CN109063151A - A kind of commercial banks data fusion method and device - Google Patents
A kind of commercial banks data fusion method and device Download PDFInfo
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- CN109063151A CN109063151A CN201810895683.XA CN201810895683A CN109063151A CN 109063151 A CN109063151 A CN 109063151A CN 201810895683 A CN201810895683 A CN 201810895683A CN 109063151 A CN109063151 A CN 109063151A
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Abstract
The present invention provides a kind of commercial banks data fusion method and devices, this method can choose the aiming field content for being fused the target labels file of internal data and obtaining target labels file, and the source field content for being fused the source label file of external data and obtaining source label file is generated, and then fusion treatment is carried out to aiming field content and source field content.The present invention carries out tagging management by establishing unified data standard, to data in the row of business bank, to support to customize data by decision objective.Simultaneously because analysis decision process is that a constantly progressive process improves data fusion flexibility there is no need to disposably prepare data, fusion cost is accordingly also just reduced.
Description
Technical field
The present invention relates to technical field of data processing, more specifically to a kind of commercial banks data fusion method and
Device.
Background technique
Data fusion, essence is associated or comprehensive analysis for multi-source data, and by choosing fusion appropriate
Mode and Processing Algorithm improve the quality of data, lay the foundation for subsequent knowledge development.
In business bank's big data analysis project, data fusion process is customized according to particular analysis decision, number
According to preparation and disposably, this results in data fusion flexibility very poor, so that fusion cost is very high.
Summary of the invention
In view of this, to solve the above problems, the present invention provides a kind of commercial banks data fusion method and device, technology
Scheme is as follows:
A kind of commercial banks data fusion method, comprising:
The target labels file for being fused internal data is chosen from the label file of pre-generated internal data, and is obtained
Take the aiming field content of the target labels file；
The source label file of external data to be fused is generated, and obtains the source field content of the source label file；
Fusion treatment is carried out to the aiming field content and the source field content according to preset data fusion mode.
Preferably, the method also includes:
Quality testing is carried out to the source field content according to preset data quality testing strategy；
In the case where quality measurements are for characterizing the first errorless result, return described in executing according to present count
Fusion treatment is carried out to the aiming field content and the source field content according to fusion mode；
In the case where quality measurements are the second result for characterizing mistake, the source field content is repaired
Positive processing, and return and quality testing is carried out to the source field content according to preset data quality testing strategy described in execution.
Preferably, the method also includes:
Detect the conflicting of the aiming field content and the source field content；
The aiming field content and the source field content there is no in the case where conflict, return execute it is described according to
Preset data fusion mode carries out fusion treatment to the aiming field content and the source field content；
It is deposited in the case of a conflict in the aiming field content and the source field content, according to preset data conflict solution
Decision slightly handles the aiming field content, and returns and execute the detection aiming field content and the source field content
Conflicting.
Preferably, the method also includes:
Calculate the confidence level of the source field content；
In the case where the confidence level is greater than default believability threshold, returns and merge mould according to preset data described in executing
Formula carries out fusion treatment to the aiming field content and the source field content；
In the case where the confidence level is not more than default believability threshold, the source word is handled according to default Processing Algorithm
Section content, and return and execute the confidence level for calculating the source field content.
Preferably, the method also includes:
Visualization projection is carried out to the source field content.
Preferably, the method also includes:
Data label is added to fusion treatment result.
A kind of commercial banks data fusing device, comprising:
First chooses module, is fused internal data for choosing from the label file of pre-generated internal data
Target labels file, and obtain the aiming field content of the target labels file；
Second chooses module, for generating the source label file of external data to be fused, and obtains the source label file
Source field content；
Fusion treatment module is used for according to preset data fusion mode in the aiming field content and the source field
Hold and carries out fusion treatment.
