CN112597468A - Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence - Google Patents
Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence Download PDFInfo
- Publication number
- CN112597468A CN112597468A CN202011566412.3A CN202011566412A CN112597468A CN 112597468 A CN112597468 A CN 112597468A CN 202011566412 A CN202011566412 A CN 202011566412A CN 112597468 A CN112597468 A CN 112597468A
- Authority
- CN
- China
- Prior art keywords
- user
- data interface
- information
- verification
- data
- 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.)
- Pending
Links
- 238000007726 management method Methods 0.000 title claims abstract description 40
- 238000013473 artificial intelligence Methods 0.000 title claims abstract description 34
- 238000012015 optical character recognition Methods 0.000 title description 28
- 238000000034 method Methods 0.000 claims abstract description 25
- 238000012795 verification Methods 0.000 claims description 156
- 230000000694 effects Effects 0.000 claims description 54
- 238000004364 calculation method Methods 0.000 claims description 12
- 230000005540 biological transmission Effects 0.000 claims description 10
- 238000005070 sampling Methods 0.000 claims description 10
- 238000003062 neural network model Methods 0.000 claims description 9
- 230000003203 everyday effect Effects 0.000 claims description 7
- 238000013507 mapping Methods 0.000 claims description 6
- 238000009417 prefabrication Methods 0.000 abstract description 5
- 230000009286 beneficial effect Effects 0.000 description 12
- 238000005516 engineering process Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000012423 maintenance Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 241000282414 Homo sapiens Species 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/31—User authentication
- G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2221/00—Indexing scheme relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/21—Indexing scheme relating to G06F21/00 and subgroups addressing additional information or applications relating to security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F2221/2137—Time limited access, e.g. to a computer or data
Abstract
The invention provides a data interface management method and a system based on stroke order, OCR and artificial intelligence, wherein the method comprises the following steps: constructing a first data interface library, prefabricating at least one first data interface, configuring interface parameters of the first data interface, and configuring a second data interface for a first user; the second data interface is only connected with the authority database; receiving handwriting information input by a first user through a second data interface; determining first user permission information of a first user based on the handwriting information; and configuring a first data interface corresponding to the first user authority information for the first user from the first data interface library. The data interface management method based on the stroke order, the OCR and the artificial intelligence constructs a data interface library, performs prefabrication of data interfaces, configures the data interfaces of corresponding authorities based on the authorities of the first user, and manages and ensures the safety of data access of the database based on the data interfaces of the stroke order, the OCR and the artificial intelligence.
Description
Technical Field
The invention relates to the technical field of database management, in particular to a data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence.
Background
At present, big data is a product of a new generation of information technology after cloud computing, the internet of things and mobile internet, and the big data is becoming a new hotspot and a new direction of the information technology and has great influence on the production and life of human beings. The database provides access for a first user through a data interface, and how to ensure the safe access of the database of the large data platform through the management of the data interface is an urgent problem to be solved.
Disclosure of Invention
One of the purposes of the invention is to provide a data interface management method based on the stroke order, the OCR and the artificial intelligence, which comprises the steps of constructing a data interface library, prefabricating a data interface, configuring a data interface of a corresponding authority based on the authority of a first user, and managing and ensuring the safety of data access of the database based on the data interface based on the stroke order, the OCR and the artificial intelligence.
The embodiment of the invention provides a data interface management method based on stroke order, OCR and artificial intelligence, which comprises the following steps:
constructing a first data interface library, prefabricating at least one first data interface, and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
configuring a second data interface for the first user; the second data interface is only connected with the authority database;
receiving handwriting information input by a first user through a second data interface;
determining first user permission information of a first user based on the handwriting information;
and configuring a first data interface corresponding to the first user authority information for the first user from the first data interface library, and simultaneously canceling a second data interface used by the first user and storing the second data interface into the second data interface library.
Preferably, the data interface management method based on stroke order, OCR and artificial intelligence further includes:
configuring a second data interface for a first user configured with a first data interface every a preset first time period;
receiving handwriting information input by a first user through a second interface;
verifying the identity of the first user;
when the verification fails or exceeds the preset verification time, mapping the first data interface to a to-be-secondarily-distributed list; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
Preferably, when the second data interface is configured for the second user every a preset first time period, and the note information input by the second user is received, the method further includes:
receiving a secondary allocation request for the first data interface input by a second user;
acquiring a first authority value corresponding to a first data interface used by a current second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using a target interface;
acquiring second user authority information and/or second liveness of a second user;
performing secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity degree, the second user permission information and/or the second activity degree;
the secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user authority information and/or the first activity, the second user authority information and/or the second activity comprises the following steps:
when the second authority value of the second user authority information is larger than the first authority value of the first user authority information, configuring a first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
and when the second activity of the second user is greater than the first activity of the first user, configuring the first data interface used by the first user in the secondary allocation list to be used by the second user.
Preferably, the step of determining the second activity is as follows:
acquiring the historical login condition of a second user;
analyzing the historical login condition, and acquiring login days of the user in a preset time period away from the current time, login time each day and a list of data in a database called during login each day;
correcting the login time of each day based on the data in the list and a preset comparison table of calling data and time, and determining effective time; the method comprises the following specific steps: counting the total calling time of the data in the calling list, and taking the login time of each day as effective time when the total calling time is more than or equal to the login time of each day; when the total calling time is less than or equal to the login time every day, taking the total calling time as the effective time;
determining the activity of the user based on the effective time of the current user, the total effective time of all the users, the login days of the current user and the days corresponding to the preset time period, wherein the calculation formula is as follows:
wherein HkActivity for the kth user in big data platforms, DkThe login days of the kth user; d0The number of days corresponding to the preset time period; b iskThe valid time of the kth user; m is the number of users of the big data platform; epsilon1、ε2Is a predetermined weight.
