CN109377104A - Data processing method, device, medium and electronic equipment - Google Patents
Data processing method, device, medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the invention provides a kind of data processing method, device, medium and electronic equipment, which includes: to obtain current knowledge property information and determine its target category；Obtain each historical knowledge property information of the target category；Obtain the object matching degree of the current knowledge property information and the target histories intellectual property information in each historical knowledge property information of the target category；The target risk grade of the current knowledge property information is assessed according to the object matching degree.The technical solution of the embodiment of the present invention can be realized the target risk grade of automatic Prediction current knowledge property information, so as to be given warning in advance according to its target risk grade.
Description
Technical field
The present invention relates to technical field of data processing, in particular to a kind of data processing method, device, medium and
Electronic equipment.
Background technique
With making rapid progress for science and technology, Innovation Main Body increasingly payes attention to the protection of all kinds of intellectual property equity, mostly
Innovation Main Body can all possess all kinds of intellectual properties such as patent, trade mark, Copyright in Computer Software, and any kind intellectual property is all wrapped
Include mass data, when enterprise carry out various product research and development or it is publicly traded when, be difficult to know whether oneself can invade others
Intellectual property, thus to enterprise's research and development of new product and publication bring very big legal risk.
It should be noted that information is only used for reinforcing the reason to background of the invention disclosed in above-mentioned background technology part
Solution, therefore may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
The embodiment of the present invention is designed to provide a kind of data processing method, device, medium and electronic equipment, Jin Erzhi
Overcoming the problems, such as to a certain extent less in the related technology can not automatic Prediction Intellectual Property Risk.
Other characteristics and advantages of the invention will be apparent from by the following detailed description, or partially by the present invention
Practice and acquistion.
According to one aspect of the disclosure, a kind of data processing method is provided, comprising: obtain current knowledge property information simultaneously
Determine its target category；Obtain each historical knowledge property information of the target category；Obtain the current knowledge property information
With the object matching degree of the target histories intellectual property information in each historical knowledge property information of the target category；According to institute
State the target risk grade that object matching degree assesses the current knowledge property information.
In a kind of exemplary embodiment of the disclosure, the method also includes: by each historical knowledge property right of all categories
Information is stored into block chain；If the current knowledge property information is stored into the block chain, it is such as above-mentioned to trigger execution
Step in embodiment.
In a kind of exemplary embodiment of the disclosure, the current knowledge property information and the target category are obtained
The object matching degree of target histories intellectual property information in each historical knowledge property information, comprising: the machine completed using training
Device learning model estimates the matching degree of each historical knowledge property information of the current knowledge property information and the target category；
It selects the maximum value in each matching degree as the object matching degree, and determines the corresponding historical knowledge property right letter of the maximum value
Breath is the target histories intellectual property information.
In a kind of exemplary embodiment of the disclosure, the current knowledge property right is assessed according to the object matching degree and is believed
The target risk grade of breath, comprising: the target risk value of the current knowledge property information is obtained according to the object matching degree；
If the target risk value is greater than risk threshold value, determine that the target risk grade is the first risk class；If the target
Value-at-risk is less than or equal to the risk threshold value, then determines that the target risk grade is the second risk class.
In a kind of exemplary embodiment of the disclosure, the method also includes: if at the current knowledge property information
In first risk class, then sends warning information and stored into block chain.
In a kind of exemplary embodiment of the disclosure, the current knowledge property right is obtained according to the object matching degree and is believed
The target risk value of breath, comprising: if the object matching degree is greater than matching degree threshold value, is calculated and obtained using the first predetermined manner
The target risk value of the current knowledge property information；If the object matching degree is less than or equal to the matching degree threshold value, adopt
The target risk value for obtaining the current knowledge property information is calculated with the second predetermined manner.
In a kind of exemplary embodiment of the disclosure, the method also includes: extract each historical knowledge production of all categories
Weigh the feature vector of information；According to the feature vector of each historical knowledge property information of all categories and utilize support vector machines mould
Each historical knowledge property information is divided into predetermined quantity classification by type；Wherein, the target category is the predetermined quantity classification
At least one of.
According to one aspect of the disclosure, a kind of data processing equipment is provided, comprising: target category obtains module, is used for
It obtains current knowledge property information and determines its target category；Historical data obtains module, for obtaining the target category
Each historical knowledge property information；Object matching degree obtains module, for obtaining the current knowledge property information and the target
The object matching degree of target histories intellectual property information in each historical knowledge property information of classification；The assessment of target risk grade
Module, for assessing the target risk grade of the current knowledge property information according to the object matching degree.
According to one aspect of the disclosure, a kind of computer-readable medium is provided, computer program is stored thereon with, it is described
Data processing method described in any of the above-described embodiment is realized when program is executed by processor.
According to one aspect of the disclosure, a kind of electronic equipment is provided, comprising: one or more processors；Storage device,
For storing one or more programs, when one or more of programs are executed by one or more of processors, so that
One or more of processors realize data processing method described in any of the above-described embodiment.
Technical solution provided in an embodiment of the present invention can include the following benefits:
In the technical solution provided by some embodiments of the present invention, by obtaining current knowledge property information and its mesh
Mark the object matching degree of the object knowledge property information in each historical knowledge property information under classification, and target described further
The object matching degree of intellectual property information assesses the target risk grade of the current knowledge property information, so as to by institute
Technical solution is stated to be applied to judge the current knowledge property information with the presence or absence of the wind for invading the object knowledge property information
Danger, and can be when determining that the current knowledge property information has the risk for invading the object knowledge property information, in advance
Issue warning information.
