CN107220892A - One kind melts data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances - Google Patents
One kind melts data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances Download PDFInfo
- Publication number
- CN107220892A CN107220892A CN201710392181.0A CN201710392181A CN107220892A CN 107220892 A CN107220892 A CN 107220892A CN 201710392181 A CN201710392181 A CN 201710392181A CN 107220892 A CN107220892 A CN 107220892A
- Authority
- CN
- China
- Prior art keywords
- data
- operator
- net
- check
- magnanimity
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Economics (AREA)
- Marketing (AREA)
- Strategic Management (AREA)
- Technology Law (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
Melt data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances the invention discloses one kind, finance data can be borrowed to magnanimity P2P nets before standard financial services databases are arrived in storage, accurately and efficiently pre-processed, ensure the accuracy and validity of data, so as to set up the effective monitoring mechanism of P2P network loan platforms, effectively strengthen the supervision to P2P network loan platforms.Pretreatment includes setting up validity and completeness check rule, realizes the data check before storage；And data classification, data deduplication, data correction, data conversion, state computation, realize the data processing before storage；Most data are loaded into standard financial services databases at last.
Description
Technical field
The present invention relates to data intelligence preprocess method is melted applied to magnanimity P2P net monetary allowances, belong to massive data processing
Method field.
Background technology
In recent years, with the fast development of domestic internet finance, the internet financial platform layer of P2P network loan types
Go out not poor.According to statistics, in nationwide by the end of in by the end of July, 2016, the P2P network loan platforms set up are up to more than 5000
Family, P2P nets borrow industry history turnover and break through 2,000,000,000,000.
However, while fast development, P2P network loans constantly trigger bad credit rate height, run away the equivalent risk event that takes place frequently,
It is estimated that there are relevant issues in the platform close to half.It would therefore be highly desirable to by a unification monitor supervision platform, grasp each platform
Specific investments and debt-credit situation, form the two-way monitoring of " information flow " and " cash flow ", carry out the big number of platform transaction data
According to analysis, so as to set up the effective monitoring mechanism of P2P network loan platforms, effectively strengthen the supervision to P2P network loan platforms.
The effective monitoring and precisely analysis of extensive platform real-time transaction data are uniformly realized on single monitoring platform, just
The verification of business data completeness is needed to have, the automatic identification of the problems such as realizing mistake, lack data.Therefore, accurately and efficiently
Pretreatment is carried out to be particularly important.
The content of the invention
The invention aims to solve the above problems, propose that one kind melts data intelligence applied to magnanimity P2P net monetary allowances
The instrument and method of pretreatment, are to access the present invention be directed to the intelligent preprocess method that magnanimity P2P nets borrow finance data
Magnanimity finance data, the implementation method through intelligent preprocessing process to the whole process of business library storage.
The present invention's is applied to instrument and method that magnanimity P2P net monetary allowances melt data intelligence pretreatment, intelligence pretreatment bag
Include classification, data deduplication, data correction, format analysis processing, data conversion, state computation of each manufacturer data etc..So as to aid in using
Set up the internet data of financial transaction java standard library of specification in family.Mainly include：
1st, Various types of data completeness and efficiency verification rule is set up, the verification of data integrity and validity is realized；
2nd, pre-treatment is put in storage.
Completeness check rule mainly includes：Null value inspection, format checking etc.：
1st, null value inspection：Whether check field is empty；
2nd, format checking：Check whether the form of field conforms to the standard.
Validity check rule includes value threshold inspection, date format verification and self-defined etc.：
1st, it is worth threshold inspection：Check whether field value goes beyond the scope；
2nd, date format is verified：Whether the form of check data field meets defined form；
3rd, it is self-defined：New validity check rule is defined, operator is developed.