Preferably, the first user permission information of the first user is determined based on the handwriting information; the method comprises the following steps:
analyzing the note information to obtain stroke order information and identification information;
determining an identity of the first user based on the identification information;
calling a preset verification model based on the identity of the first user;
verifying the identity of the first user based on the verification model, and acquiring the authority information of the first user when the verification is passed;
wherein verifying the identity of the first user based on the verification model comprises:
extracting a characteristic value of stroke order information and/or identification information, substituting the characteristic value into a pre-established neural network model to obtain a verification factor, inquiring a preset verification table, and passing the verification when the verification factor exists in the verification table;
or the like, or, alternatively,
constructing a verification vector based on the stroke order information and/or the identification information, matching the verification vector with a standard vector in a pre-established verification library, and passing the verification when the matching degree of the verification vector and the standard vector is greater than a preset matching value;
the matching degree calculation formula of the verification vector and the standard vector is as follows:
wherein, PqMatching degree of the verification vector and the qth standard vector in the verification library; n is the dimension of the verification vector and the standard vector; a isi,qIs the ith dimension data value of the qth standard vector; biAn ith dimension data value that is a verification vector;
the stroke order information includes: one or more of the types of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined;
the parameter information of each stroke includes: the handwriting intensity parameter comprises a starting point, an end point, position relation parameters among a preset number of sampling points among the starting point and the end point of each stroke, and/or handwriting intensity parameters of a preset number of sampling points among the starting point, the end point, the starting point and the end point of each stroke;
the identification information includes: one or more of characters, figures and symbols.
The invention also provides a data interface management system based on stroke order, OCR and artificial intelligence, comprising:
the building module is used for building a first data interface library, prefabricating at least one first data interface and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
the first configuration module is used for configuring a second data interface for a first user; the second data interface is only connected with the authority database;
the first input module is used for receiving handwriting information input by a first user through a second data interface;
the authority acquisition module is used for determining first user authority information of a first user based on the handwriting information;
and the second configuration module is used for configuring a first data interface corresponding to the first user permission information for the first user from the first data interface library, and simultaneously canceling a second data interface used by the first user and storing the second data interface into the second data interface library.
Preferably, the data interface management system based on the stroke order, the OCR and the artificial intelligence further comprises: a verification module that performs the following operations:
configuring a second data interface for a first user configured with a first data interface every a preset first time period;
receiving handwriting information input by a first user through a second interface;
verifying the identity of the first user;
when the verification fails or exceeds the preset verification time, mapping the first data interface to a to-be-secondarily-distributed list; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
Preferably, the data interface management system based on the stroke order, the OCR and the artificial intelligence further comprises: the secondary distribution module is used for configuring a second data interface for the second user at intervals of a preset first time period and executing the following operations when receiving the note information input by the second user:
receiving a secondary allocation request for the first data interface input by a second user;
acquiring a first authority value corresponding to a first data interface used by a current second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using a target interface;
acquiring second user authority information and/or second liveness of a second user;
performing secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity degree, the second user permission information and/or the second activity degree;
the secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user authority information and/or the first activity, the second user authority information and/or the second activity comprises the following steps:
when the second authority value of the second user authority information is larger than the first authority value of the first user authority information, configuring a first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
and when the second activity of the second user is greater than the first activity of the first user, configuring the first data interface used by the first user in the secondary allocation list to be used by the second user.
Preferably, the step of determining the second activity is as follows:
acquiring the historical login condition of a second user;
analyzing the historical login condition, and acquiring login days of the user in a preset time period away from the current time, login time each day and a list of data in a database called during login each day;
correcting the login time of each day based on the data in the list and a preset comparison table of calling data and time, and determining effective time; the method comprises the following specific steps: counting the total calling time of the data in the calling list, and taking the login time of each day as effective time when the total calling time is more than or equal to the login time of each day; when the total calling time is less than or equal to the login time every day, taking the total calling time as the effective time;
determining the activity of the user based on the effective time of the current user, the total effective time of all the users, the login days of the current user and the days corresponding to the preset time period, wherein the calculation formula is as follows:
wherein HkActivity for the kth user in big data platforms, DkThe login days of the kth user; d0The number of days corresponding to the preset time period; b iskThe valid time of the kth user; m is the number of users of the big data platform; epsilon1、ε2Is a predetermined weight.