In the technical solution provided by other embodiments of the invention, pass through each historical knowledge property right under of all categories
Information is stored in advance into block chain, and when new current knowledge property information is added in the block chain, triggering is executed and commented
Estimate the risk class of existing historical knowledge property information in the current knowledge property information and block chain, and described in the judgement
When current knowledge property information is in high-risk grade, warning information is uploaded into the block chain, on the one hand, pass through block chain
Stored knowledge property information ensure that the safety of the data of storage the features such as can have secret protection, can be traced, is anti-tamper
Property and reliability；On the other hand, it can use block chain technology and realize the open permission of the graduation of data, there is corresponding permission
Personnel just can be carried out corresponding operation, such as check data, modification data, delete data etc. and be required to obtain and award accordingly
Power.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
It can the limitation present invention.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows and meets implementation of the invention
Example, and be used to explain the principle of the present invention together with specification.It should be evident that the accompanying drawings in the following description is only the present invention
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.In the accompanying drawings:
Fig. 1 diagrammatically illustrates the flow chart of data processing method according to an embodiment of the invention；
Fig. 2 diagrammatically illustrates the flow chart of one embodiment of the step S130 in Fig. 1；
Fig. 3 diagrammatically illustrates the flow chart of one embodiment of the step S140 in Fig. 1；
Fig. 4 diagrammatically illustrates the flow chart of data processing method according to another embodiment of the invention；
Fig. 5 diagrammatically illustrates the block diagram of data processing equipment according to an embodiment of the invention；
Fig. 6 shows the structural schematic diagram for being suitable for the computer system for the electronic equipment for being used to realize the embodiment of the present invention.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, thesing embodiments are provided so that the present invention will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.
In addition, described feature, structure or characteristic can be incorporated in one or more implementations in any suitable manner
In example.In the following description, many details are provided to provide and fully understand to the embodiment of the present invention.However,
It will be appreciated by persons skilled in the art that technical solution of the present invention can be practiced without one or more in specific detail,
Or it can be using other methods, constituent element, device, step etc..In other cases, it is not shown in detail or describes known side
Method, device, realization or operation are to avoid fuzzy each aspect of the present invention.
Block diagram shown in the drawings is only functional entity, not necessarily must be corresponding with physically separate entity.
I.e., it is possible to realize these functional entitys using software form, or realized in one or more hardware modules or integrated circuit
These functional entitys, or these functional entitys are realized in heterogeneous networks and/or processor device and/or microcontroller device.
Flow chart shown in the drawings is merely illustrative, it is not necessary to including all content and operation/step,
It is not required to execute by described sequence.For example, some operation/steps can also decompose, and some operation/steps can close
And or part merge, therefore the sequence actually executed is possible to change according to the actual situation.
Block chain (Blockchain) is that Distributed Storage, point-to-point transmission, common recognition mechanism, Encryption Algorithm etc. calculate
The new application mode of machine technology.So-called common recognition mechanism is to realize to establish between different nodes in block catenary system trust, obtain
The mathematical algorithm of equity.
Block chain is substantially the database of a decentralization.Block chain is a string of use cryptography method correlation coproduction
Raw data block contains the information of a bit coin network trading in each data block, for verifying the effective of its information
Property (anti-fake) and generate next block.
For narrow sense, block chain is a kind of be sequentially in time combined into data block in such a way that sequence is connected one
Kind linked data structure, and the distributed account book that can not be distorted He can not forge guaranteed in a manner of cryptography.
Broadly, block chain technology is to verify to save with storing data, using distribution using block linked data structure
Point common recognition algorithm come generate and more new data, guarantee in the way of cryptography data transmission and access safety, using by from
The intelligent contract of dynamicization scripted code composition programs and the completely new distributed basis framework of one kind of operation data and calculating side
Formula.
It is, in general, that block catenary system is made of data Layer, network layer, common recognition layer, excitation layer, contract layer and application layer.
Wherein, data Layer encapsulates bottom data block and the basic datas such as relevant data encryption and timestamp and rudimentary algorithm；
Network layer then includes distributed networking mechanism, data dissemination mechanism and data authentication mechanism etc.；Common recognition layer predominant package network section
All kinds of common recognition algorithms of point；Economic factor is integrated into block chain technical system by excitation layer, and main includes economic incentives
Issuing mechanism and distribution mechanism etc.；All kinds of scripts of contract layer predominant package, algorithm and intelligent contract, are block chain programmable features
Basis；Application layer then encapsulates the various application scenarios and case of block chain.In the model, the chain type block based on timestamp
Structure, the common recognition mechanism of distributed node, the intelligent contract based on the know together economic incentives and flexible programmable of calculating power are blocks
The most representative innovative point of chain technology.
A kind of data processing method that the embodiment of the present invention proposes, can effectively realize intellectual property in block chain network
Monitoring and tracing management.The Hash calculation and add that its chain transaction data structure that can use block chain Hash pointer and encryption are learned
It is close learn digital signature mechanism, realize process of exchange in multi-level evidence approval, thus come realize Different Individual counterparty it
Between trust problem.Meanwhile using block chain stored knowledge property information, there can also be secret protection, can be traced and prevent usurping
The features such as changing.
Fig. 1 diagrammatically illustrates the flow chart of data processing method according to an embodiment of the invention, at the data
The executing subject of reason method can be the equipment with calculation processing function, such as server and/or mobile terminal.
As shown in Figure 1, the data processing method that embodiment of the present invention provides may comprise steps of.
In step s 110, it obtains current knowledge property information and determines its target category.
In the embodiment of the present invention, intellectual property is the concept of a broad sense, such as the current knowledge property information can be with
Including newly research and develop or newly the product issued perhaps the information on services product or information on services for example may include product or
Person's service name, product or service function or effect, production process flow, product form structure etc. and the new product or
Person services relevant any information.For another example the current knowledge property information also may include new research and development or newly issue
The information such as product or the relevant patent of service, trade mark, Copyright in Computer Software.This is not limited by the present invention.