Storage pre-treatment includes：Data classification, data deduplication, data correction, data conversion, state computation, data loading
Deng：
1st, data are classified：By enterprise to data category filter, it is input to respective channel and carries out data prediction flow；
2nd, data deduplication：Filter out repeated data；
3rd, data correction：By rejecting, the means such as shearing are not modified to missing, form to, the data-message such as abnormal
Processing；
4th, data conversion：Different platform data type or type of transaction are inconsistent with central standard, are provided according to platform
The table of comparisons is converted into type data, such as：1 represents investment data in ant gold clothes；And regulation 2 represents investment number in java standard library
According to being now accomplished by data conversion and be adjusted.
5th, state computation：The product data (dissipate mark | financing) of P2P Wang Dai enterprises, product-specific investments and debt-credit state change are (full
Mark, fail to be sold at auction, it is overdue, refund), it is necessary to be calculated by transaction journal data.Calculation formula：
(1) full scale：Investment amount>The base number of a tender amount of money；
(2) fail to be sold at auction：Without record of making loans；
(3) it is overdue：+ 8 days opening of bid time+time limit<Current time.
6th, data are loaded：The data that loading pretreatment passes through, into business library.
The present invention is ensures high efficiency, the scalability of intelligence pretreatment, using following technological means：
1st, data prediction is using distributed processing framework in real time, the spy consumed using the batch of Distributed Message Queue
Point, by formulating and developing data integrity, validity check rule, realizes the real-time inspection to data integrity, validity
And processing；
2nd, the loose coupling of intermodule is realized by message queue, the scalability and robustness of system is improved；
3rd, operator specification and operator extension.Operator is to follow certain specification exploitation, realizes certain aspect pretreatment of data
Program bag.Such as NULLCHECK operator, the date checks operator, and codomain checks that operator, character string check that operator, mess code check operator etc..
In the present invention, such as integrality and validity check rule can be seen as the operator in streaming task, can be with
Whether " yyyy-MM-dd HH are met to such as exchange hour:mm:Ss " forms, or scattered mark state value whether 1,2,3 scope
It is interior, or the field such as user profile mess code carries out completeness and efficiency verification.It can be calculated simultaneously by developing other verification rules
Son extends validity and completeness check to data, it is only necessary to follow certain exploitation and packing specification.It is newly developed
Operator upload to system by uploading interface, you can use.In terms of operator, system possesses following function：
(1) preset Operators, such as null value check that operator, date check operator；
(2) issue operator development specifications and packing specification；
(3) operator is uploaded, is system addition and growth data pretreatment potentiality.
The advantage of the invention is that：
1st, instrument of the invention, possesses distributed treatment feature, being capable of parallel computation, efficient process；Have simultaneously fault-tolerant
System features in terms of property, expansible and persistence；
2nd, instrument of the invention, with very strong specific aim, efficiently can borrow finance data for magnanimity P2P nets and carry out intelligence
Can pretreatment, with being widely applied very much prospect.
Brief description of the drawings
Fig. 1 is that net monetary allowance melts data prediction flow；
Fig. 2 is SAMZA+KAFKA real-time processing frame structure；
Fig. 3 is the SAMZA scheduling of resource flows based on YARN；
Fig. 4 is streaming applied framework design figure；
Fig. 5 is one of the present invention and applies example.
Embodiment
Below in conjunction with accompanying drawing, the present invention is described in further detail.
It is as shown in Figure 1 that magnanimity P2P net monetary allowances melt data intelligence pretreatment process.Data access Message Queuing system first,
During pretreatment, with the role of consumer, the consumption data from message queue carries out integrality and validation verification first.If
Checking does not pass through, will be transferred to dealing of abnormal data sub-process, and borrow platform return error code to net；If the verification passes, it will turn
Enter and handle sub-process, carry out the operation such as data classification, data deduplication, data correction, data conversion, state computation, most net at last
Borrow finance data and be loaded into internet financial business storehouse.