Preferably, the right acquiring module performs the following operations:
analyzing the note information to obtain stroke order information and identification information;
determining an identity of the first user based on the identification information;
calling a preset verification model based on the identity of the first user;
verifying the identity of the first user based on the verification model, and acquiring the authority information of the first user when the verification is passed;
wherein verifying the identity of the first user based on the verification model comprises:
extracting a characteristic value of stroke order information and/or identification information, substituting the characteristic value into a pre-established neural network model to obtain a verification factor, inquiring a preset verification table, and passing the verification when the verification factor exists in the verification table;
or the like, or, alternatively,
constructing a verification vector based on the stroke order information and/or the identification information, matching the verification vector with a standard vector in a pre-established verification library, and passing the verification when the matching degree of the verification vector and the standard vector is greater than a preset matching value;
the matching degree calculation formula of the verification vector and the standard vector is as follows:
wherein, PqMatching degree of the verification vector and the qth standard vector in the verification library; n is the dimension of the verification vector and the standard vector; a isi,qIs the ith dimension data value of the qth standard vector; biAn ith dimension data value that is a verification vector;
the stroke order information includes: one or more of the types of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined;
the parameter information of each stroke includes: the handwriting intensity parameter comprises a starting point, an end point, position relation parameters among a preset number of sampling points among the starting point and the end point of each stroke, and/or handwriting intensity parameters of a preset number of sampling points among the starting point, the end point, the starting point and the end point of each stroke;
the identification information includes: one or more of characters, figures and symbols.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a diagram illustrating a rights management method according to an embodiment of the invention;
FIG. 2 is a diagram illustrating another rights management method according to an embodiment of the invention;
fig. 3 is a schematic diagram of a rights management system according to an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
The embodiment of the invention provides a data interface management method based on stroke order, OCR and artificial intelligence, as shown in FIG. 1, comprising the following steps:
step S1: constructing a first data interface library, prefabricating at least one first data interface, and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
step S2: configuring a second data interface for the first user; the second data interface is only connected with the authority database;
step S3: receiving handwriting information input by a first user through a second data interface;
step S4: determining first user permission information of a first user based on the handwriting information;
step S5: and configuring a first data interface corresponding to the first user authority information for the first user from the first data interface library, and simultaneously canceling a second data interface used by the first user and storing the second data interface into the second data interface library.
The working principle and the beneficial effects of the technical scheme are as follows:
the method comprises the steps that a data interface library is established for a database, a first data interface is prefabricated in the data interface library, interface parameters of the first data interface are configured, the first data interface is numbered during configuration, the first data interface can be numbered according to interface authorities of the first data interface, namely the number with the highest authority is 1, and then numbering is carried out according to the authorities in sequence; certainly, when the data source is configured, the interfaces with higher authority can access more data sources, the data with higher data security level is stored in the corresponding data source, and the access interfaces of the data source are relatively less in setting, so that the monitoring of the data interface of the data source is facilitated; during configuration, the transmission speed can be configured according to the level of the authority, namely the higher the authority is, the higher the transmission speed of the interface is; the number of the prefabricated interfaces can be configured according to the allowable access speed of the database, namely the sum of the maximum limit speeds of all the data interfaces is lower than the maximum speed of the allowable access of the database, so that the data streaming network attack can be effectively avoided, namely the database does not exceed the load when all the data interfaces operate at the maximum speed. When the first user uses the database, the first user accesses the permission database in the database through the second data interface, the first user permission information of the first user is determined in a handwriting information verification mode, after the first user permission information is determined, a data interface corresponding to the permission is configured for the first user from the data interface database, reasonable control of the data interface is achieved through prefabrication of the data interface and permission configuration, and therefore the flow of data in the database accessed through the data interface is guaranteed not to be higher than the allowable range of the database, and the safety of data access of the database is guaranteed. The second data interface is also configured according to the permission of the permission database, namely the quantity of the second data interfaces which exist at the same time is ensured not to exceed the load of the permission database; after the first data interface is configured, the second data interface of the first user with the first data interface configured is cancelled. According to the method and the system, the intelligent education platform provides the public data WCF interfaces such as unified subjects, versions, book sections and knowledge points for the whole platform, and rapid configuration and personalized customization of the data interfaces are provided; in addition, the interfaces and the services provide an API based on an REST framework for the system, and a butt-jointed client system can access application scenes such as service program meeting summary merging, intelligent education and the like through a universal interface of an HTTP application protocol by depending on the data interface, so that the cross-module data interconnection and intercommunication are effectively supported, and unified maintenance and management can be conveniently carried out.
The data interface management method based on the stroke order, the OCR and the artificial intelligence constructs a data interface library, performs prefabrication of data interfaces, configures the data interfaces of corresponding authorities based on the authorities of the first user, and ensures the safety of data access of the database through the data interface management based on the stroke order, the OCR and the artificial intelligence.
In one embodiment, the data interface management method based on stroke order, OCR and artificial intelligence, as shown in fig. 2, further includes:
step S11: configuring a second data interface for a first user configured with a first data interface every a preset first time period;
step S12: receiving handwriting information input by a first user through a second interface;
step S13: verifying the identity of the first user;
step S14: when the verification fails or exceeds the preset verification time, mapping the first data interface to a to-be-secondarily-distributed list; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
The working principle and the beneficial effects of the technical scheme are as follows:
when the intelligent education data platform is in application operation, in order to achieve reasonable configuration of the first data interface, the first user configured with the first data interface is subjected to identity verification after every preset first time period, the identity of a use object of the first data interface is confirmed, the first data interface which fails in verification is subjected to secondary distribution, the utilization rate of the first data interface with high authority is guaranteed, and management of the data interface is optimized.
In one embodiment, when the second data interface is configured for the second user every preset first time period and the note information input by the second user is received, the method further includes:
receiving a secondary allocation request for the first data interface input by a second user;
acquiring a first authority value corresponding to a first data interface used by a current second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using a target interface;
acquiring second user authority information and/or second liveness of a second user;
performing secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity degree, the second user permission information and/or the second activity degree;
the secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user authority information and/or the first activity, the second user authority information and/or the second activity comprises the following steps:
when the second authority value of the second user authority information is larger than the first authority value of the first user authority information, configuring a first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
and when the activity of the second user is greater than that of the first user, configuring the first data interface used by the first user in the secondary distribution list as the second user.