In the embodiment of the present invention, intellectual property information can be classified in advance, classification may include following two side
Face, in a first aspect, patent (can further be subdivided into invention, utility model, design three classes again), quotient can be classified as
These classifications such as mark, Copyright in Computer Software.Second aspect can further be led according to technology in this classification of patent
The difference in domain can also be segmented are as follows: electric consumers technological invention patent, Information and Communication Technology patent of invention, e-commerce
The classifications such as technological invention patent, high-end manufacturing technology patent of invention, chip technology patent of invention.Wherein, the target category can
It can also only include one of which to include above two classification.
In the step s 120, each historical knowledge property information of the target category is obtained.
In the embodiment of the present invention, each historical knowledge property information of all categories can be stored into block chain in advance.When
When the current knowledge property information is stored into the block chain, it can trigger and execute above-mentioned steps S110, i.e., from the area
The current knowledge property information is collected in block chain, it is first determined the target category of the current knowledge property information, then
Each historical knowledge property information under the target category is extracted from the block chain again.
For example, if the current knowledge property information is determined as patent and is Information and Communication Technology patent of invention, by institute
The Information and Communication Technology patent of invention stored in block chain is stated to extract.
In step s 130, each historical knowledge property right for obtaining the current knowledge property information and the target category is believed
The object matching degree of target histories intellectual property information in breath.
In the embodiment of the present invention, the current knowledge property information and respectively going through under the target category can be calculated first
The matching degree of history intellectual property information, wherein the target histories intellectual property information can be one or more.When described
When target histories intellectual property information is one, the maximum value in each matching degree that above-mentioned calculating can be taken to obtain is as the mesh
Matching degree is marked, the historical knowledge property information of the corresponding maximum value is as the target histories intellectual property information.When described
When target histories intellectual property information is multiple, (certainly, each matching degree that above-mentioned calculating obtains can be subjected to descending sort
Can carry out ascending sort), m (m is the positive integer more than or equal to 2) a maximum matching degree is as the object matching before selecting
Degree, or Mathematical treatment can also be carried out to preceding m maximum matching degrees and for example ask arithmetic mean of instantaneous value as the object matching
Degree, this is not limited by the present invention.
In step S140, the target risk etc. of the current knowledge property information is assessed according to the object matching degree
Grade.
In the embodiment of the present invention, the method can also include: by each historical knowledge property information of all categories store to
In block chain；If the current knowledge property information is stored into the block chain, the step S110 executed as shown in figure 1 is triggered
To S140.
In the embodiment of the present invention, the method can also include the construction step of block chain node and block chain network, use
In building, update and the maintenance of being responsible for block chain node and block chain network.For example, can be with some branch's machine of certain group
Structure is minimum node, block chain network that one or more large size groups/companies' participation intellectual property monitors and tracing management is traded
Building.
In the embodiment of the present invention, the method can also include pre-defining information storage and authentification of message data format,
The data structure mode, information storage means and the agreement that define according to the embodiment of the present invention stores and authenticates shared information
Deng to guarantee the high efficiency of information storage and information processing.
For example, the monitoring of intellectual property and the input of tracing management Transaction Information can be enterprise or individual authorized
The advertising of the intellectual property informations such as patent, copyright and enterprise or individual, product publication and a surname lead the information such as activity and
The public-key cryptography of related personnel and signature, it is related to tracing management information that the output of a transaction can be intellectual property monitoring
Storage links, the risk of the possible piracy of intellectual property rights of system automatic identification and the mentioning to relevant departments' sending of voucher material
Awake, public-key cryptography (account address) of relevant information visitor etc..One specific example is described in table 1 below:
Table 1
In above-mentioned table 1, the intellectual property transaction can specifically include the authorization of intellectual property, transfer, pay, make
With, reference, maintenance etc. transactions.
In the embodiment of the present invention, the enterprise or individual registered in systems can be by knowledge such as the patent of authorization, copyrights
The advertising of property information and enterprise or individual, product publication and a surname lead the information such as activity and upload to block chain, can help
The picture concerned or video etc. for further confirming that relevant knowledge property right or related publication or propaganda activity can also upload to block
Chain.
For example, certain mobile phone manufacturing company A application and 5G communication the relevant technologies patent of invention is obtained, for this journey
For, can generate a new block in block catenary system, the input of block may is that patent essential information patent name=
Xxx5G communication technology patent, the patent No.=12345, enterprise name=xx mobile phone manufacturing company, authorization date=
20180801 ... }, other information { advertising of enterprise or the personal patent information authorized, enterprise or individual, product hair
Cloth and a surname lead the information such as activity ... } and storage links=Kdkd49kdkkdkdkkdatcgmpq, related personnel public-key cryptography
=ATCGWKY123YTU, signature=XXXY, etc..The output of one transaction can be intellectual property monitoring and tracing management information
Storage links=ostfmmqqjjwwttyuyt of associated documents material, system automatic identification possible piracy of intellectual property rights
Risk and the public-key cryptography (account of prompting=low-risk/high risk, relevant information visitor that is issued to relevant departments
Location)=1392929293346 etc..
Wherein, all records in block chain can open different groups/company's graduation, and block chain is made full use of to believe
Breath secret protection (access authority limitation, picture or video with watermark etc.) can be traced, be not easy the characteristics of distorting, sharp to greatest extent
Intellectual property is monitored with historical information and tracing management, and the risk of the possible piracy of intellectual property rights of automatic identification is simultaneously
The prompting issued to relevant departments.