Data prediction is using distributed processing framework in real time.By analyzing SAMZA+KAFKA, STORM and SPARK
STREAMING analysis and research, selection uses SAMZA+KAFKA real-time processing framework.KAFKA is used as a distributed message
Queue system, has been realized in many core infrastructures of Stream Processing framework bottom；And SAMZA is distributed as one
Stream data handles framework, is natively integrated with KAFKA Distributed Message Queues, and it, which is given tacit consent to, realizes it is based on KAFKA.
As shown in Fig. 2 the data integrity, validity check rule in the present invention are all located in real time as SAMZA+KAFKA
Manage a work JOB in framework.SAMZA JOB basic handling flow is a user task from one or more
Data are read in inlet flow, after certain processing, then is output in one or more output streams, is specifically mapped to KAFKA
Upper is exactly to read in data from one or more TOPIC/PARTITION, then is written out to another or multiple TOPIC/PARTITION
In；Multiple JOB, which are together in series, just completes the flow chart of data processing of streaming.
SAMZA+KAFKA this real-time tupe is somewhat like MapReduce process, STREAM importations in fact
Subregion and task (Task) number are determined by KAFKA TOPIC/PARTITION, similar to a Map process, during output by
User Task specifies TOPIC and subregion (or framework determines subregion by Key automatically), this process equivalent to a Shuffle,
When next JOB reads new STREAM, it is believed that be a Reduce, it is also assumed that being opening for next Map processes
Begin.Difference is end of the series connection between JOB without waiting for a upper JOB, and real-time message distribution mechanism is determined
The JOB entirely connected is continuous continual, that is, streaming.
SAMZA carries out resource allocation scheduling (scheduler module can be replaced, and acquiescence uses YARN) such as Fig. 3 using YARN
It is shown.SAMZA AM are responsible for JOB scheduling, and Task runner are responsible for user TASK operation, by KAFKA and YARN help,
SAMZA is achieved the characteristic in terms of its distribution/fault-tolerance/expansible/persistence.
The instrument of the present invention, user can build preprocessing tasks by graphical interfaces.It is one or more pre- by adding
Operator is handled, and configures the operational factor of each operator, a streaming task is constituted.Fig. 4 is setting for streaming application framework
Meter figure, its operational process is described as follows：
(1) operator 1 is called：Processing data is sent to topic1 as the producer；
(2) operator 2 is called：The data after data processing are obtained from topic1 as consumer and send operator 3.It is other
Operator is by that analogy.
(3) abnormal data is found：Abnormal data is sent to abnormal topic, handled by abnormality processing operator, and is borrowed to net
Platform returns to error code.
Net borrows the basic procedure of platform data pretreatment：
(1) basic data is classified by platform, and transformation rule is formulated according to each platform character；
(2) data deduplication is handled, it is to avoid enterprise repeats reported data phenomenon；
(3) net, which is borrowed, dissipates mark data mode calculating, and it is real to calculate scattered mark according to transaction journal, base number of a tender attribute, time several dimensions
Border state；
(4) dissipate mark end-state and calculate extraction；
(5) net, which is borrowed, dissipates mark trade classification, sets rule according to amount of money scope and field contents, industrial applications are stamped to scattered mark
Label；
(6) type of transaction normalizing, according to the stateful transaction specification (referring to table 1) of established a set of unified standard, to not
Calculating is normalized in stateful transaction with enterprise, is synchronized to business library；
(7) invalid data is filtered, and deletion filtering is carried out to historical test data and the expired data without transaction process；
(8) dictionary data is extracted, and data report batch code, national region code, telephone number etc..
1st, instrument of the invention, finance data is borrowed for magnanimity P2P nets, sets up validity and completeness check rule, real
Data check before being now put in storage；And data classification, data deduplication, data correction, data conversion, state computation, realize storage
Preceding data processing.
2nd, instrument of the invention, by distributed processing framework in real time, while being disappeared using the batch of Distributed Message Queue
The characteristics of taking, by formulating and developing data integrity, validity check rule, realize to data integrity, the reality of validity
When check and handle so that ensure pretreatment high efficiency, robustness and scalability.
