CN108681811A - A kind of data ecosystem of decentralization - Google Patents
A kind of data ecosystem of decentralization Download PDFInfo
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- CN108681811A CN108681811A CN201810435333.5A CN201810435333A CN108681811A CN 108681811 A CN108681811 A CN 108681811A CN 201810435333 A CN201810435333 A CN 201810435333A CN 108681811 A CN108681811 A CN 108681811A
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Abstract
The present invention discloses a kind of decentralization data ecosystem, including:The demand data information of demand data side is distributed to data providing by task distribution system；After the data that data providing offer is provided, gives data check and correction task to data check and correction side respectively, be loaded into calibration data to data quality checking system；Data quality checking system, the check and correction data for receiving data check and correction side deliver finished product data after check and correction confirmation according to calibration data and/or AI technologies to proofreading Data Detection to demand data side, payment instruction is submitted to settlement system simultaneously, to task distribution system feedback data production quality；Settlement system receives the advanced charge of demand data side, according to payment instruction to data providing and data check and correction side payment and settlement expense from advanced charge.The present invention can ensure manually to proofread the quality of datamation in a manner of decentralization.
Description
Technical field
The present invention relates to the supply and demand Ecosystem Technologies fields of artificial intelligence database, and in particular to a kind of decentralization
The data ecosystem.
Background technology
Nearly ten years, artificial intelligence (AI) achieves development at full speed.Increasing income and calculating with technologies such as deep learnings
The rapid advancement of equipment, artificial intelligence have begun gradually to influence the various aspects of human lives.Intelligent sound, recognition of face,
The technologies such as automatic Pilot have no longer been the hot spot of academia, but will really enter into everyone life.
Possessing unlimited possible artificial intelligence technology and application behind, provide fuel is the high-quality data of magnanimity.This
A little training and test data and machine learning algorithm of the data as intelligent algorithm possess the status of no less important.In depth
The background that degree learning algorithm has been increased income comprehensively under, training data becomes particularly important.
In future, greater amount is depended on the high-quality data of magnanimity to support by the progress of artificial intelligence technology.On the one hand, existing
The production capacity of somebody's work intelligent data is limited, can not support following demand data.On the other hand, each of us has existed
Mass data is left on internet, but the property right of these data is indefinite, utilization rate has very big room for promotion.Current data
In the industrial chain of library, there is multistage agent between database party in request and actual fabrication side, lead to data creating efficiency
It is low, it is of high cost, and can not provide safeguard to the personal information data safety of picker.
Application block chain (decentralization) technology be using magnanimity fragmentation Internet user data, improve data production capacity and
The optimal path of service efficiency.The data ecosystem of decentralization can make the personal data safety that mass users generate
Higher, i.e. data to eliminate each level data agent only to specific amount of data real demand side as it can be seen that obtain data
In cover the possibility of information.In addition, the data ecosystem of decentralization can make the provider of data obtains to be carried for it
The data class of confession and the complete control of whereabouts abuse data providing privacy and personal letter so as to avoid data agent
The possibility of breath.
Although currently existing various decentralization agreements and solution based on Hash (HASH) algorithm, these
Scheme all cannot be directly applied in the data ecosystem of a decentralization.Wherein most important problem is：Data
(such as voice data, image data) is if want to generate contribution, data itself to a kind of intelligent algorithm (such as deep learning)
It needs accurately to be marked.As if a voice recording is want to be applied by speech recognition algorithm, it is necessary to have with this section of voice signal
Text signal (content in this section of voice signal being write exactly, hereinafter referred to as with data) be supplied to algorithm to be trained together.
And obtain for the corresponding work for explaining content of a certain data, referred to as mark work, it usually needs manually carry out check and correction mark.
It can be seen that current decentralization technology can ensure the uniqueness of data that data providing provides, safety and can be right
The transaction of a certain data records etc.；It is also ensured that a certain proof-reader to data proofreads the unique of the adjoint data generated
Property, safety and the transaction of data after a certain check and correction can be recorded.But currently, can not be ensured in a manner of decentralization
The quality of artificial check and correction datamation.If this link cannot be guaranteed, the data generated cannot be used by artificial intelligence system.