It should be noted that above-mentioned enterprise or the personal patent information authorized are mainly the testimonial material of license,
The advertising of authorized enterprise or individual, product publication, a surname lead the information such as activity must with license range, etc.
Grade, licensing term etc. are consistent.
In the embodiment of the present invention, the relevant departments for receiving warning information be can be at patent relevant departments of various countries or correlation
The district court for managing intellectual property case, is also possible to the Intellectual Property Department or legal department of enterprise, the present invention to this not
It limits.
The data processing method that embodiment of the present invention provides, by obtaining current knowledge property information and its target category
Under each historical knowledge property information in object knowledge property information object matching degree, and object knowledge described further produce
The object matching degree of information is weighed to assess the target risk grade of the current knowledge property information, so as to by the technology
Scheme is applied to judge that the current knowledge property information whether there is the risk for invading the object knowledge property information, and can
To issue early warning in advance when determining that the current knowledge property information has the risk for invading the object knowledge property information
Information.
On the other hand, the data processing method that embodiment of the present invention provides, can also by historical knowledge property information and
Current knowledge property information is stored into block chain, and is receiving current knowledge property information, and it is current that triggering executes judgement
Intellectual property information is determining exist with the presence or absence of the risk for invading historical knowledge property information stored in block chain
When risk in time to relevant departments issue remind, so as to effectively promote block chain technical application intellectual property monitor and with
Track management aspect.As block chain technology monitors and tracing management, medical treatment endowment and treasury management services' management, guarantor in intellectual property
The extensive use of the multiple fields such as danger, finance, logistics, the program will bring considerable economic benefit and social benefit.
Fig. 2 diagrammatically illustrates the flow chart of one embodiment of the step S130 in Fig. 1.
As shown in Fig. 2, above-mentioned steps S130 may further include following steps in the embodiment of the present invention.
In step S131, using training complete machine learning model estimate the current knowledge property information with it is described
The matching degree of each historical knowledge property information of target category.
In the embodiment of the present invention, historical knowledge property information one machine of training stored in block chain can be advanced with
Learning model, the trained machine learning model can be used for exporting the current knowledge property information and the target category
Each historical knowledge property information matching degree.
In some embodiments, the machine learning model can be convolutional neural networks (Convolutional
Neural Networks, CNN), it can be used for calculating the matching degree of the intellectual property information of image type, such as design.
In further embodiments, the machine learning model can be recurrent neural network (Recurrent Neural Network,
RNN), it can be used for calculating the matching degree of the intellectual property information of literal type, such as patent of invention or utility model patent.
The present invention is not construed as limiting the specific algorithm of machine learning model.
In step S132, select the maximum value in each matching degree as the object matching degree, and determine the maximum
Being worth corresponding historical knowledge property information is the target histories intellectual property information.
For example, being calculated and the n-th class if current knowledge property information belongs to the n-th classification in the N number of classification divided in advance
The matching degree of all K historical knowledge property informations in not is respectively { P1, P2 ... PK }, then the object matching degree can be with
For P=max { P1, P2 ..., PK }.But the present invention is not limited to this, also can choose the multiple of foremost after descending sort
Matching degree is used as object matching degree.
Fig. 3 diagrammatically illustrates the flow chart of one embodiment of the step S140 in Fig. 1.
As shown in figure 3, above-mentioned steps S140 may further include following steps in the embodiment of the present invention.
In step s 141, the target risk value of the current knowledge property information is obtained according to the object matching degree.
In the exemplary embodiment, the target risk of the current knowledge property information is obtained according to the object matching degree
It is described current to calculate acquisition using the first predetermined manner if may include: that the object matching degree is greater than matching degree threshold value for value
The target risk value of intellectual property information；It is pre- using second if the object matching degree is less than or equal to the matching degree threshold value
If mode calculates the target risk value for obtaining the current knowledge property information.
For example, it is assumed that the object matching degree is P, then the current knowledge property right letter can be calculated according to the following formula
The target risk value Y of breath:
In above-mentioned formula, a, b, c is preset constant parameter, for example, a value can be the value of 90, b can be with
It is that the value of 80, c can be 10, but these values are only used for for example, the present invention is not limited to this, it can be according to specific
Application scenarios carry out from main modulation.
It should be noted that assuming that the matching degree threshold value is 70% in above-mentioned formula, it is only for for example, this hair
It is bright that it's not limited to that.
In step S142, judge whether the target risk value is greater than risk threshold value, if the target risk value is greater than
Risk threshold value then enters step S143；If the target risk value is less than or equal to the risk threshold value, S144 is entered step.
In the embodiment of the present invention, the value of the risk threshold value can be set according to actual needs, for example, it can be set to
It is 80, but the present invention is not limited to this.
In step S143, determine that the target risk grade is the first risk class.
In step S144, determine that the target risk grade is the second risk class.
In the embodiment of the present invention, it can will calculate the target risk value Y obtained and be normalized, be normalized to [0,100],
Assuming that the risk threshold value value is 80, if Y > 80 after then normalizing, determine that the target risk grade is the first risk
Grade, then it is assumed that the risk class of the current knowledge property information is high；If Y≤80 after normalization, determine the target
Risk class is the second risk class, then it is assumed that the risk class of the current knowledge property information is low.
With continued reference to Fig. 3, data processing method provided in an embodiment of the present invention can also include the following steps,
In step s310, if the current knowledge property information is in first risk class, early warning letter is sent
Breath is stored into block chain.
In step s 320, if the current knowledge property information is in second risk class, early warning is not sent
Information.