3rd, instrument of the invention, operator definitions and implementation are the big key elements for ensureing flexibility and autgmentability.Formulate and send out
Cloth operator is developed and packing specification, the operator that preset acquiescence is realized, and can be developed and be extended according to operator specification；In this hair
In bright, such as integrality and validity check rule can be seen as the operator in streaming task, be operations in distributed task scheduling.
4th, there is provided visual modeling tool for instrument of the invention.User can build pretreatment by graphical interfaces and appoint
Business.By adding one or more preconditioning operators, and configure the operational factor of each operator, each operator completes different pre-
Processing function, constitutes a streaming task.In the present invention, operator can be dragged to by way of dragging from operator list
Workspace, and operator parameter configuration area is opened simultaneously, select and configure after multiple operators, save as a preprocessing tasks,
So as to provide preferable Consumer's Experience.
5th, instrument of the invention, basic data can be borrowed platform classification by net, borrowed platform character for different nets, formulated phase
The transformation rule answered, so that it is guaranteed that can correctly be converted into normal data from the data that different nets borrow platform.Meanwhile, it is capable to enter
Row repeated data is screened, and prevents net from borrowing platform data and repeating to report the generation of phenomenon, so that it is guaranteed that later data statistics and analysis
As a result accuracy.
6th, instrument of the invention, can complete the scattered mark data mode of net loan and calculate：According to transaction journal, base number of a tender attribute, when
Between several dimensions calculate dissipate mark virtual condition；Net can be completed and borrow scattered mark trade classification：Set according to amount of money scope and field contents
Set pattern then, industrial applications label is stamped to scattered mark；
Using example：
As shown in figure 5, each P2P nets borrow platform, such as ant gold takes, pats loan, preferably believes, by data access layer, enters
Enter KAFKA message queues.Data by the present invention provide instrument --- magnanimity P2P net monetary allowances melt data prediction, pass through number
According to loading, into standard financial services databases.
Table 1 --- stateful transaction specification sheet：
Claims (7)
1. one kind melts data intelligence preprocess method applied to magnanimity P2P net monetary allowances, it is characterised in that data access message queue
System, carries out data prediction, with the role of consumer, the consumption data from message queue, carries out integrality and validity is tested
Card, if checking does not pass through, is transferred to dealing of abnormal data sub-process, and borrows platform return error code to net, if the verification passes,
Processing sub-process is transferred to, storage pre-treatment is carried out, data classification, data deduplication, data correction, data conversion, state meter is carried out
Calculate, data are loaded, most net borrows finance data and is loaded into internet financial business storehouse at last.
2. the integrity verification function described in claim 1 includes, null value inspection and format checking, null value inspection refer to check word
Whether section is empty, and format checking refers to whether the form for checking field conforms to the standard.
3. the validation verification function described in claim 1 includes the inspection of value threshold, date format verification and self-defined validity school
Test, value threshold inspection refers to check whether field value goes beyond the scope, date format verification refers to that the form of check data field is
Form as defined in no satisfaction, self-defined validity check refers to customized validity check rule.
4. the storage pre-treatment described in claim 1, specifically comprising following committed step：
(1) data are classified：By enterprise to data category filter, it is input to respective channel and carries out data prediction flow；
(2) data deduplication：Filter out repeated data；
(3) data correction：Processing is not modified to, abnormal data message to missing, form；
(4) data conversion：Different platform data type or type of transaction and central standard are inconsistent, the control provided according to platform
Table is converted into type data.
(5) state computation：The product data (dissipate mark | financing) of P2P Wang Dai enterprises, product-specific investments and debt-credit state change (full scale,
Fail to be sold at auction, it is overdue, refund), it is necessary to be calculated by transaction journal data, calculation formula：
<1>Full scale：Investment amount>The base number of a tender amount of money；
<2>Fail to be sold at auction：Without record of making loans；
<3>It is overdue：+ 8 days opening of bid time+time limit<Current time；
(6) data are loaded：The data that loading pretreatment passes through, into business library.