The working principle and the beneficial effects of the technical scheme are as follows:
when the intelligent education data platform is in application operation, a secondary distribution mechanism is implemented on the first data interface, reasonable utilization of the first data interface with high authority is guaranteed, namely when a user who logs in previously uses the first data interface with the highest authority, the user does not log in, so that the highest authority is always used, and when an account which logs in later wants to use the highest authority, the user can obtain the first data interface through the secondary distribution mechanism. And after the secondary distribution is successful, when the original user operates, the configuration of the first data interface is carried out again.
In one embodiment, the second activity is determined by the steps of:
acquiring the historical login condition of a second user;
analyzing the historical login condition, and acquiring login days of the user in a preset time period away from the current time, login time each day and a list of data in a database called during login each day;
correcting the login time of each day based on the data in the list and a preset comparison table of calling data and time, and determining effective time; the method comprises the following specific steps: counting the total calling time of the data in the calling list, and taking the login time of each day as effective time when the total calling time is more than or equal to the login time of each day; when the total calling time is less than or equal to the login time every day, taking the total calling time as the effective time;
determining the activity of the user based on the effective time of the current user, the total effective time of all the users, the login days of the current user and the days corresponding to the preset time period, wherein the calculation formula is as follows:
wherein HkActivity for the kth user in big data platforms, DkNumber of login days for kth user；D0The number of days corresponding to the preset time period; b iskThe valid time of the kth user; m is the number of users of the big data platform; epsilon1、ε2Is a predetermined weight.
The working principle and the beneficial effects of the technical scheme are as follows:
the method has the advantages that the activity calculation is carried out on the user based on the login days and the effective login time every day, the accuracy of the activity is guaranteed, in addition, the effective time is introduced, the influence of no operation time of the user is eliminated through correcting the login time by the data called when the user logs in every time, and the activity is more accurate and objective. Similarly, the first activity level determining step is the same as the second activity level determining step.
In one embodiment, the data interface management method based on stroke order, OCR and artificial intelligence further comprises:
acquiring first equipment information and first user permission information of a terminal used by a first user;
acquiring second device information and interface authority information which are allowed to be accessed of a first data interface;
constructing a login vector based on the first device information and the first authority information;
constructing an interface vector based on the second device information and the interface authority information;
and calculating the similarity between the login vector and the interface vector, and configuring the first data interface with the maximum similarity to the first user for use.
The working principle and the beneficial effects of the technical scheme are as follows:
and introducing equipment information, participating in the configuration of the first data interface, and considering the compatibility of the first data interface and the terminal to realize the rationality of the configuration of the first data interface.
Wherein the first device information or the second device information includes: voltage of the device, current of the device, model number of each component in the device, upload speed of the device, and download speed of the device.
In one embodiment, first user permission information of a first user is determined based on handwriting information; the method comprises the following steps:
analyzing the note information to obtain stroke order information and identification information;
determining an identity of the first user based on the identification information;
calling a preset verification model based on the identity of the first user;
verifying the identity of the first user based on the verification model, and acquiring the authority information of the first user when the verification is passed;
wherein verifying the identity of the first user based on the verification model comprises:
extracting a characteristic value of stroke order information and/or identification information, substituting the characteristic value into a pre-established neural network model to obtain a verification factor, inquiring a preset verification table, and passing the verification when the verification factor exists in the verification table;
or the like, or, alternatively,
constructing a verification vector based on the stroke order information and/or the identification information, matching the verification vector with a standard vector in a pre-established verification library, and passing the verification when the matching degree of the verification vector and the standard vector is greater than a preset matching value;
the matching degree calculation formula of the verification vector and the standard vector is as follows:
wherein, PqMatching degree of the verification vector and the qth standard vector in the verification library; n is the dimension of the verification vector and the standard vector; a isi,qIs the ith dimension data value of the qth standard vector; biAn ith dimension data value that is a verification vector;
the stroke order information includes: one or more of the types of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined;
the parameter information of each stroke includes: the handwriting intensity parameter comprises a starting point, an end point, position relation parameters among a preset number of sampling points among the starting point and the end point of each stroke, and/or handwriting intensity parameters of a preset number of sampling points among the starting point, the end point, the starting point and the end point of each stroke;
the identification information includes: one or more of characters, figures and symbols.
The working principle and the beneficial effects of the technical scheme are as follows:
the method includes the steps of firstly, determining the identity of a first user through identification information of note information identified by an OCR (Optical Character Recognition) identification technology, then calling a verification model stored corresponding to the identity of the first user for identity verification, and obtaining authority information of the first user after verification is passed. According to the first scheme, a pre-trained neural network model is adopted, characteristic values of stroke order information and/or identification information are extracted and input into the neural network model, a verification factor is obtained, and a final verification result is determined based on the verification factor. And a second scheme is that a pre-established verification library is adopted, a verification vector is constructed based on the stroke order information and/or the identification information, the verification vector is matched with a standard vector in the verification library, and verification is performed through a matching result. Furthermore, the stroke order information and the identification information are integrated, so that the verification precision is improved, namely the self-definition of the first user is realized according to the stroke order as a verification point instead of the standard when the characters are written, the verification granularity is improved, and the self-defined operability of the first user is realized. In addition, the handwriting dynamics parameters among strokes are considered, the recognition of the same stroke written by different people in the same character is realized, and the recognition degree of personnel on the basis of stroke order information and recognition information schemes is improved.