For example, certain drugmaker A has the historical knowledge property right (it is assumed that for patent of invention) of a drug E, patent is protected
The shield date is 2010.01.01-2020.01.01, and drugmaker B also has developed a quasi-drugs F during this period, and B company will
The relevant information of drug F, for example, the main constituents of drug F, production process, process flow, at assignment system etc., be uploaded to area
Block chain finds the object matching degree P=90% of drug F and drug E, risk assessment after trained good machine learning model assessment
As a result Y=97 is high-risk grade, then system can prompt the drugmaker of relevant departments B there may be abuses.
In the embodiment of the present invention, it is pre- the data processing method can be applied to intellectual property such as patent infringement risk
It is alert, on the one hand, potential infringed person can be made to know that the product issued or openly sold on the market whether there is infringement
May, its interests is protected so as to take some corresponding legal measures, avoids further enlargement loss；Another party
Face can make potential infringing party know that it has a possibility that invading other people intellectual property rights in advance, so that its
It can carry out evading the legal risk designed during the authorization for perhaps seeking obligee avoids research and development of products or sells, keep away
Exempt to do useless R&D work.
In further embodiments, data processing method provided in an embodiment of the present invention can be also used for enterprise or correlation
Department look into the courses of work such as new, infringement, invalid, novelty, creativeness, such as patent retrieval and analysis, currently, mainly
Patent retrieval and analysis to be carried out by manpower, and utilize technical solution provided in this embodiment, may be implemented system automatically into
Row patent retrieval, it would be possible to which existing influences novelty and creative documents is retrieved from block chain, and is supplied to
Retrieval personnel so as to substantially reduce the workload of retrieval personnel, and improve the accuracy rate of retrieval, reduce omission factor.
Fig. 4 diagrammatically illustrates the flow chart of data processing method according to another embodiment of the invention.
As shown in figure 4, data processing method provided in an embodiment of the present invention can also include the following steps.
In step S410, the feature vector of each historical knowledge property information of all categories is extracted.
In the embodiment of the present invention, if the current knowledge property information and each historical knowledge property information are content of text
(being assumed to be patent text) can then pass through the technologies such as Text region, semantics recognition from patent text and extract relevant protection
Point；If the current knowledge property information and each historical knowledge property information are that can be mentioned by way of image recognition
Relevant protection point is taken, after the protection point that these are extracted carries out binary set, the available current knowledge property right letter
The feature vector of breath and each historical knowledge property information.
In the embodiment of the present invention, can also the protection point to said extracted further pass through semantic analysis and similar merging
Method carries out Feature Dimension Reduction, to obtain crucial protection point, can form the spy by the binary set of each crucial protection point
Levy vector.
In the step s 420, according to the feature vector of each historical knowledge property information of all categories and utilize support vector machines
Each historical knowledge property information is divided into predetermined quantity classification by model.
Wherein, the target category is in the predetermined quantity classification (being assumed to be N, N is the positive integer more than or equal to 1)
It is at least one.
In the embodiment of the present invention, support vector machines (Support Vector Machine, SVM) model can be used by area
Existing historical knowledge property information is divided into N classification in block chain: { 1,2 ..N }, and will be current in new addition block catenary system
Intellectual property information one or more of is sorted out to existing N classification.
In the embodiment of the present invention, the method can also include: the intellectual property information of each classification in N classification
In, according to the principle that time random sample is random, extraction intellectual property information, and the intellectual property information of follow-up investigations extraction
In following information any one or it is a variety of: if the intellectual property extracted is patent, it is special to can decide whether arrive this
Whether the patent protection Expiration Date of benefit, situations such as can also judging license expense, the patent royalties of the patent are reasonable.Here
Can whether reasonable to judge automatically license expense and patent royalties by being compared with the similar cases in system.
For example, can by the comparison of similar times, similar technique or like product etc., if under condition of similarity difference be more than 15% with
On, then it may determine that the license expense of the patent or patent royalties are unreasonable.
In the embodiment of the present invention, the method can also include: assessment to the monitoring of intellectual property and tracing management and
Shi Xing, validity and accuracy, availability.
The device of the invention embodiment introduced below can be used for executing the above-mentioned data processing method of the present invention.
Fig. 5 diagrammatically illustrates the block diagram of data processing equipment according to an embodiment of the invention.
As shown in figure 5, the data processing equipment 500 that embodiment of the present invention provides may include that target category obtains module
510, historical data obtains module 520, object matching degree obtains module 530 and target risk grade evaluation module 540.
Wherein, target category obtains module 510 and can be used for obtaining current knowledge property information and determine its target category.
Historical data, which obtains module 520, can be used for obtaining each historical knowledge property information of the target category.
Object matching degree, which obtains module 530, can be used for obtaining the current knowledge property information and the target category
The object matching degree of target histories intellectual property information in each historical knowledge property information.
Target risk grade evaluation module 540 can be used for assessing the current knowledge property right according to the object matching degree
The target risk grade of information.
In the exemplary embodiment, data processing equipment 500 can also include: history data store module, can be used for
Each historical knowledge property information of all categories is stored into block chain；Execution module is triggered, if can be used for described currently knowing
Know property information to store into the block chain, then trigger execution following steps: obtaining current knowledge property information and determine it
Target category；Obtain each historical knowledge property information of the target category；Obtain the current knowledge property information with it is described
The object matching degree of target histories intellectual property information in each historical knowledge property information of target category；According to the target
Matching degree assesses the target risk grade of the current knowledge property information.
In the exemplary embodiment, it may include: that matching degree estimates unit, Ke Yiyong that object matching degree, which obtains module 530,
The current knowledge property information is estimated in the machine learning model completed using training and each history of the target category is known
Know the matching degree of property information；Object matching degree selecting unit can be used for selecting the maximum value in each matching degree as described in
Object matching degree, and determine that the corresponding historical knowledge property information of the maximum value is the target histories intellectual property information.