5. the data prediction described in claim 1 is using distributed processing framework in real time, i.e., using the real-time of SAMZA+KAFKA
Handle framework.
6. one kind melts data intelligence pretreating tool applied to magnanimity P2P net monetary allowances, task is built by graphical interfaces, added many
Individual operator, and the operational factor of each operator is configured, a streaming task is constituted, data prediction, logarithm are realized by operator
According to integrality and validation verification is carried out, if checking does not pass through, dealing of abnormal data is carried out, borrowing platform to net returns to mistake
Code, if the verification passes, data classification, data deduplication, data correction, data conversion, state computation, data is realized by algorithm
Loading, finally borrows finance data by net and is loaded into internet financial business storehouse.
7. the operator described in claim 6, which includes NULLCHECK operator, date, checks that operator, codomain check operator, character string inspection
Operator, mess code check operator etc..Meanwhile, user can develop according to operator specification and apply new operator.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710392181.0A CN107220892B (en) | 2017-05-27 | 2017-05-27 | Intelligent preprocessing tool and method applied to massive P2P network loan financial data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710392181.0A CN107220892B (en) | 2017-05-27 | 2017-05-27 | Intelligent preprocessing tool and method applied to massive P2P network loan financial data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107220892A true CN107220892A (en) | 2017-09-29 |
| CN107220892B CN107220892B (en) | 2020-10-16 |
Family
ID=59946751
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710392181.0A Active CN107220892B (en) | 2017-05-27 | 2017-05-27 | Intelligent preprocessing tool and method applied to massive P2P network loan financial data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107220892B (en) |
Cited By (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108154431A (en) * | 2018-01-17 | 2018-06-12 | 北京网信云服信息科技有限公司 | A kind of target raises condition processing method and device |
| CN108446973A (en) * | 2018-02-28 | 2018-08-24 | 四川新网银行股份有限公司 | Credit solution on a kind of conventional banking facilities line based on finance opening platform |
| CN109635162A (en) * | 2018-12-18 | 2019-04-16 | 北京九章云极科技有限公司 | A kind of data processing system and method |
| CN110020952A (en) * | 2019-04-12 | 2019-07-16 | 李升东 | A kind of finance data processing method and device |
| CN111047431A (en) * | 2019-12-11 | 2020-04-21 | 深圳微众信用科技股份有限公司 | Credit service processing device, method and equipment based on big data |
| CN111382579A (en) * | 2020-01-13 | 2020-07-07 | 中船第九设计研究院工程有限公司 | Data preprocessing verification platform of ship pipeline manufacturing execution system |
| CN111724178A (en) * | 2019-03-18 | 2020-09-29 | 河南省技术产权交易所有限公司 | Intellectual property entrusting quotation method, system and computer readable storage medium |
| CN112527820A (en) * | 2020-12-09 | 2021-03-19 | 航天信息股份有限公司广州航天软件分公司 | Method and system for carrying out unified verification on various types of service application data |
| CN112632169A (en) * | 2020-12-29 | 2021-04-09 | 永辉云金科技有限公司 | Automatic financial data reporting method and device and computer equipment |
| CN113239188A (en) * | 2021-04-21 | 2021-08-10 | 上海快确信息科技有限公司 | Financial transaction conversation information analysis technical scheme |
| CN115242349A (en) * | 2022-06-21 | 2022-10-25 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method and device, computer equipment and storage medium |
| CN115391838A (en) * | 2022-10-27 | 2022-11-25 | 湖南三湘银行股份有限公司 | Data interaction service platform based on trusted prediction machine |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102693508A (en) * | 2012-05-11 | 2012-09-26 | 杭州商友全球网信息技术有限公司 | Data processing method for bank loan application management |