Invention content
In view of the technical drawbacks of the prior art, it is an object of the present invention to provide a kind of decentralization data ecologies
System.
The technical solution adopted to achieve the purpose of the present invention is：
A kind of decentralization data ecosystem, including:
Task distribution system, for the demand data information of demand data side to be distributed to data by scheduled allocation rule
Provider；After the data that data providing offer is provided, data check and correction task is pressed into default allocation rule respectively to data
Check and correction side is labeled data by data check and correction side, and is loaded into calibration data to data quality checking system；
Data quality checking system, the check and correction data for receiving data check and correction side, according to the calibration data of loading and/or
AI technologies are detected check and correction data, proofread and deliver finished product data to demand data side after being identified through, while being to clearing
System submits payment instruction, and carries out data creating Quality Feedback to task distribution system simultaneously；
Settlement system, the advanced charge for receiving demand data side, and the payment according to data quality checking system
Instruction carries out disbursement and sattlement, into pre-payment to data providing and data check and correction side payment and settlement expense.
The demand data information includes data type, data scale, data price, quality of data requirement, data quality checking
Method.
The task distribution system after receiving demand data information, first by data party in request arrange in advance rule into
The inspection of row submission demand, such as meets examination requirements, then distributes data acquisition session to data providing；Otherwise to demand data
Side's feedback, it is desirable that demand data side is changed, and is executed repeatedly, until by inspection.
The task distribution system to data providing before distributing data acquisition session, and first the data of broadcast collection downwards carry
Supplier and data check and correction side such as fail to obtain minimum participant quantity within certain time, are then fed back to demand data side
As a result, and prompt demand data side to change demand, until reach minimum participant quantity.
Each minimum unit data in the data that data providing that the task distribution system receives is submitted will be with
The personally identifiable information of data providing generates the cryptographic Hash of a regular length by wishing operation together.
The data quality checking system receives each minimum unit number in the check and correction data submitted data check and correction side
The Kazakhstan for generating a regular length according to uncommon operation will be passed through together with the personally identifiable information of data markup information, data check and correction side
Uncommon value.
The data quality checking system is obstructed out-of-date in check and correction, is sent to data check and correction side and proofreads instruction of doing over again, data
Check and correction side need to again be uploaded after improving quality of proofreading until passing through.
The calibration data is the finished product data provided by demand data side.
The data quality checking system examines check and correction data by the calibration data and/or artificial intelligence
It surveys.
The decentralization data ecosystem provided by the invention can ensure manually to proofread data work in a manner of decentralization
The quality of work ensures that the data generated will be used by artificial intelligence system.
Description of the drawings
Fig. 1 is the principle schematic of the data ecosystem of decentralization.
Specific implementation mode
The present invention is described in further detail below in conjunction with the drawings and specific embodiments.It should be appreciated that described herein
Specific embodiment be only used to explain the present invention, be not intended to limit the present invention.
It is shown in Figure 1, a kind of data ecosystem of decentralization, including：
Task distribution system, for the demand data information of demand data side to be distributed to data by scheduled allocation rule
Provider；After the data that data providing offer is provided, data check and correction task is pressed into default allocation rule respectively to data
Check and correction side is labeled data by data check and correction side, and is loaded into calibration data to data quality checking system；
Data quality checking system, the check and correction data for receiving data check and correction side, according to the calibration data of loading and/or
AI technologies are detected check and correction data, proofread and deliver finished product data to demand data side after being identified through, while being to clearing
System submits payment instruction, and carries out data creating Quality Feedback to task distribution system simultaneously；
Settlement system, the advanced charge for receiving demand data side, and the payment according to data quality checking system
Instruction carries out disbursement and sattlement, into pre-payment to data providing and data check and correction side payment and settlement expense.