In the exemplary embodiment, target risk grade evaluation module 540 may include: target risk value obtaining unit,
It can be used for obtaining the target risk value of the current knowledge property information according to the object matching degree；First judging unit,
If can be used for the target risk value greater than risk threshold value, determine that the target risk grade is the first risk class；The
Two judging units determine described target risk etc. if can be used for the target risk value less than or equal to the risk threshold value
Grade is the second risk class.
In the exemplary embodiment, data processing equipment 500 can also include: warning module, if can be used for described work as
Preceding intellectual property information is in first risk class, then sends warning information and store into block chain.
In the exemplary embodiment, the target risk value obtaining unit may include: the first computation subunit, Ke Yiyong
If being greater than matching degree threshold value in the object matching degree, is calculated using the first predetermined manner and obtain the current knowledge property right letter
The target risk value of breath；Second computation subunit, if can be used for the object matching degree is less than or equal to the matching degree threshold value,
The target risk value for obtaining the current knowledge property information is then calculated using the second predetermined manner.
In the exemplary embodiment, data processing equipment 500 can also include: characteristic vector pickup module, can be used for
Extract the feature vector of each historical knowledge property information of all categories；Category division module can be used for according to of all categories each
The feature vector of historical knowledge property information simultaneously utilizes supporting vector machine model, each historical knowledge property information is divided into predetermined
Quantity classification；Wherein, the target category is at least one of described predetermined quantity classification.
Due to each functional module and above-mentioned data processing method of the data processing equipment of example embodiments of the present invention
Example embodiment the step of it is corresponding, therefore for undisclosed details in apparatus of the present invention embodiment, please refer in the present invention
The embodiment for the data processing method stated.
Below with reference to Fig. 6, it illustrates the computer systems 800 for the electronic equipment for being suitable for being used to realize the embodiment of the present invention
Structural schematic diagram.The computer system 800 of electronic equipment shown in Fig. 6 is only an example, should not be to the embodiment of the present invention
Function and use scope bring any restrictions.
As shown in fig. 6, computer system 800 includes central processing unit (CPU) 801, it can be read-only according to being stored in
Program in memory (ROM) 802 or be loaded into the program in random access storage device (RAM) 803 from storage section 807 and
Execute various movements appropriate and processing.In RAM 803, it is also stored with various programs and data needed for system operatio.CPU
801, ROM 802 and RAM 803 is connected with each other by bus 804.Input/output (I/O) interface 805 is also connected to bus
804。
I/O interface 805 is connected to lower component: the importation 806 including keyboard, mouse etc.；It is penetrated including such as cathode
The output par, c 807 of spool (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.；Storage section 808 including hard disk etc.；
And the communications portion 809 of the network interface card including LAN card, modem etc..Communications portion 809 via such as because
The network of spy's net executes communication process.Driver 810 is also connected to I/O interface 805 as needed.Detachable media 811, such as
Disk, CD, magneto-optic disk, semiconductor memory etc. are mounted on as needed on driver 810, in order to read from thereon
Computer program be mounted into storage section 807 as needed.
Particularly, according to an embodiment of the invention, may be implemented as computer above with reference to the process of flow chart description
Software program.For example, the embodiment of the present invention includes a kind of computer program product comprising be carried on computer-readable medium
On computer program, which includes the program code for method shown in execution flow chart.In such reality
It applies in example, which can be downloaded and installed from network by communications portion 809, and/or from detachable media
811 are mounted.When the computer program is executed by central processing unit (CPU) 801, executes and limited in the system of the application
Above-mentioned function.
It should be noted that computer-readable medium shown in the present invention can be computer-readable signal media or meter
Calculation machine readable storage medium storing program for executing either the two any combination.Computer readable storage medium for example can be --- but not
Be limited to --- electricity, magnetic, optical, electromagnetic, infrared ray or semiconductor system, device or device, or any above combination.Meter
The more specific example of calculation machine readable storage medium storing program for executing can include but is not limited to: have the electrical connection, just of one or more conducting wires
Taking formula computer disk, hard disk, random access storage device (RAM), read-only memory (ROM), erasable type may be programmed read-only storage
Device (EPROM or flash memory), optical fiber, portable compact disc read-only memory (CD-ROM), light storage device, magnetic memory device,
Or above-mentioned any appropriate combination.In the present invention, computer readable storage medium can be it is any include or storage journey
The tangible medium of sequence, the program can be commanded execution system, device or device use or in connection.And at this
In invention, computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
Wherein carry computer-readable program code.The data-signal of this propagation can take various forms, including but unlimited
In electromagnetic signal, optical signal or above-mentioned any appropriate combination.Computer-readable signal media can also be that computer can
Any computer-readable medium other than storage medium is read, which can send, propagates or transmit and be used for
By the use of instruction execution system, device or device or program in connection.Include on computer-readable medium
Program code can transmit with any suitable medium, including but not limited to: wireless, electric wire, optical cable, RF etc. are above-mentioned
Any appropriate combination.
Flow chart and block diagram in attached drawing are illustrated according to the system of various embodiments of the invention, method and computer journey
The architecture, function and operation in the cards of sequence product.In this regard, each box in flowchart or block diagram can generation
A part of one module, program segment or code of table, a part of above-mentioned module, program segment or code include one or more
Executable instruction for implementing the specified logical function.It should also be noted that in some implementations as replacements, institute in box
The function of mark can also occur in a different order than that indicated in the drawings.For example, two boxes succeedingly indicated are practical
On can be basically executed in parallel, they can also be executed in the opposite order sometimes, and this depends on the function involved.Also it wants
It is noted that the combination of each box in block diagram or flow chart and the box in block diagram or flow chart, can use and execute rule
The dedicated hardware based systems of fixed functions or operations is realized, or can use the group of specialized hardware and computer instruction
It closes to realize.