The present invention also provides a data interface management system based on stroke order, OCR and artificial intelligence, as shown in fig. 3, including:
the building module 1 is used for building a first data interface library, prefabricating at least one first data interface, and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
the first configuration module 2 is used for configuring a second data interface for a first user; the second data interface is only connected with the authority database;
the first input module 3 is used for receiving handwriting information input by a first user through a second data interface;
the authority acquiring module 4 is used for determining first user authority information of a first user based on the handwriting information;
and the second configuration module 5 is configured to configure a first data interface corresponding to the first user permission information for the first user from the first data interface library, and simultaneously cancel a second data interface used by the first user and store the second data interface into the second data interface library.
The working principle and the beneficial effects of the technical scheme are as follows:
the method comprises the steps that a data interface library is established for a database, a first data interface is prefabricated in the data interface library, interface parameters of the first data interface are configured, the first data interface is numbered during configuration, the first data interface can be numbered according to interface authorities of the first data interface, namely the number with the highest authority is 1, and then numbering is carried out according to the authorities in sequence; certainly, when the data source is configured, the interfaces with higher authority can access more data sources, the data with higher data security level is stored in the corresponding data source, and the access interfaces of the data source are relatively less in setting, so that the monitoring of the data interface of the data source is facilitated; during configuration, the transmission speed can be configured according to the level of the authority, namely the higher the authority is, the higher the transmission speed of the interface is; the number of the prefabricated interfaces can be configured according to the allowable access speed of the database, namely the sum of the maximum limit speeds of all the data interfaces is lower than the maximum speed of the allowable access of the database, so that the data streaming network attack can be effectively avoided, namely the database does not exceed the load when all the data interfaces operate at the maximum speed. When the first user uses the database, the first user accesses the permission database in the database through the second data interface, the first user permission information of the first user is determined in a handwriting information verification mode, after the first user permission information is determined, a data interface corresponding to the permission is configured for the first user from the data interface database, reasonable control of the data interface is achieved through prefabrication of the data interface and permission configuration, and therefore the flow of data in the database accessed through the data interface is guaranteed not to be higher than the allowable range of the database, and the safety of data access of the database is guaranteed. The second data interface is also configured according to the permission of the permission database, namely the quantity of the second data interfaces which exist at the same time is ensured not to exceed the load of the permission database; after the first data interface is configured, the second data interface of the first user with the first data interface configured is cancelled. According to the method and the system, the intelligent education platform provides the public data WCF interfaces such as unified subjects, versions, book sections and knowledge points for the whole platform, and rapid configuration and personalized customization of the data interfaces are provided; in addition, the interfaces and the services provide an API based on an REST framework for the system, and a butt-jointed client system can access application scenes such as service program meeting summary merging, intelligent education and the like through a universal interface of an HTTP application protocol by depending on the data interface, so that the cross-module data interconnection and intercommunication are effectively supported, and unified maintenance and management can be conveniently carried out.
The data interface management method based on the stroke order, the OCR and the artificial intelligence constructs a data interface library, performs prefabrication of data interfaces, configures the data interfaces of corresponding authorities based on the authorities of the first user, and ensures the safety of data access of the database through the data interface management based on the stroke order, the OCR and the artificial intelligence.
In one embodiment, the data interface management system based on stroke order, OCR and artificial intelligence further comprises: a verification module that performs the following operations:
configuring a second data interface for a first user configured with a first data interface every a preset first time period;
receiving handwriting information input by a first user through a second interface;
verifying the identity of the first user;
when the verification fails or exceeds the preset verification time, mapping the first data interface to a to-be-secondarily-distributed list; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
The working principle and the beneficial effects of the technical scheme are as follows:
when the intelligent education data platform is in application operation, in order to achieve reasonable configuration of the first data interface, the first user configured with the first data interface is subjected to identity verification after every preset first time period, the identity of a use object of the first data interface is confirmed, the first data interface which fails in verification is subjected to secondary distribution, the utilization rate of the first data interface with high authority is guaranteed, and management of the data interface is optimized.
In one embodiment, the data interface management system based on stroke order, OCR and artificial intelligence further comprises: the secondary distribution module is used for configuring a second data interface for the second user at intervals of a preset first time period and executing the following operations when receiving the note information input by the second user:
receiving a secondary allocation request for the first data interface input by a second user;
acquiring a first authority value corresponding to a first data interface used by a current second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using a target interface;
acquiring second user authority information and/or second liveness of a second user;
performing secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity degree, the second user permission information and/or the second activity degree;
the secondary distribution of the first data interface for the second user from the secondary distribution list based on the first user authority information and/or the first activity, the second user authority information and/or the second activity comprises the following steps:
when the second authority value of the second user authority information is larger than the first authority value of the first user authority information, configuring a first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
and when the second activity of the second user is greater than the first activity of the first user, configuring the first data interface used by the first user in the secondary allocation list to be used by the second user.