| CN103605512A (en) * | 2013-11-05 | 2014-02-26 | 广东电网公司电力科学研究院 | System and method for data verification based on GTechnology platform |
| CN104463662A (en) * | 2014-12-02 | 2015-03-25 | 山东中创软件工程股份有限公司 | Financial data calculation method and device |
| CN105512937A (en) * | 2015-12-18 | 2016-04-20 | 中国建设银行股份有限公司 | Payment data processing method and deposit storage system |
| US20160203461A1 (en) * | 2011-06-17 | 2016-07-14 | Chicago Mercantile Exchange Inc. | Facilitation of payments between counterparties by a central counterparty |
| CN106254543A (en) * | 2016-09-27 | 2016-12-21 | 盐城工学院 | Distributed interconnection Network and Finance Network based on cloud computing framework borrows method and system |
| CN106600369A (en) * | 2016-12-09 | 2017-04-26 | 广东奡风科技股份有限公司 | Real-time recommendation system and method of financial products of banks based on Naive Bayesian classification |
| EP3166065A1 (en) * | 2015-11-04 | 2017-05-10 | Validus Services (Bermuda) Ltd | Portfolio optimization and evaluation tool |
-
2017
- 2017-05-27 CN CN201710392181.0A patent/CN107220892B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160203461A1 (en) * | 2011-06-17 | 2016-07-14 | Chicago Mercantile Exchange Inc. | Facilitation of payments between counterparties by a central counterparty |
| CN102693508A (en) * | 2012-05-11 | 2012-09-26 | 杭州商友全球网信息技术有限公司 | Data processing method for bank loan application management |
| CN103605512A (en) * | 2013-11-05 | 2014-02-26 | 广东电网公司电力科学研究院 | System and method for data verification based on GTechnology platform |
| CN104463662A (en) * | 2014-12-02 | 2015-03-25 | 山东中创软件工程股份有限公司 | Financial data calculation method and device |
| EP3166065A1 (en) * | 2015-11-04 | 2017-05-10 | Validus Services (Bermuda) Ltd | Portfolio optimization and evaluation tool |
| CN105512937A (en) * | 2015-12-18 | 2016-04-20 | 中国建设银行股份有限公司 | Payment data processing method and deposit storage system |
| CN106254543A (en) * | 2016-09-27 | 2016-12-21 | 盐城工学院 | Distributed interconnection Network and Finance Network based on cloud computing framework borrows method and system |
| CN106600369A (en) * | 2016-12-09 | 2017-04-26 | 广东奡风科技股份有限公司 | Real-time recommendation system and method of financial products of banks based on Naive Bayesian classification |
Non-Patent Citations (3)
| Title |
|---|
| 张前进: "基于Storm的物联网海量实时数据流处理研究", 《常州工学院学报》 * |
| 易佳 等: "分布式流数据加载和查询技术优化", 《计算机科学》 * |
| 郑文俊 等: "大并发、高吞吐量实时数据平台的研究", 《电信快报》 * |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108154431A (en) * | 2018-01-17 | 2018-06-12 | 北京网信云服信息科技有限公司 | A kind of target raises condition processing method and device |
| CN108154431B (en) * | 2018-01-17 | 2021-07-06 | 北京网信云服信息科技有限公司 | Target recruitment state processing method and device |
| CN108446973A (en) * | 2018-02-28 | 2018-08-24 | 四川新网银行股份有限公司 | Credit solution on a kind of conventional banking facilities line based on finance opening platform |
| CN109635162A (en) * | 2018-12-18 | 2019-04-16 | 北京九章云极科技有限公司 | A kind of data processing system and method |
| CN111724178A (en) * | 2019-03-18 | 2020-09-29 | 河南省技术产权交易所有限公司 | Intellectual property entrusting quotation method, system and computer readable storage medium |
| CN110020952A (en) * | 2019-04-12 | 2019-07-16 | 李升东 | A kind of finance data processing method and device |
| CN111047431A (en) * | 2019-12-11 | 2020-04-21 | 深圳微众信用科技股份有限公司 | Credit service processing device, method and equipment based on big data |
| CN111382579A (en) * | 2020-01-13 | 2020-07-07 | 中船第九设计研究院工程有限公司 | Data preprocessing verification platform of ship pipeline manufacturing execution system |
| CN112527820B (en) * | 2020-12-09 | 2024-04-09 | 航天信息股份有限公司广州航天软件分公司 | Method and system for uniformly checking various service application data |
| CN112527820A (en) * | 2020-12-09 | 2021-03-19 | 航天信息股份有限公司广州航天软件分公司 | Method and system for carrying out unified verification on various types of service application data |