Being described in unit involved in the embodiment of the present invention can be realized by way of software, can also be by hard
The mode of part realizes that described unit also can be set in the processor.Wherein, the title of these units is in certain situation
Under do not constitute restriction to the unit itself.
As on the other hand, present invention also provides a kind of computer-readable medium, which be can be
Included in electronic equipment described in above-described embodiment；It is also possible to individualism, and without in the supplying electronic equipment.
Above-mentioned computer-readable medium carries one or more program, when the electronics is set by one for said one or multiple programs
When standby execution, so that the electronic equipment realizes such as above-mentioned data processing method as described in the examples.
For example, the electronic equipment may be implemented as shown in Figure 1: step S110 obtains current knowledge property right letter
It ceases and determines its target category；Step S120 obtains each historical knowledge property information of the target category；Step S130, is obtained
Obtain the target histories intellectual property in the current knowledge property information and each historical knowledge property information of the target category
The object matching degree of information；Step S140 assesses the target wind of the current knowledge property information according to the object matching degree
Dangerous grade.
For another example, each step as shown in Figures 2 to 4 may be implemented in the electronic equipment.
It should be noted that although being referred to several modules or list for acting the equipment executed in the above detailed description
Member, but this division is not enforceable.In fact, embodiment according to the present invention, it is above-described two or more
Module or the feature and function of unit can embody in a module or unit.Conversely, an above-described mould
The feature and function of block or unit can be to be embodied by multiple modules or unit with further division.
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the present invention
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server, touch control terminal or network equipment etc.) executes embodiment according to the present invention
Method.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to of the invention its
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the invention, these modifications, purposes or
Person's adaptive change follows general principle of the invention and including the undocumented common knowledge in the art of the present invention
Or conventional techniques.The description and examples are only to be considered as illustrative, and true scope and spirit of the invention are by following
Claim is pointed out.
It should be understood that the present invention is not limited to the precise structure already described above and shown in the accompanying drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present invention is limited only by the attached claims.
Claims (10)
1. a kind of data processing method characterized by comprising
It obtains current knowledge property information and determines its target category；
Obtain each historical knowledge property information of the target category；
The current knowledge property information is obtained to know with the target histories in each historical knowledge property information of the target category
Know the object matching degree of property information；
The target risk grade of the current knowledge property information is assessed according to the object matching degree.
2. data processing method according to claim 1, which is characterized in that further include:
Each historical knowledge property information of all categories is stored into block chain；
If the current knowledge property information is stored into the block chain, triggers and execute step as claimed in claim 1.
3. data processing method according to claim 1, which is characterized in that obtain the current knowledge property information and institute
State the object matching degree of the target histories intellectual property information in each historical knowledge property information of target category, comprising:
Each history of the current knowledge property information Yu the target category is estimated using the machine learning model that training is completed
The matching degree of intellectual property information；
It selects the maximum value in each matching degree as the object matching degree, and determines that the corresponding historical knowledge of the maximum value produces
Power information is the target histories intellectual property information.
4. data processing method according to claim 1, which is characterized in that work as according to object matching degree assessment
The target risk grade of preceding intellectual property information, comprising:
The target risk value of the current knowledge property information is obtained according to the object matching degree；
If the target risk value is greater than risk threshold value, determine that the target risk grade is the first risk class；
If the target risk value is less than or equal to the risk threshold value, determine that the target risk grade is second risk etc.
Grade.
5. data processing method according to claim 4, which is characterized in that further include:
If the current knowledge property information is in first risk class, sends warning information and stored into block chain.
6. data processing method according to claim 4, which is characterized in that work as according to object matching degree acquisition
The target risk value of preceding intellectual property information, comprising:
If the object matching degree is greater than matching degree threshold value, is calculated using the first predetermined manner and obtain the current knowledge property right
The target risk value of information；
If the object matching degree is less than or equal to the matching degree threshold value, it is described current that acquisition is calculated using the second predetermined manner
The target risk value of intellectual property information.
7. data processing method according to claim 1, which is characterized in that further include:
Extract the feature vector of each historical knowledge property information of all categories；
According to the feature vector of each historical knowledge property information of all categories and supporting vector machine model is utilized, by each historical knowledge
Property information is divided into predetermined quantity classification；
Wherein, the target category is at least one of described predetermined quantity classification.
8. a kind of data processing equipment characterized by comprising
Target category obtains module, for obtaining current knowledge property information and determining its target category；
Historical data obtains module, for obtaining each historical knowledge property information of the target category；
Object matching degree obtains module, for obtaining each historical knowledge of the current knowledge property information Yu the target category
The object matching degree of target histories intellectual property information in property information；
Target risk grade evaluation module, for assessing the target of the current knowledge property information according to the object matching degree
Risk class.
9. a kind of computer-readable medium, is stored thereon with computer program, which is characterized in that described program is executed by processor
Data processing method of the Shi Shixian as described in any one of claims 1 to 7.
10. a kind of electronic equipment characterized by comprising
One or more processors；
Storage device, for storing one or more programs, when one or more of programs are by one or more of processing
When device executes, so that one or more of processors realize the data processing side as described in any one of claims 1 to 7
Method.