It should be noted that in the present invention, the subsystems in the data ecosystem are all in a manner of decentralization
It is built, i.e., only there is logically but be actually deployed in as data ecosystem each system in a distributed fashion
System is provided in the computer for calculating power, and the transmission of modem instruction is carried out by encrypted interconnection web form.It is any that there is calculating money
The entity in source can provide for system to be calculated power and therefrom makes a profit, wherein also including demand data side, data providing sum number
According to check and correction side.
Wherein, in the present invention, the demand data information or specification demands of the demand data are divided from demand data to task
Match system submission includes, but are not limited to data type (such as voice, image, text, video), data scale, data price, number
(such as using the calibration data quality inspection of demand data side's offer, or artificial intelligence AI is used according to quality requirement, data quality checking method
Technology quality inspection).
Wherein, the task distribution system is after receiving demand data information, first by arranging in advance data party in request
Rule carries out the inspection of submission demand, such as meets examination requirements, then distributes data acquisition session to data providing；Otherwise to number
Fed back according to party in request, feedback there are the problem of, it is desirable that demand data side change；It submits and examines again after the modification of pending data party in request
Core.This process is executed repeatedly until demand passes through.
Wherein, after the demand data of demand data side is examined by system, the task distribution system is to data
Before provider distributes data acquisition session, first data providing and data check and correction side are collected in broadcast downwards, such as in certain time
Within fail to obtain the minimum participant quantity of system requirements, then task distribution system is to demand data side's feedback result, and
Demand data side's modification demand (such as data price or quotation) is prompted, until reaching minimum participant quantity.
After reaching minimum participant quantity, expense is paid in advance by a certain percentage by demand data side to settlement system
In, data acquisition session then is distributed from the task distribution system to data providing again, starts the collection of material school of data
The subsequent work of equity.
When the task distribution system distributes data acquisition session to data providing, provider's data creating is considered
Ability, making quality of data etc. are allocated.
Wherein, a part for the expense paid in advance will be paid to the side for providing check and correction for this data acquisition session
Expense, to the guarantee of data providing clearing when another part is then completed as data creating.It will before data are successfully delivered
It rests in data settlement system, until the data finished product of data providing submission has passed through the quality of data quality checking system
It detects and has submitted to demand data side.
The data providing will carry out data acquisition on demand after receiving acquisition tasks, acquisition complete after to appoint
Distribution system of being engaged in submits data, wherein each in the data that data providing that the task distribution system receives is submitted
Minimum unit data data_capture (in such as voice data, minimum unit is in short) knows the individual with data providing
Other information userID generates the cryptographic Hash of a regular length by wishing operation together, is shown below：
Hc=hash (data_capture+userID)
In addition, data providing to task distribution system upload gathered data while also in a broadcast manner to system
Cryptographic Hash is issued, for stating the right of the data to a certain acquisition, to ensure accuracy when clearing and two time selling knot
The accuracy of calculation.
After certain data are uploaded to task distribution system by data providing, task distribution system presses check and correction task
According to certain rule data check and correction side is distributed to (such as according to the ability of data check and correction side data creating, quality).
Data check and correction side will carry out data check and correction on demand after receiving check and correction task, to the quality of data after check and correction is completed
Detecting system submit data, the data quality checking system receive in the check and correction data submitted data check and correction side each most
Junior unit data data_capture (in such as voice data, minimum unit is in short) identifies the individual with data check and correction side
Information userID, data label data_labelling generate the cryptographic Hash of a regular length by wishing operation together, as follows
Shown in formula.
Hl=hash (data_capture+data_labelling+userID)
It also issues and breathes out to system in a broadcast manner while uploading collection result to system in the data check and correction side
Uncommon value, for stating the right of the data to a certain check and correction, to ensure accuracy when clearing and the standard of two time selling clearing
True property.