Preferably, described device further include:
Quality detection module, for carrying out quality inspection to the source field content according to preset data quality testing strategy
It surveys；In the case where quality measurements are for characterizing the first errorless result, the fusion treatment module is triggered；In quality
In the case that testing result is the second result for characterizing mistake, processing is modified to the source field content, and return
Quality testing is carried out to the source field content according to preset data quality testing strategy described in executing.
Preferably, described device further include:
Collision detection module, for detecting the conflicting of the aiming field content and the source field content；Described
Aiming field content and the source field content trigger the fusion treatment module there is no in the case where conflict；In the mesh
Mark field contents and the source field content are deposited in the case of a conflict, handle the mesh according to preset data conflict-solving strategy
Field contents are marked, and return to the conflicting for executing detection the aiming field content and the source field content.
Preferably, described device further include:
Confidence level computing module, for calculating the confidence level of the source field content；The confidence level be greater than it is default can
In the case where confidence threshold, the fusion treatment module is triggered；The case where the confidence level is not more than default believability threshold
Under, the source field content is handled according to default Processing Algorithm, and return and execute the credible of the calculating source field content
Degree.
Compared to the prior art, what the present invention realized has the beneficial effect that
Above the present invention provides a kind of commercial banks data fusion method and device, in this method can be chosen and be fused
The target labels file of portion's data and the aiming field content for obtaining target labels file, and generate and be fused external data
Source label file and the source field content for obtaining source label file, and then aiming field content and source field content are merged
Processing.The present invention carries out tagging management by establishing unified data standard, to data in the row of business bank, to support
Data are customized by decision objective.Simultaneously because analysis decision process is a constantly progressive process, there is no need to disposably prepare
Data improve data fusion flexibility, accordingly also just reduce fusion cost.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the method flow diagram of commercial banks data fusion method provided in an embodiment of the present invention；
Fig. 2 is the agent structure schematic diagram of label file in the embodiment of the present invention；
Fig. 3 is the structural schematic diagram of commercial banks data fusing device provided in an embodiment of the present invention.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The embodiment of the present invention provides a kind of commercial banks data fusion method, the method flow diagram of this method as shown in Figure 1,
Include the following steps:
S10 chooses the target labels file for being fused internal data from the label file of pre-generated internal data,
And obtain the aiming field content of target labels file.
In the present embodiment, data are defined in a manner of file in the row of business bank, for all alternative inside numbers
According to by mechanized classification all corresponding label files of generation, that is, target labels file, to be solved to internal data
It releases and life cycle management.Label file is made of data file, dimension file, data meaning file and index file, main body
Structure is as shown in Figure 2.Simple introduction is done respectively to data file, dimension file, data meaning file and index file below:
Data file is the ontology of data, the main contents of storing data；
Dimension file, mainly for data file be count class destination file when, need to mark Statistical Criteria；
Data meaning file is the file for explaining data attribute；
Index file is that have up to a hundred for certain special datas, such as the destination file of alternate analysis, possible source data
A field, but participate in intersect field only some, this index file can be used to search participate in alternate analysis column.
In addition, illustrating the feature of data in data management table shown in Fig. 2 with specific example:
File format: standard, it is non-standard；
Map style: map, area-graph, histogram, thermodynamic chart, bubble diagram；
Calculate bore: administrative bore, geographical bore, customized bore；
Computer capacity: Sichuan, Hubei ... other national provinces and cities or municipality directly under the Central Government；
Computation levels: head office, level-one branch, second level branch, subbranch, site；
The reflection of graphics type: Geographical projections, value distribution, site ranking, value composition；
Data granularity: levels of clients, organizational level, customized group of grade；
File type: data file, dimension file, data meaning file, index file.
During executing step S10, user uses system to initiate fusion order from front-end interface, and system first melt by basis
Input condition in conjunction order, such as " the business date: 20170228, file format: standard, map style: map calculates mouth
Diameter: administrative bore, computer capacity: the whole nation, computation levels: level-one branch, the reflection of graphics type: Geographical projections, data granularity: machine
Structure rank, file type: data file " chooses corresponding target labels file, i.e. target data file, target dimension file, mesh
Data meaning file and target indicator file are marked, and then above-mentioned target labels file is parsed to obtain target labels file
Aiming field content.