The working principle and the beneficial effects of the technical scheme are as follows:
when the intelligent education data platform is in application operation, a secondary distribution mechanism is implemented on the first data interface, reasonable utilization of the first data interface with high authority is guaranteed, namely when a user who logs in previously uses the first data interface with the highest authority, the user does not log in, so that the highest authority is always used, and when an account which logs in later wants to use the highest authority, the user can obtain the first data interface through the secondary distribution mechanism. And after the secondary distribution is successful, when the original user operates, the configuration of the first data interface is carried out again.
In one embodiment, the second activity is determined by the steps of:
acquiring the historical login condition of a second user;
analyzing the historical login condition, and acquiring login days of the user in a preset time period away from the current time, login time each day and a list of data in a database called during login each day;
correcting the login time of each day based on the data in the list and a preset comparison table of calling data and time, and determining effective time; the method comprises the following specific steps: counting the total calling time of the data in the calling list, and taking the login time of each day as effective time when the total calling time is more than or equal to the login time of each day; when the total calling time is less than or equal to the login time every day, taking the total calling time as the effective time;
determining the activity of the user based on the effective time of the current user, the total effective time of all the users, the login days of the current user and the days corresponding to the preset time period, wherein the calculation formula is as follows:
wherein HkActivity for the kth user in big data platforms, DkThe login days of the kth user; d0The number of days corresponding to the preset time period; b iskThe valid time of the kth user; m is the number of users of the big data platform; epsilon1、ε2Is a predetermined weight.
The working principle and the beneficial effects of the technical scheme are as follows:
the method has the advantages that the activity calculation is carried out on the user based on the login days and the effective login time every day, the accuracy of the activity is guaranteed, in addition, the effective time is introduced, the influence of no operation time of the user is eliminated through correcting the login time by the data called when the user logs in every time, and the activity is more accurate and objective. Similarly, the first activity level determining step is the same as the second activity level determining step.
In one embodiment, the rights acquisition module performs the following operations:
analyzing the note information to obtain stroke order information and identification information;
determining an identity of the first user based on the identification information;
calling a preset verification model based on the identity of the first user;
verifying the identity of the first user based on the verification model, and acquiring the authority information of the first user when the verification is passed;
wherein verifying the identity of the first user based on the verification model comprises:
extracting a characteristic value of stroke order information and/or identification information, substituting the characteristic value into a pre-established neural network model to obtain a verification factor, inquiring a preset verification table, and passing the verification when the verification factor exists in the verification table;
or the like, or, alternatively,
constructing a verification vector based on the stroke order information and/or the identification information, matching the verification vector with a standard vector in a pre-established verification library, and passing the verification when the matching degree of the verification vector and the standard vector is greater than a preset matching value;
the matching degree calculation formula of the verification vector and the standard vector is as follows:
wherein, PqMatching degree of the verification vector and the qth standard vector in the verification library; n is the dimension of the verification vector and the standard vector; a isi,qIs the ith dimension data value of the qth standard vector; biAn ith dimension data value that is a verification vector;
the stroke order information includes: one or more of the types of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined;
the parameter information of each stroke includes: the handwriting intensity parameter comprises a starting point, an end point, position relation parameters among a preset number of sampling points among the starting point and the end point of each stroke, and/or handwriting intensity parameters of a preset number of sampling points among the starting point, the end point, the starting point and the end point of each stroke;
the identification information includes: one or more of characters, figures and symbols.
The working principle and the beneficial effects of the technical scheme are as follows:
the method includes the steps of firstly, determining the identity of a first user through identification information of note information identified by an OCR (Optical Character Recognition) identification technology, then calling a verification model stored corresponding to the identity of the first user for identity verification, and obtaining authority information of the first user after verification is passed. According to the first scheme, a pre-trained neural network model is adopted, characteristic values of stroke order information and/or identification information are extracted and input into the neural network model, a verification factor is obtained, and a final verification result is determined based on the verification factor. And a second scheme is that a pre-established verification library is adopted, a verification vector is constructed based on the stroke order information and/or the identification information, the verification vector is matched with a standard vector in the verification library, and verification is performed through a matching result. Furthermore, the stroke order information and the identification information are integrated, so that the verification precision is improved, namely the self-definition of the first user is realized according to the stroke order as a verification point instead of the standard when the characters are written, the verification granularity is improved, and the self-defined operability of the first user is realized. In addition, the handwriting dynamics parameters among strokes are considered, the recognition of the same stroke written by different people in the same character is realized, and the recognition degree of personnel on the basis of stroke order information and recognition information schemes is improved.
The embodiment of the present invention further provides a data interface management system based on stroke order, OCR and artificial intelligence, including:
the first acquisition module is used for acquiring first equipment information and first user permission information of a terminal used by a first user;
the second acquisition module is used for acquiring the second device information and the interface authority information which are allowed to be accessed of the first data interface;
the third configuration module is used for constructing a login vector based on the first equipment information and the first authority information; constructing an interface vector based on the second device information and the interface authority information; and calculating the similarity between the login vector and the interface vector, and configuring the first data interface with the maximum similarity to the first user for use.
The working principle and the beneficial effects of the technical scheme are as follows:
and introducing equipment information, participating in the configuration of the first data interface, and considering the compatibility of the first data interface and the terminal to realize the rationality of the configuration of the first data interface.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A data interface management method based on stroke order, OCR and artificial intelligence is characterized by comprising the following steps:
constructing a first data interface library, prefabricating at least one first data interface, and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
configuring a second data interface for the first user; the second data interface is only connected with the authority database;
receiving handwriting information input by a first user through the second data interface;
determining first user permission information of the first user based on the handwriting information;
and configuring a first data interface corresponding to the first user authority information for the first user from the first data interface library, and simultaneously canceling the second data interface used by the first user and storing the second data interface into a second data interface library.