Wherein, specifically, in the present invention, the data quality checking system is obstructed out-of-date in check and correction, to data check and correction side
It sends and proofreads instruction of doing over again, data check and correction side need to again be uploaded after improving quality of proofreading until passing through.To demand data
After side provides qualified data, the data quality checking system will be to task distribution system feedback data provider and data
The work quality of check and correction side, for additionally (caused system i.e. off quality is additionally secondary for consumption calculation power in processing procedure
The waste of the computing resources such as verification) each side punished, measure include but not limited to the clearing that power cost is calculated outside deduction, under
Subtask distributes the adjustment etc. of priority.
Wherein, in the present invention, when carrying out quality testing, the calibration data is to pass through people by what demand data side provided
The qualified finished product data that work mode detects.
Since initial data is acquired by data providing, adjoint markup information is provided by data check and correction side.Due to uncommon
The work quality for hoping verify data check and correction side can be in data quality checking system：
A) it introduces and provides some good finished product data conduct evaluation check and correction side's work of hand inspection by demand data side
The foundation of quality；
B) one or more existing artificial intelligence systems are added and are judged that result is as the work of evaluation data check and correction side
The foundation of quality；
C) the finished product data and artificial intelligence system provided using demand data side carry out comprehensive judgement, and result is used as and comments
Valence mumber according to check and correction side's work quality foundation.
The method of above-mentioned data quality checking is illustrated below.
A) demand data side provides the soft check method of a small amount of calibration data
If the data needed for demand data side are that (voice signal can be N number of unit in such as speech recognition database
The data of one unit), the requirement according to demand data side to database quality can prepare M calibration data (M simultaneously<<N).
Specifically, these data can be inserted randomly into during data check and correction, it is desirable that data check and correction side is as required to phase
Data are answered to be proofreaded (but which is calibration data in check and correction data needed for not informing).Number will be calibrated such as in speech database
The recorded audio data of audio signal and the data providing acquisition that will be proofread in are randomly sent with certain ratio
Proof-reading is carried out to data check and correction side.
The minimum value of M calibration data is
Mmin=Imax*m
Wherein, ImaxThe maximum check and correction number accepted is allowed (to submit check and correction Shen according to initial stage by individual data check and correction side
Please, I has at most accepted in each data check and correction sidemaxSecondary check and correction task, since data acquisition needs some cycles, data will be according to
Certain unit is issued to data check and correction side, such as the data of 1000 units of check and correction every time in batches)；M is added by check and correction every time
Calibration data amount (as every time check and correction 1000 units data in may include that 20 calibration data, i.e., practical labeled data are
980 units).It can ensure that calibration data (i.e. verification data) used in each check and correction side does not repeat in this way.
In data quality checking system, for the unit data that a certain data check and correction side is submitted, extract in this data set
Partial collimation data verified.The method of verification be compare data check and correction side for proofread verify data result and confession
The deviation of the collation just provided.Such as image data, the verification of object pixel level deviation can be labeled.
By taking most common image box mark as an example, if the left upper apex coordinate of figure Pi mark boxes is (a, b), bottom right top
Point coordinates is (c, d), and the left upper apex coordinate of verify data is (A, B), and bottom right vertex coordinate is (C, D), then deviation diff is：
Wherein, diffLTFor the error on the mark box upper left vertex (Left, Top) and verification box left upper apex；diffRB
For the error on the mark box bottom right vertex (Right, Bottom) and verification box bottom right vertex；
To arbitrary picture Pi, if deviation is less than preset value (difftarget), then judge that picture is labeled with effect, i.e.,：
Such as mark 1 pixel of box upper left deviation, 1 pixel of bottom right deviation, then diffLTWith diffRBIt is 2.If difftarget
More than 2, then the mark can pass through.
If the accuracy of m unit calibration data is more than preset value, judge that corresponding real data is effective.
B) system uses artificial intelligence system, provides the additional method of calibration for calculating power
If demand data side can not provide calibration data, system can provide additional calculation by using artificial intelligence system
Power carries out the verification of quality of proofreading.