Certainly, user can also specify certain field as aiming field in input condition, such as " field: payroll credit
Income ", the present embodiment does not limit this, and can be configured according to actual needs.
, can be by all data abstractions by generating the label file of internal data in the present embodiment, user can be by
According to self-demand, target labels file can be chosen by inputting class SQL password.It is thereby achieved that quickly positioning and inquiry,
It reduces the consuming for looking for data greatly in this way, greatly improves the efficiency of data fusion, ensure that the stability of data fusion.
S20, generates the source label file of external data to be fused, and obtains the source field content of source label file.
During executing step S20, its corresponding label text is generated by carrying out classification to external data to be fused
Part, that is, source label file.For label file introduction referring to the introduction in step S10 to label file, the present embodiment
It repeats no more.
Further, since source field content can not be projected directly on map as the attribute data of operation flow,
It has to merge geodata.Therefore, visualization projection further can be carried out to source field content, projection process is as follows:
The data dimension of detection source field contents first；If data dimension is mechanism dimension, according to dimension institute of mechanism
Geographic coordinate data is merged in corresponding city；If data dimension is client's dimension, according to statistical dimension text predetermined
Part counts the mechanism dimension of client's institutional affiliation, and then the city according to corresponding to mechanism dimension, merges geographic coordinate data；Most
Afterwards, it after merging geographic coordinate data, can be rendered with invocation map projection function.
In addition, it should be noted that, can multiplicity according to the statistical method that statistical dimension file counts client's institutional affiliation
Change, supports summation and the calculating of average and accounting etc..
S30 carries out fusion treatment to aiming field content and source field content according to preset data fusion mode.
During executing step S30, preset data fusion mode can be association splicing, can also be statistics fortune
It calculates, can also be filtration operation etc., can be called on demand according to customized data anastomosing algorithm library.
In addition, life cycle management is carried out for convenience of to fusion treatment result in some other embodiment, it can also be right
Fusion treatment result adds data label, wherein the data label can be used as the version number of fusion treatment result.
In some other embodiment, for the reliability for guaranteeing data, commercial banks data fusion method is shown in Fig. 1
On the basis of, further include following steps:
Quality testing is carried out to source field content according to preset data quality testing strategy；Quality measurements be for
In the case where characterizing the first errorless result, S30 is returned to step；In second that quality measurements are for characterizing mistake
As a result in the case where, processing is modified to source field content, and return to step S30.
In the present embodiment, preset data quality testing strategy can for frequency detection, missing values detection, rejecting outliers,
Any one or more, table in the strategy such as particular value (variance or expectation or standard deviation) detection and complex rule detection
1, table 2, table 3, table 4 and table 5 be respectively above-mentioned frequency detection, missing values detection, rejecting outliers, particular value _ expectation detect with
And the example of complex rule detection reports an error if the tolerance degree of bias is greater than default tolerance degree of bias threshold value:
Table 1
Table 2
Table 3
Table 4
Table 5
In actual application, preset data quality testing strategy supports customized selection and configuration, automatically generates inspection
Survey pol-icy code.Detection part timeliness is high, and the statistical analysis module based on sas, execution efficiency is higher, for ten million magnitude
As a result, corresponding quality measurements can be obtained in two to three minutes.
In some other embodiment, to solve the problems, such as fusion conflict, commercial banks data fusion method is shown in Fig. 1
On the basis of, further include following steps:
Detect the conflicting of aiming field content and source field content；It is not present in aiming field content and source field content
In the case where conflict, S30 is returned to step；Aiming field content and source field content deposit in the case of a conflict, according to
Preset data conflict-solving strategy processing target field contents, and return to step S30.