2. The method for data interface management based on stroke order, OCR and artificial intelligence of claim 1 further comprising:
configuring the second data interface for a first user configured with the first data interface every a preset first time period;
receiving the handwriting information input by a first user through the second interface;
verifying the identity of the first user;
when the verification fails or exceeds the preset verification time, mapping the first data interface to a list to be secondarily distributed; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
3. The method for managing a data interface based on stroke order, OCR and artificial intelligence as claimed in claim 2, wherein when configuring a second data interface for a second user every predetermined first time period and receiving the input note information of the second user, further comprising:
receiving a second user input secondary allocation request for the first data interface;
acquiring a first authority value corresponding to the first data interface used by the second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using the target interface;
acquiring second user permission information and/or second liveness of the second user;
performing secondary distribution of a first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity, the second user permission information and/or the second activity;
performing secondary distribution of a first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity, the second user permission information and/or the second activity, including:
when the second authority value of the second user authority information is larger than the first authority value in the first user authority information, configuring the first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
configuring the first data interface used by the first user in the secondary allocation list to be used by a second user when the second activity of the second user is greater than the first activity of the first user.
4. The method for data interface management based on stroke order, OCR and artificial intelligence as claimed in claim 3, wherein the determining step of the second liveness is as follows:
acquiring the historical login condition of the second user;
analyzing the historical login condition, and acquiring login days of the user in a preset time period away from the current time, login time each day and a list of data in a database called during login each day;
correcting the login time of each day based on the data in the list and a preset comparison table of calling data and time, and determining effective time; the method comprises the following specific steps: counting the total calling time of the data in the calling list, and taking the login time of each day as effective time when the total calling time is more than or equal to the login time of each day; when the total calling time is less than or equal to the login time every day, taking the total calling time as the effective time;
determining the activity of the user based on the effective time of the current user, the total effective time of all the users, the login days of the current user and the days corresponding to the preset time period, wherein the calculation formula is as follows:
wherein HkActivity for the kth user in big data platforms, DkThe login days of the kth user; d0The number of days corresponding to the preset time period; b iskThe valid time of the kth user; m is the number of users of the big data platform; epsilon1、ε2Is a predetermined weight.
5. The method for data interface management based on stroke order, OCR and artificial intelligence of claim 1 wherein said determining first user permission information of said first user based on said handwriting information; the method comprises the following steps:
analyzing the note information to obtain stroke order information and identification information;
determining an identity of a first user based on the identification information;
calling a preset verification model based on the identity of the first user;
verifying the identity of the first user based on the verification model, and acquiring authority information of the first user when the verification is passed;
wherein verifying the identity of the first user based on the verification model comprises:
extracting a characteristic value of the stroke order information and/or the identification information, substituting the characteristic value into a pre-established neural network model to obtain a verification factor, inquiring a preset verification table, and passing the verification when the verification factor exists in the verification table;
or the like, or, alternatively,
constructing a verification vector based on the stroke order information and/or the identification information, matching the verification vector with a standard vector in a pre-established verification library, and passing the verification when the matching degree of the verification vector and the standard vector is greater than a preset matching value;
the matching degree calculation formula of the verification vector and the standard vector is as follows:
wherein, PqMatching the verification vector with the qth standard vector in the verification library; n is the dimension of the verification vector and the standard vector; a isi,qIs the ith dimension data value of the qth of the standard vector; biIs the ith dimension data value of the verification vector;
the stroke order information includes: one or more of the types of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined;
the parameter information of each stroke comprises: the handwriting intensity parameter comprises a starting point, an end point, position relation parameters between a preset number of sampling points in the middle of the starting point and the end point of each stroke, and/or handwriting intensity parameters of a preset number of sampling points in the middle of the starting point, the end point, the starting point and the end point of each stroke;
the identification information includes: one or more of characters, figures and symbols.
6. The method for data interface management based on stroke order, OCR and artificial intelligence of claim 1 further comprising:
acquiring first equipment information and first user permission information of a terminal used by a first user;
acquiring second device information and interface authority information which are allowed to be accessed of a first data interface;
constructing a login vector based on the first device information and the first permission information;
constructing an interface vector based on the second device information and the interface authority information;
and calculating the similarity of the login vector and the interface vector, and configuring the first data interface with the maximum similarity to a first user for use.
7. The method for data interface management based on stroke order, OCR and artificial intelligence of claim 1 wherein said first device information or said second device information comprises: voltage of the device, current of the device, model number of each component in the device, upload speed of the device, and download speed of the device.
8. A data interface management system based on stroke order, OCR and artificial intelligence, comprising:
the building module is used for building a first data interface library, prefabricating at least one first data interface and configuring interface parameters of the first data interface, wherein the interface parameters comprise: one or more combinations of interface authority of the data interface, serial number of the data interface, data source which can be accessed by the data interface and transmission speed of the data interface;
the first configuration module is used for configuring a second data interface for a first user; the second data interface is only connected with the authority database;
the first input module is used for receiving handwriting information input by a first user through the second data interface;
the authority acquiring module is used for determining first user authority information of the first user based on the handwriting information;
and the second configuration module is used for configuring a first data interface corresponding to the first user permission information for the first user from the first data interface library, and simultaneously canceling the second data interface used by the first user and storing the second data interface into a second data interface library.