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Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110020800A (en) * | 2019-04-04 | 2019-07-16 | 泰康保险集团股份有限公司 | Information processing method, device, medium and electronic equipment based on block chain |
| CN110457808A (en) * | 2019-08-02 | 2019-11-15 | 泰康保险集团股份有限公司 | Manipulator design method, apparatus, medium and electronic equipment |
| CN110852761A (en) * | 2019-10-11 | 2020-02-28 | 支付宝(杭州)信息技术有限公司 | Method and device for formulating anti-cheating strategy and electronic equipment |
| CN111198945A (en) * | 2019-12-03 | 2020-05-26 | 泰康保险集团股份有限公司 | Data processing method, device, medium and electronic equipment |
| CN111311112A (en) * | 2020-03-10 | 2020-06-19 | 开封博士创新技术转移有限公司 | Enterprise intellectual property data management method and device, electronic equipment and readable storage medium |
| CN111368362A (en) * | 2020-03-06 | 2020-07-03 | 广联达科技股份有限公司 | Building model component protection method and system based on block chain |
| CN111798062A (en) * | 2020-07-08 | 2020-10-20 | 洋浦美诺安电子科技有限责任公司 | Financial data prediction system based on block chain and big data |
| CN111832583A (en) * | 2019-04-15 | 2020-10-27 | 泰康保险集团股份有限公司 | Health management method, device, medium and electronic equipment based on block chain |
| CN112035754A (en) * | 2020-11-02 | 2020-12-04 | 北京梦知网科技有限公司 | Trademark retrieval method and device, electronic equipment and storage medium |
| CN116866086A (en) * | 2023-09-01 | 2023-10-10 | 华能信息技术有限公司 | Data security control method and system based on watermark addition |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105808524A (en) * | 2016-03-11 | 2016-07-27 | 江苏畅远信息科技有限公司 | Patent document abstract-based automatic patent classification method |
| CN105930495A (en) * | 2016-05-06 | 2016-09-07 | 长沙市麓智信息科技有限公司 | Product tort monitoring system and monitoring method therefor |
| US20160350886A1 (en) * | 2011-04-15 | 2016-12-01 | Ip Street Holdings, Llc | Method and System for Evaluating Intellectual Property |
| CN107644080A (en) * | 2017-09-21 | 2018-01-30 | 合肥集知网知识产权运营有限公司 | A kind of big data patent retrieval method based on probability retrieval model |
| CN108876213A (en) * | 2018-08-22 | 2018-11-23 | 泰康保险集团股份有限公司 | Product management method, device, medium and electronic equipment based on block chain |
-
2018
- 2018-12-04 CN CN201811472245.9A patent/CN109377104A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160350886A1 (en) * | 2011-04-15 | 2016-12-01 | Ip Street Holdings, Llc | Method and System for Evaluating Intellectual Property |
| CN105808524A (en) * | 2016-03-11 | 2016-07-27 | 江苏畅远信息科技有限公司 | Patent document abstract-based automatic patent classification method |
| CN105930495A (en) * | 2016-05-06 | 2016-09-07 | 长沙市麓智信息科技有限公司 | Product tort monitoring system and monitoring method therefor |
| CN107644080A (en) * | 2017-09-21 | 2018-01-30 | 合肥集知网知识产权运营有限公司 | A kind of big data patent retrieval method based on probability retrieval model |
| CN108876213A (en) * | 2018-08-22 | 2018-11-23 | 泰康保险集团股份有限公司 | Product management method, device, medium and electronic equipment based on block chain |
Non-Patent Citations (2)
| Title |
|---|
| 曹祺: "《情报学视域下的数据研究：理论、原理与方法》", 31 October 2018 * |
| 李振飞: "企业商标侵权监测预警***研究及应用", 《中国优秀硕士学位论文全文数据库社会科学Ⅰ辑》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110020800A (en) * | 2019-04-04 | 2019-07-16 | 泰康保险集团股份有限公司 | Information processing method, device, medium and electronic equipment based on block chain |
| CN111832583A (en) * | 2019-04-15 | 2020-10-27 | 泰康保险集团股份有限公司 | Health management method, device, medium and electronic equipment based on block chain |
| CN110457808A (en) * | 2019-08-02 | 2019-11-15 | 泰康保险集团股份有限公司 | Manipulator design method, apparatus, medium and electronic equipment |
| CN110852761A (en) * | 2019-10-11 | 2020-02-28 | 支付宝(杭州)信息技术有限公司 | Method and device for formulating anti-cheating strategy and electronic equipment |
| CN111198945A (en) * | 2019-12-03 | 2020-05-26 | 泰康保险集团股份有限公司 | Data processing method, device, medium and electronic equipment |
| CN111368362B (en) * | 2020-03-06 | 2024-06-07 | 广联达科技股份有限公司 | Building model component protection method and system based on block chain |
| CN111368362A (en) * | 2020-03-06 | 2020-07-03 | 广联达科技股份有限公司 | Building model component protection method and system based on block chain |
| CN111311112A (en) * | 2020-03-10 | 2020-06-19 | 开封博士创新技术转移有限公司 | Enterprise intellectual property data management method and device, electronic equipment and readable storage medium |
| CN111798062A (en) * | 2020-07-08 | 2020-10-20 | 洋浦美诺安电子科技有限责任公司 | Financial data prediction system based on block chain and big data |
| CN111798062B (en) * | 2020-07-08 | 2021-04-02 | 中信消费金融有限公司 | Financial data prediction system based on block chain and big data |
| CN112035754B (en) * | 2020-11-02 | 2021-03-19 | 北京梦知网科技有限公司 | Trademark retrieval method and device, electronic equipment and storage medium |
| CN112035754A (en) * | 2020-11-02 | 2020-12-04 | 北京梦知网科技有限公司 | Trademark retrieval method and device, electronic equipment and storage medium |
| CN116866086A (en) * | 2023-09-01 | 2023-10-10 | 华能信息技术有限公司 | Data security control method and system based on watermark addition |
| CN116866086B (en) * | 2023-09-01 | 2024-01-30 | 华能信息技术有限公司 | Data security control method and system based on watermark addition |
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Application publication date: 20190222 |