In the present embodiment, the process for detecting conflicting is as follows: first, in accordance with preset data quality testing strategy to source field
Content carries out quality testing, wherein the process of quality testing can be with parameter above-described embodiment disclosure, and the present embodiment is no longer superfluous
It states.
In the case where quality measurements are for characterizing the first errorless result, target labels file and source mark are judged
Whether consistent sign dimension file in file；If it is inconsistent, needing specified dimension, and source field content is recalculated, and return
The step for receipt row " judging whether target labels file and dimension file in the label file of source are consistent "；If consistent, press
According to default statistical items (for example, the statistical items of value type are mean value, variance, null value rate, frequency, quantile etc., character for another example
The statistical items of type are null value rate, frequency, particular value accounting etc.) count aiming field content and the respective field of source field content
Distribution integrates two field distribution results at this time and further determines whether there is conflict.
In the case where quality measurements are the second result for characterizing mistake, directly give up source field content, and
Determine that aiming field content and source field content have conflict；
It should be noted that preset data conflict-solving strategy can be adjusted on demand according to customized conflict resolution algorithm library
With.
In some other embodiment, to solve the problems, such as the data multiframe occurred since data quality can not be screened,
Further include following steps on the basis of Fig. 1 shows commercial banks data fusion method:
Calculate the confidence level of source field content；In the case where confidence level is greater than default believability threshold, return executes step
Rapid S30；In the case where confidence level is not more than default believability threshold, source field content is handled according to default Processing Algorithm, and
Return to the step for executing " confidence level for calculating source field content ".
In the present embodiment, the confidence level of source field content can be calculated using bayes method.And default Processing Algorithm is then
It can be using based on any one or more in the methods of information retrieval, web-link analysis and Bayesian model.
Commercial banks data fusion method provided in an embodiment of the present invention, by establishing unified data standard, to business
Data carry out tagging management in the row of bank, to support to customize data by decision objective.Simultaneously because analysis decision process is
One constantly progressive process improves data fusion flexibility, accordingly also just reduces there is no need to disposably prepare data
Merge cost.
The commercial banks data fusion method provided based on the above embodiment, the embodiment of the present invention is then corresponding to be provided one kind and holds
The device of the above-mentioned commercial banks data fusion method of row, the structural schematic diagram of the device are as shown in Figure 3, comprising:
First chooses module 10, is fused internal data for choosing from the label file of pre-generated internal data
Target labels file, and obtain the aiming field content of target labels file；
Second chooses module 20, for generating the source label file of external data to be fused, and obtains source label file
Source field content；
Fusion treatment module 30, for being carried out according to preset data fusion mode to aiming field content and source field content
Fusion treatment.
In some other embodiment, for the reliability for guaranteeing data, commercial banks data fusing device is shown in Fig. 3
On the basis of, further include following module:
Quality detection module, for carrying out quality testing to source field content according to preset data quality testing strategy；?
Quality measurements be for characterizing the first errorless result in the case where, trigger fusion treatment module 30；In quality testing knot
In the case that fruit is the second result for characterizing mistake, processing is modified to source field content, and returns and is pressed described in execution
Quality testing is carried out to source field content according to preset data quality testing strategy.
In some other embodiment, to solve the problems, such as fusion conflict, commercial banks data fusing device is shown in Fig. 3
On the basis of, further include following module:
Collision detection module, for detecting the conflicting of aiming field content and source field content；In aiming field content
With source field content there is no in the case where conflict, fusion treatment module 30 is triggered；In aiming field content and source field content
It deposits in the case of a conflict, according to preset data conflict-solving strategy processing target field contents, and returns and execute the detection
The conflicting of aiming field content and source field content.
In some other embodiment, to solve the problems, such as the data multiframe occurred since data quality can not be screened,
Further include following module on the basis of Fig. 3 shows commercial banks data fusing device:
Confidence level computing module, for calculating the confidence level of source field content；It is greater than default believability threshold in confidence level
In the case where, trigger fusion treatment module 30；In the case where confidence level is not more than default believability threshold, according to default processing
Algorithm process source field content, and return and execute the confidence level for calculating source field content.