9. The data interface management system based on stroke order, OCR and artificial intelligence of claim 8 further comprising: a verification module that performs the following operations:
configuring the second data interface for a first user configured with the first data interface every a preset first time period;
receiving the handwriting information input by a first user through the second interface;
verifying the identity of the first user;
when the verification fails or exceeds the preset verification time, mapping the first data interface to a list to be secondarily distributed; when other first users acquire the use right of the first data interface from the secondary distribution list, other first data interfaces are configured for the first users again;
and when the verification is passed within the preset verification time, keeping the first user using the first data interface.
10. The data interface management system based on stroke order, OCR and artificial intelligence of claim 7 further comprising: the secondary distribution module is used for configuring a second data interface for the second user at preset intervals of the first time period and executing the following operations when receiving the note information input by the second user:
receiving a second user input secondary allocation request for the first data interface;
acquiring a first authority value corresponding to the first data interface used by the second user;
comparing the first authority value with a second authority value of the first data interface in the secondary distribution list to obtain at least one selectable first data interface as a target interface;
acquiring first user permission information and/or first liveness of a first user using the target interface;
acquiring second user permission information and/or second liveness of the second user;
performing secondary distribution of a first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity, the second user permission information and/or the second activity;
performing secondary distribution of a first data interface for the second user from the secondary distribution list based on the first user permission information and/or the first activity, the second user permission information and/or the second activity, including:
when the second authority value of the second user authority information is larger than the first authority value in the first user authority information, configuring the first data interface used by the first user in the secondary distribution list as the second user;
and/or the presence of a gas in the gas,
configuring the first data interface used by the first user in the secondary allocation list to be used by a second user when the second activity of the second user is greater than the first activity of the first user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011566412.3A CN112597468A (en) | 2020-12-25 | 2020-12-25 | Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011566412.3A CN112597468A (en) | 2020-12-25 | 2020-12-25 | Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112597468A true CN112597468A (en) | 2021-04-02 |
Family
ID=75202686
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011566412.3A Pending CN112597468A (en) | 2020-12-25 | 2020-12-25 | Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112597468A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113177075A (en) * | 2021-04-08 | 2021-07-27 | 中电鹰硕(深圳)智慧互联有限公司 | Handwriting data storage method and system based on big data platform |
-
2020
- 2020-12-25 CN CN202011566412.3A patent/CN112597468A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113177075A (en) * | 2021-04-08 | 2021-07-27 | 中电鹰硕(深圳)智慧互联有限公司 | Handwriting data storage method and system based on big data platform |
| CN113177075B (en) * | 2021-04-08 | 2023-10-03 | 中电鹰硕(深圳)智慧互联有限公司 | Handwriting data storage method and system based on big data platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110414373B (en) | Deep learning palm vein recognition system and method based on cloud edge-side cooperative computing | |
| US11557302B2 (en) | Digital assistant processing of stacked data structures | |
| CN111932144B (en) | Customer service agent distribution method and device, server and storage medium | |
| CN115271635B (en) | Intelligent community service platform system | |
| WO2022217781A1 (en) | Data processing method, apparatus, device, and medium | |
| CN112465513A (en) | Network security system and method based on identity authentication | |
| CN114943511A (en) | Government affair office automation platform and optimization implementation method thereof | |
| CN113918526A (en) | Log processing method and device, computer equipment and storage medium | |
| Archilles et al. | Vision: a web service for face recognition using convolutional network | |
| CN112597468A (en) | Data interface management method and system based on stroke order, OCR (optical character recognition) and artificial intelligence | |
| CN115114906A (en) | Method and device for extracting entity content, electronic equipment and storage medium | |
| CN113821587A (en) | Text relevance determination method, model training method, device and storage medium | |
| WO2021135549A1 (en) | Service item processing permissions authorization method and apparatus, computer device, and storage medium | |
| EP3871117A1 (en) | Providing images with privacy label | |
| Bhowmik et al. | mTrust: call behavioral trust predictive analytics using unsupervised learning in mobile cloud computing | |
| CN113362852A (en) | User attribute identification method and device | |
| CN111694884B (en) | Intelligent government affair request processing method based on big data | |
| CN109857748A (en) | A kind of contract dataset processing method, device and electronic equipment | |
| WO2022217784A1 (en) | Data processing methods and apparatus, device, and medium | |
| CN116167025A (en) | Multi-factor user identity dynamic authentication system and method thereof | |
| CN114125845A (en) | Automatic networking method and device for intelligent equipment based on Internet of things | |
| CN114328818A (en) | Text corpus processing method and device, storage medium and electronic equipment | |
| CN112511352A (en) | User management method and system | |
| CN114548831B (en) | Evaluation report generation method and device, electronic equipment and storage medium | |
| CN115515083B (en) | Message issuing method, device, server and storage medium |
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 | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20211126 Address after: Room 301, building D, Hongwei Industrial Zone, No.6 Liuxian 3rd road, Xingdong community, Xin'an street, Bao'an District, Shenzhen City, Guangdong Province Applicant after: SHENZHEN EAGLESOUL TECHNOLOGY Co.,Ltd. Address before: Room 301, building D, Hongwei Industrial Zone, No.6 Liuxian 3rd road, Xingdong community, Xin'an street, Bao'an District, Shenzhen City, Guangdong Province Applicant before: Shenzhen YINGSHUO Education Service Co., Ltd |