Generally for a data acquisition session, purpose is usually to improve the performance for having artificial intelligence system.Therefore it can
To use existing artificial intelligence system to verify.If the accuracy P of required datadLess than the discrimination of existing artificial intelligence system
Ps, then the data after verification can be generated result by existing artificial intelligence system and collation compares, if consistent ratio
More than or equal to PdThen data can pass through verification.
If the accuracy P of required datadHigher than the discrimination P of existing artificial intelligence systems, then can be by the data after verification
Result is generated by existing artificial intelligence system and collation compares, if consistent ratio is less than PsThen data directly verify mistake
It loses；If consistent ratio is more than PsThen partial data is proposed to be used as redundancy calibration data, this partial data is distributed to simultaneously
Several data check and correction sides are proofreaded again.It is right value to take check and correction answer more than number, with the original check and correction data in this part into
Row compares, if concordance rate is more than Pd, then proofread and be verified, otherwise do not pass through.Descendant is verified again in the calibration data of redundancy
The redundancy calibration data that the more check and correction answer of number can be used as system distributes to other proof-readers that this batch of calibration data was not used
Operation in carrying out a).
The data verification method of the above-mentioned data quality checking system of the present invention can be according to preset verification method and ratio
Verify whether a certain data acquisition system meets specific authentication demand, that is, the data set being verified will be allowed that there are a degree of mistakes
Mistake, error etc. can all regard data acquisition system meet demand as a whole as long as disclosure satisfy that scheduled accuracy, precision etc..
The above is only a preferred embodiment of the present invention, it is noted that for the common skill of the art
For art personnel, various improvements and modifications may be made without departing from the principle of the present invention, these improvements and modifications
Also it should be regarded as protection scope of the present invention.
Claims (8)
1. a kind of data ecosystem of decentralization, which is characterized in that including:
Task distribution system is provided for the demand data information of demand data side to be distributed to data by scheduled allocation rule
Side；After the data that data providing offer is provided, data check and correction task is pressed into default allocation rule and is proofreaded respectively to data
Side, is labeled data by data check and correction side, and be loaded into calibration data to data quality checking system；
Data quality checking system, the check and correction data for receiving data check and correction side, according to the calibration data of loading and/or AI skills
Art is detected check and correction data, proofreads and delivers finished product data to demand data side after being identified through, while being carried to settlement system
Payment instruction is handed over, and carries out data creating Quality Feedback to task distribution system simultaneously；
Settlement system, the advanced charge for receiving demand data side, and the payment instruction according to data quality checking system
Disbursement and sattlement is carried out, to data providing and data check and correction side payment and settlement expense from pre-payment.
2. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the demand data information includes data
Type, data scale, data price, quality of data requirement, data quality checking method.
3. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the task distribution system is receiving number
After demand information, the inspection of submission demand is first carried out by the rule arranged in advance data party in request, such as meets examination requirements,
Then data acquisition session is distributed to data providing；Otherwise it is fed back to demand data side, it is desirable that demand data side is changed, and is held repeatedly
Row, until by inspection.
4. according to the data ecosystem for requiring 3 decentralizations, which is characterized in that the task distribution system is to data
Before provider distributes data acquisition session, the first data providing and data check and correction side of broadcast collection downwards, such as certain time it
Inside fail to obtain minimum participant quantity, then to demand data side's feedback result, and demand data side is prompted to change demand, directly
To reaching minimum participant quantity.
5. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the number that the task distribution system receives
Each minimum unit data in the data submitted according to provider will together pass through with the personally identifiable information of data providing
Uncommon operation generates the cryptographic Hash of a regular length.
6. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the data quality checking system receives
Each minimum unit data in the check and correction data that data check and correction side is submitted are by with data markup information, data check and correction side
People's identification information generates the cryptographic Hash of a regular length by wishing operation together.
7. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the data quality checking system is in school
To obstructed out-of-date, sent to data check and correction side and proofread instruction of doing over again, data check and correction side need to again carry out after improving quality of proofreading
It passes until passing through.
8. according to the data ecosystem for requiring 1 decentralization, which is characterized in that the calibration data is by demand data
The finished product data just provided.
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