Commercial banks data fusing device provided in an embodiment of the present invention, by establishing unified data standard, to business
Data carry out tagging management in the row of bank, to support to customize data by decision objective.Simultaneously because analysis decision process is
One constantly progressive process improves data fusion flexibility, accordingly also just reduces there is no need to disposably prepare data
Merge cost.
A kind of commercial banks data fusion method provided by the present invention and device are described in detail above, herein
In apply that a specific example illustrates the principle and implementation of the invention, the explanation of above example is only intended to sides
Assistant solves method and its core concept of the invention；At the same time, for those skilled in the art, think of according to the present invention
Think, there will be changes in the specific implementation manner and application range, in conclusion the content of the present specification should not be construed as pair
Limitation of the invention.
It should be noted that all the embodiments in this specification are described in a progressive manner, each embodiment weight
Point explanation is the difference from other embodiments, and the same or similar parts between the embodiments can be referred to each other.
For the device disclosed in the embodiment, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, phase
Place is closed referring to method part illustration.
It should also be noted that, herein, relational terms such as first and second and the like are used merely to one
Entity or operation are distinguished with another entity or operation, without necessarily requiring or implying between these entities or operation
There are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant are intended to contain
Lid non-exclusive inclusion, so that the element that the process, method, article or equipment including a series of elements is intrinsic,
It further include either the element intrinsic for these process, method, article or equipments.In the absence of more restrictions,
The element limited by sentence "including a ...", it is not excluded that in the process, method, article or equipment including the element
In there is also other identical elements.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein
General Principle can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore, of the invention
It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one
The widest scope of cause.
Claims (10)
1. a kind of commercial banks data fusion method characterized by comprising
The target labels file for being fused internal data is chosen from the label file of pre-generated internal data, and obtains institute
State the aiming field content of target labels file；
The source label file of external data to be fused is generated, and obtains the source field content of the source label file；
Fusion treatment is carried out to the aiming field content and the source field content according to preset data fusion mode.
2. the method according to claim 1, wherein the method also includes:
Quality testing is carried out to the source field content according to preset data quality testing strategy；
In the case where quality measurements are for characterizing the first errorless result, return and melt described in executing according to preset data
Syntype carries out fusion treatment to the aiming field content and the source field content；
In the case where quality measurements are the second result for characterizing mistake, place is modified to the source field content
Reason, and return and quality testing is carried out to the source field content according to preset data quality testing strategy described in execution.
3. the method according to claim 1, wherein the method also includes:
Detect the conflicting of the aiming field content and the source field content；
In the aiming field content and the source field content there is no in the case where conflict, return described in executing according to default
Data fusion mode carries out fusion treatment to the aiming field content and the source field content；
It is deposited in the case of a conflict in the aiming field content and the source field content, according to preset data Conflict solving plan
The aiming field content is slightly handled, and returns to execute and described detects rushing for the aiming field content and the source field content
Prominent property.
4. the method according to claim 1, wherein the method also includes:
Calculate the confidence level of the source field content；
In the case where the confidence level is greater than default believability threshold, return described in executing according to preset data fusion mode pair
The aiming field content and the source field content carry out fusion treatment；
In the case where the confidence level is not more than default believability threshold, handled in the source field according to default Processing Algorithm
Hold, and returns and execute the confidence level for calculating the source field content.
5. the method according to claim 1, wherein the method also includes:
Visualization projection is carried out to the source field content.
6. the method according to claim 1, wherein the method also includes:
Data label is added to fusion treatment result.
7. a kind of commercial banks data fusing device characterized by comprising
First chooses module, for choosing the target for being fused internal data from the label file of pre-generated internal data
Label file, and obtain the aiming field content of the target labels file；
Second chooses module, for generating the source label file of external data to be fused, and obtains the source of the source label file
Field contents；
Fusion treatment module, for according to preset data fusion mode to the aiming field content and the source field content into
Row fusion treatment.
8. device according to claim 7, which is characterized in that described device further include:
Quality detection module, for carrying out quality testing to the source field content according to preset data quality testing strategy；?
Quality measurements be for characterizing the first errorless result in the case where, trigger the fusion treatment module；In quality testing
As a result for for characterize mistake the second result in the case where, processing is modified to the source field content, and return to execution
It is described that quality testing is carried out to the source field content according to preset data quality testing strategy.
9. device according to claim 7, which is characterized in that described device further include:
Collision detection module, for detecting the conflicting of the aiming field content and the source field content；In the target
Field contents and the source field content trigger the fusion treatment module there is no in the case where conflict；In the target word
Section content and the source field content are deposited in the case of a conflict, handle the target word according to preset data conflict-solving strategy
Section content, and return to the conflicting for executing detection the aiming field content and the source field content.
10. device according to claim 7, which is characterized in that described device further include:
Confidence level computing module, for calculating the confidence level of the source field content；It is greater than default confidence level in the confidence level
In the case where threshold value, the fusion treatment module is triggered；In the case where the confidence level is not more than default believability threshold, press
According to the default Processing Algorithm processing source field content, and returns and execute the confidence level for calculating the source field content.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110992168A (en) * | 2019-11-29 | 2020-04-10 | 交通银行股份有限公司 | Bank internal and external data fusion method and system |
| CN111966636A (en) * | 2020-08-20 | 2020-11-20 | 中国农业银行股份有限公司 | Data file fusion method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104346377A (en) * | 2013-07-31 | 2015-02-11 | 克拉玛依红有软件有限责任公司 | Method for integrating and exchanging data on basis of unique identification |
| CN105630475A (en) * | 2014-11-06 | 2016-06-01 | 阿里巴巴集团控股有限公司 | Data label organization system and organization method |
| US20160162480A1 (en) * | 2014-12-03 | 2016-06-09 | Hans-Peter Schaerges | Adaptive computerized mapping technique in database systems |
| CN106506454A (en) * | 2016-10-10 | 2017-03-15 | 江苏通付盾科技有限公司 | Fraud business recognition method and device |
| CN106909689A (en) * | 2017-03-07 | 2017-06-30 | 山东浪潮云服务信息科技有限公司 | A kind of data fusion method and device |
| CN107704930A (en) * | 2017-09-25 | 2018-02-16 | 阿里巴巴集团控股有限公司 | Modeling method, device, system and electronic equipment based on shared data |
-
2018
- 2018-08-08 CN CN201810895683.XA patent/CN109063151B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104346377A (en) * | 2013-07-31 | 2015-02-11 | 克拉玛依红有软件有限责任公司 | Method for integrating and exchanging data on basis of unique identification |
| CN105630475A (en) * | 2014-11-06 | 2016-06-01 | 阿里巴巴集团控股有限公司 | Data label organization system and organization method |
| US20160162480A1 (en) * | 2014-12-03 | 2016-06-09 | Hans-Peter Schaerges | Adaptive computerized mapping technique in database systems |
| CN106506454A (en) * | 2016-10-10 | 2017-03-15 | 江苏通付盾科技有限公司 | Fraud business recognition method and device |
| CN106909689A (en) * | 2017-03-07 | 2017-06-30 | 山东浪潮云服务信息科技有限公司 | A kind of data fusion method and device |
| CN107704930A (en) * | 2017-09-25 | 2018-02-16 | 阿里巴巴集团控股有限公司 | Modeling method, device, system and electronic equipment based on shared data |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110992168A (en) * | 2019-11-29 | 2020-04-10 | 交通银行股份有限公司 | Bank internal and external data fusion method and system |
| CN111966636A (en) * | 2020-08-20 | 2020-11-20 | 中国农业银行股份有限公司 | Data file fusion method and device |
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| CN109063151B (en) | 2022-07-12 |
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