsidy to granted patent, and then is solved and is adopted in the related technology
Carry out patent subsidy with single ration standard, caused by can not embody the technology of attention and guidance to high value patent and ask
Topic.
Optionally, prediction module includes: that patent data is separately input into few two assessment models, by least two assessments
Model exports point value of evaluation, wherein each assessment models is to be obtained using multiple groups training data by machine learning training
, every group of data in multiple groups training data include: granted patent data and the corresponding point value of evaluation of granted patent data.
Optionally it is determined that module includes: acquiring unit, it is corresponding between default subsidy rank and score value section for obtaining
Relationship；First determination unit, for determining score value section belonging to the mean value result of multiple point value of evaluation；Second determination unit,
For according to corresponding relationship, determining that the corresponding default subsidy rank in score value section belonging to mean value result is granted patent data pair
The subsidy rank answered.
According to another aspect of an embodiment of the present invention, a kind of storage medium is additionally provided, storage medium includes the journey of storage
Sequence, wherein equipment where control storage medium executes any one of above-mentioned patent and subsidizes method in program operation.
According to another aspect of an embodiment of the present invention, a kind of processor is additionally provided, processor is used to run program,
In, program executes any one of above-mentioned patent and subsidizes method when running.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
In the above embodiment of the invention, it all emphasizes particularly on different fields to the description of each embodiment, does not have in some embodiment
The part of detailed description, reference can be made to the related descriptions of other embodiments.
In several embodiments provided herein, it should be understood that disclosed technology contents can pass through others
Mode is realized.Wherein, the apparatus embodiments described above are merely exemplary, such as the division of the unit, Ke Yiwei
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored or not executed.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be through some interfaces, the INDIRECT COUPLING or communication link of unit or module
It connects, can be electrical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
On unit.It can some or all of the units may be selected to achieve the purpose of the solution of this embodiment according to the actual needs.
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 for personal computer, server or network equipment etc.) execute each embodiment the method for the present invention whole or
Part steps.And storage medium above-mentioned includes: that USB flash disk, read-only memory (ROM, Read-Only Memory), arbitrary access are deposited
Reservoir (RAM, Random Access Memory), mobile hard disk, magnetic or disk etc. be various to can store program code
Medium.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications are also answered
It is considered as protection scope of the present invention.
Claims (10)
1. a kind of patent subsidizes method characterized by comprising
It obtains patent and subsidizes the granted patent data for declaring object；
According at least two assessment models, multiple point value of evaluation of the granted patent data are predicted；
Mean value according to the multiple point value of evaluation is as a result, determine the corresponding subsidy rank of the granted patent data；
Based on the subsidy rank, the grubstake of the granted patent data is generated.
2. the method according to claim 1, wherein obtaining patent subsidizes the granted patent data packet for declaring object
It includes:
Determine that patent subsidizes the applying type for declaring object, wherein the applying type includes at least following one: enterprise, thing
Industry unit, individual；
The applying type for declaring object is subsidized according to patent, matches granted patent data corresponding with the applying type.
3. the method according to claim 1, wherein predicting the patent number according at least two assessment models
According to multiple point value of evaluation include:
The granted patent data are separately input into few two assessment models, by at least two assessment models output assessments
Score value, wherein each described assessment models is to be obtained using multiple groups training data by machine learning training, described more
Every group of data in group training data include: granted patent data and the corresponding point value of evaluation of the granted patent data.
4. according to the method described in claim 3, it is characterized in that, granted patent data include patent content data, wherein institute
Stating patent content data includes at least one of: claim, specification, appearance patent image.
5. the method according to claim 1, wherein the mean value according to the multiple point value of evaluation is as a result, determine
The corresponding subsidy rank of the granted patent data includes:
Obtain the default corresponding relationship subsidized between rank and score value section；
Determine score value section belonging to the mean value result of the multiple point value of evaluation；
According to the corresponding relationship, determine that the corresponding default subsidy rank in score value section belonging to the mean value result is described awards
Weigh the corresponding subsidy rank of patent data.
6. a kind of patent subsidizes device characterized by comprising
Module is obtained, the granted patent data of object are declared for obtaining patent subsidy；
Prediction module, for predicting multiple point value of evaluation of the granted patent data according at least two assessment models；
Determining module, for the mean value according to the multiple point value of evaluation as a result, determining the corresponding money of the granted patent data
Help rank；
Generation module generates the grubstake of the granted patent data for being based on the subsidy rank.
7. device according to claim 6, which is characterized in that the prediction module includes:
The patent data is separately input into few two assessment models, by at least two assessment models output assessments point
Value, wherein each described assessment models is to be obtained by machine learning training, the multiple groups using multiple groups training data
Every group of data in training data include: granted patent data and the corresponding point value of evaluation of the granted patent data.
8. device according to claim 6, which is characterized in that the determining module includes:
Acquiring unit, for obtaining the default corresponding relationship subsidized between rank and score value section；
First determination unit, for determining score value section belonging to the mean value result of the multiple point value of evaluation；
Second determination unit, for determining that score value section belonging to the mean value result is corresponding pre- according to the corresponding relationship
If subsidy rank is the corresponding subsidy rank of the granted patent data.
9. a kind of storage medium, which is characterized in that the storage medium includes the program of storage, wherein run in described program
When control the storage medium where equipment perform claim require any one of 1 to 5 described in patent subsidize method.
10. a kind of processor, which is characterized in that the processor is for running program, wherein right of execution when described program is run
Benefit require any one of 1 to 5 described in patent subsidize method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910557263.5A CN110348706A (en) | 2019-06-25 | 2019-06-25 | Patent subsidizes method, apparatus, storage medium and processor |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910557263.5A CN110348706A (en) | 2019-06-25 | 2019-06-25 | Patent subsidizes method, apparatus, storage medium and processor |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110348706A true CN110348706A (en) | 2019-10-18 |
Family
ID=68183039
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910557263.5A Withdrawn CN110348706A (en) | 2019-06-25 | 2019-06-25 | Patent subsidizes method, apparatus, storage medium and processor |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110348706A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113191870A (en) * | 2021-01-19 | 2021-07-30 | 迅鳐成都科技有限公司 | Intellectual property value evaluation method and system based on block chain |
| CN114092035A (en) * | 2021-10-29 | 2022-02-25 | 珠海大横琴科技发展有限公司 | Data processing method and device based on enterprise service system |
-
2019
- 2019-06-25 CN CN201910557263.5A patent/CN110348706A/en not_active Withdrawn
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113191870A (en) * | 2021-01-19 | 2021-07-30 | 迅鳐成都科技有限公司 | Intellectual property value evaluation method and system based on block chain |
| CN113191870B (en) * | 2021-01-19 | 2023-08-08 | 迅鳐成都科技有限公司 | Intellectual property value evaluation method and system based on blockchain |
| CN114092035A (en) * | 2021-10-29 | 2022-02-25 | 珠海大横琴科技发展有限公司 | Data processing method and device based on enterprise service system |
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