| CN112632169A (en) * | 2020-12-29 | 2021-04-09 | 永辉云金科技有限公司 | Automatic financial data reporting method and device and computer equipment |
| CN113239188A (en) * | 2021-04-21 | 2021-08-10 | 上海快确信息科技有限公司 | Financial transaction conversation information analysis technical scheme |
| CN115242349A (en) * | 2022-06-21 | 2022-10-25 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method and device, computer equipment and storage medium |
| CN115242349B (en) * | 2022-06-21 | 2023-11-14 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method, enterprise-level data verification device, computer equipment and storage medium |
| CN115391838A (en) * | 2022-10-27 | 2022-11-25 | 湖南三湘银行股份有限公司 | Data interaction service platform based on trusted prediction machine |
| CN115391838B (en) * | 2022-10-27 | 2023-02-28 | 湖南三湘银行股份有限公司 | Data interaction service platform based on trusted prediction machine |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107220892B (en) | 2020-10-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107220892A (en) | One kind melts data intelligence pretreating tool and method applied to magnanimity P2P net monetary allowances | |
| CN104144204B (en) | A kind of method and system for the simulation for carrying out industrial automation system | |
| US11436550B2 (en) | Cash forecast system, apparatus, and method | |
| CN107220217A (en) | Characteristic coefficient training method and device that logic-based is returned | |
| CN108229828A (en) | A kind of analysis system based on industrial data | |
| CN107077114A (en) | Soft sensor is used in programmable logic controller (PLC) | |
| CN110389748A (en) | Business data processing method and terminal device | |
| CN106852177B (en) | System and method for pattern recognition based monitoring and controlled processing of data objects based on consistency measurements | |
| Achar | Early Consequences Regarding the Impact of Artificial Intelligence on International Trade | |
| CN109285071A (en) | A kind of data processing platform (DPP) and data processing method based on block chain | |
| CN110503551A (en) | A kind of network funds transaction channel maintaining method, device and equipment | |
| CN110189220A (en) | A kind of risk analysis decision-making technique, device, system and storage medium | |
| CN115423289B (en) | Intelligent plate processing workshop data processing method and terminal | |
| CN103095808A (en) | Execution method of computer integrated manufacturing based on cloud manufacturing and system thereof | |
| Adams et al. | A framework for extracting and encoding features from object-centric event data | |
| CN106383916A (en) | Data processing method based on predictive maintenance of industrial equipment | |
| CN113379530A (en) | User risk determination method and device and server | |
| CN110502395A (en) | Equipment running status appraisal procedure, terminal device and storage medium based on cluster | |
| CN109588054A (en) | Accurate and detailed modeling using distributed simulation engine to the system with large complicated data set | |
| Muñoz et al. | Ontological framework for the enterprise from a process perspective | |
| CN115562199A (en) | Industrial internet operating system and product processing method | |
| Ladva et al. | An Analysis on various Machine Learning Algorithms (AI) & Nature Inspired Algorithms for modern Inventory Management | |
| CA3211789A1 (en) | Computer-implemented methods referring to an industrial process for manufacturing a product and system for performing said methods | |
| CN112801798A (en) | Method, system and equipment for analyzing influence propagation and identifying pattern of associated network | |
| Durand et al. | Determination of storage tanks location for optimal short-term scheduling in multipurpose/multiproduct batch-continuous plants under uncertainties |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |