CN112511352A - User management method and system - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
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- 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
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- G—PHYSICS
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- 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
- G06F21/45—Structures or tools for the administration of authentication
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
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Abstract
The invention provides a user management method and a user management system, wherein the method comprises the following steps: constructing a unified user management server, and respectively connecting the unified user management server with the big data platform in a communication way; the unified user management server performs the following operations: constructing mirror image user management modules corresponding to the big data platforms; sequentially acquiring first user information of each big data platform, and constructing a plurality of mirror image user sub-modules under the mirror image user management modules corresponding to the big data platforms; the mirror image user sub-modules correspond to the first user information of the big data platform one by one; when second user information inquiry of one big data platform is received, mirror image user management modules of other big data platforms are inquired, and mirror image user sub-modules corresponding to the second user information are obtained; and generating temporary user information on the big data platform based on the mirror image user sub-module. The user management method of the invention realizes the unified management of the users among all the big data education platforms.
Description
Technical Field
The invention relates to the technical field of database management, in particular to a user management method and a user management system.
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 development direction of big data is mastered, a big data education platform is developed, the improvement of education quality is facilitated, on the basis of the purposes, a plurality of big data education platforms are correspondingly established by each education institution and each department, however, because the responsible units for establishing the big data education platforms are different, the user data among the big data education platforms are not intercommunicated, the user needs to be registered on each platform, the user needs to remember a plurality of account numbers and passwords, the password forgetting is frequently generated, although the password retrieving mode is very quick at present, and the experience of the user using the platform is influenced. .
Disclosure of Invention
One purpose of the invention is to provide a user management method, which realizes unified management of users among all big data education platforms.
The user management method provided by the embodiment of the invention is applied to a plurality of big data platforms and comprises the following steps:
constructing a unified user management server, and respectively connecting the unified user management server with the big data platform in a communication way;
the unified user management server performs the following operations:
constructing mirror image user management modules corresponding to the big data platforms;
sequentially acquiring first user information of each big data platform, and constructing a plurality of mirror image user sub-modules under the mirror image user management modules corresponding to the big data platforms; the mirror image user sub-modules correspond to the first user information of the big data platform one by one;
when receiving a second user information inquiry of one of the big data platforms, inquiring mirror image user management modules of other big data platforms,
acquiring a mirror image user sub-module corresponding to the second user information;
and generating temporary user information on the big data platform based on the mirror image user sub-module.
Preferably, the unified user management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to a mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module into a mirror image user management module corresponding to a big data platform corresponding to temporary user information or not based on the first historical login condition and the second historical login condition, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated into the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated into the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to a mirror image user management module corresponding to a big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, wherein the determining comprises:
analyzing the first historical login condition, and acquiring the first login times of the user in a preset first time period from the current time, the first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on the data in the first list, a preset call data and time comparison table, and determining a first effective time, which is specifically as follows: counting first total calling time for calling data in the first list, and taking the first login time as first effective time when the first total calling time is greater than or equal to first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as a first effective time;
correcting the second login time based on the data in the second list, the preset calling data and the comparison table of the time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as a second effective time;
determining the preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein the calculation formula is as follows:
wherein P is a preference value; n is a radical of1The number of the first login times is the first login number; n is a radical of2The second login times; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the first list during the ith login; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to a mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
Preferably, the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; the user account takes the name of the user list and the user name in the user list as the login name.
Preferably, when the user account logs in for the first time, the big data platform performs the following operations:
acquiring handwriting of a login name input by a user for multiple times;
performing feature extraction on the handwriting to obtain handwriting features;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when a user account logs in after the initial model is trained and converged.
Preferably, the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying users based on historical login conditions, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of a unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server migrates the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in a mirror image user management module and a frozen user management module of a mirror image user management module except for the mirror image user management module corresponding to the big data platform in the active user, a general user, a semi-frozen user and the unified user management server are sequentially inquired, login information which is input and output when the user logs in is verified, and then the user login is completed.
The invention also provides a user management system, which is applied to a plurality of big data platforms and comprises the following components:
the unified user management server is respectively in communication connection with the big data platform;
the unified user management server includes:
the first construction module is used for constructing mirror image user management modules corresponding to the big data platforms;
the second construction module is used for sequentially acquiring the first user information of each big data platform and constructing a plurality of mirror image user sub-modules under the mirror image user management module corresponding to the big data platform; the mirror image user sub-modules correspond to the first user information of the big data platform one by one;
the query module is used for querying the mirror image user management module of other big data platforms when receiving a second user information query of one big data platform,
the acquisition module is used for acquiring a mirror image user sub-module corresponding to the second user information;
and the generation module is used for generating temporary user information on the big data platform based on the mirror image user sub-module.
Preferably, the unified user management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to a mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module into a mirror image user management module corresponding to a big data platform corresponding to temporary user information or not based on the first historical login condition and the second historical login condition, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated into the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated into the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to a mirror image user management module corresponding to a big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, wherein the determining comprises:
analyzing the first historical login condition, and acquiring the first login times of the user in a preset first time period from the current time, the first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on the data in the first list, a preset call data and time comparison table, and determining a first effective time, which is specifically as follows: counting first total calling time for calling data in the first list, and taking the first login time as first effective time when the first total calling time is greater than or equal to first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as a first effective time;
correcting the second login time based on the data in the second list, the preset calling data and the comparison table of the time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as a second effective time;
determining the preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein the calculation formula is as follows:
wherein P is a preference value; n is a radical of1The number of the first login times is the first login number; n is a radical of2The second login times; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset number according to the data quantity in the first list at the i-th loginThe relation coefficient determined by the data quantity and relation coefficient table; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to a mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
Preferably, the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; the user account takes the name of the user list and the user name in the user list as the login name.
Preferably, when the user account logs in for the first time, the big data platform performs the following operations:
acquiring handwriting of a login name input by a user for multiple times;
performing feature extraction on the handwriting to obtain handwriting features;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when a user account logs in after the initial model is trained and converged.
Preferably, the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying users based on historical login conditions, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of a unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server migrates the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in a mirror image user management module and a frozen user management module of a mirror image user management module except for the mirror image user management module corresponding to the big data platform in the active user, a general user, a semi-frozen user and the unified user management server are sequentially inquired, login information which is input and output when the user logs in is verified, and then the user login is completed.
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 schematic diagram illustrating steps executed by a unified user management server in a user management method according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating a user management system according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a unified subscriber management server according to an embodiment of the present 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 user management method, which is applied to a plurality of big data platforms and comprises the following steps:
constructing a unified user management server, and respectively connecting the unified user management server with the big data platform in a communication way;
as shown in fig. 1, the unified subscriber management server performs the following operations:
step S1: constructing mirror image user management modules corresponding to the big data platforms;
step S2: sequentially acquiring first user information of each big data platform, and constructing a plurality of mirror image user sub-modules under the mirror image user management modules corresponding to the big data platforms; the mirror image user sub-modules correspond to the first user information of the big data platform one by one;
step S3: when receiving a second user information inquiry of one of the big data platforms, inquiring mirror image user management modules of other big data platforms,
step S4: acquiring a mirror image user sub-module corresponding to the second user information;
step S5: and generating temporary user information on the big data platform based on the mirror image user sub-module.
The working principle and the beneficial effects of the technical scheme are as follows:
the big data platform network for education constructs each big data platform in province/city/county level, and realizes a unified user identity and PKI digital authentication management system through a unified user management server: the platform provides different informationized services for all education participants according to different identities and performs unified management; thereby greatly improving the pertinence and maintainability of the system and effectively reducing the complexity of the system; meanwhile, the system adopts a Web single sign-on scheme based on PKI and adopts bidirectional authentication to ensure the legal identities of the user and the authentication server. The two-stage authorization mechanism and the SSO proxy are used, the coupling of the single sign-on system and the Web application is reduced, and the user can safely and effectively realize 'one-time sign-on and free switching'. And single sign-on and unified authentication of province, city and county education cloud platform users on the national platform are supported. The method specifically comprises the following steps: the unified user management server mirrors the user information of each big data platform to the corresponding mirror image user management module, when a user logs in each big data platform and the big data platform fails to determine that the user is a registered user in the user information of the big data platform, a user inquiry is sent to the unified user management server, the user management server is unified, the mirror image user management modules corresponding to other big data platforms are inquired, the corresponding mirror image user sub-modules are inquired, temporary user information is generated on the big data platform based on the mirror image user sub-modules, and the user logs in the big data platform.
The user management method of the invention realizes the unified management of the users among all the big data education platforms.
In one embodiment, the unified subscriber management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to a mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module into a mirror image user management module corresponding to a big data platform corresponding to temporary user information or not based on the first historical login condition and the second historical login condition, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated into the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated into the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to a mirror image user management module corresponding to a big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, wherein the determining comprises:
analyzing the first historical login condition, and acquiring the first login times of the user in a preset first time period from the current time, the first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on the data in the first list, a preset call data and time comparison table, and determining a first effective time, which is specifically as follows: counting first total calling time for calling data in the first list, and taking the first login time as first effective time when the first total calling time is greater than or equal to first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as a first effective time;
correcting the second login time based on the data in the second list, the preset calling data and the comparison table of the time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as a second effective time;
determining the preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein the calculation formula is as follows:
wherein P is a preference value; n is a radical of!The number of the first login times is the first login number; n is a radical of2The second login times; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the first list during the ith login; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to a mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
The working principle and the beneficial effects of the technical scheme are as follows:
the unified user management module analyzes the big data platforms preferred by the user according to the actual login conditions of the user on each big data platform; and then, the user information is migrated, relatively speaking, the large data platform directly queries the user information of the large data platform to realize that the user logs in faster than that of the large data platform by unifying the user management servers, and through the migration of the user information, the speed of logging in the large data platform preferred by the user is improved, and the intellectualization of user management is realized.
In one embodiment, the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; the user account takes the name of the user list and the user name in the user list as the login name.
The working principle and the beneficial effects of the technical scheme are as follows:
the first user with high-level authority is a class principal, the user list is a class student list, and the user accounts for all students are simultaneously set in batches by taking classes as a unit according to the user list, so that the account setting speed is increased; furthermore, the user list may be filled with specific information of each user, or may be supplemented when the user account logs in for the first time.
In one embodiment, when a user account logs in for the first time, the big data platform performs the following operations:
acquiring handwriting of a login name input by a user for multiple times;
performing feature extraction on the handwriting to obtain handwriting features;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when a user account logs in after the initial model is trained and converged.
The working principle and the beneficial effects of the technical scheme are as follows:
when the user logs in, the user only needs to input the handwriting of the login name with the handwriting input equipment to finish the login without memorizing the password, the complicated operation that needs to be found back after forgetting the password is avoided, the characters, figures, characters and the like identified by the user input handwriting through an ORC (Optical Character Recognition) identification technology are taken as the login name, and the order of strokes information when the user writes the handwriting is taken as the password, and the order of strokes information comprises: one or more of the type of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined into a login password; the parameter information of each stroke includes: the handwriting intensity parameter comprises a position relation parameter of a starting point, an end point, a preset number of sampling points in the middle of the starting point and the end point of each stroke, and/or a handwriting intensity parameter 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.
In one embodiment, the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying users based on historical login conditions, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of a unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server migrates the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in a mirror image user management module and a frozen user management module of a mirror image user management module except for the mirror image user management module corresponding to the big data platform in the active user, a general user, a semi-frozen user and the unified user management server are sequentially inquired, login information which is input and output when the user logs in is verified, and then the user login is completed.
The working principle and the beneficial effects of the technical scheme are as follows:
the method has the advantages that users are classified, login speed of active users is improved during login, login experience of the active users is improved, in addition, the frozen users are moved out of the big data platform and placed to the unified user management server, storage space of the big data platform is made free, operation efficiency of the big data platform is improved, and meanwhile the users cannot be lost.
In one embodiment, ranking users based on historical login conditions includes:
analyzing the historical login condition, and acquiring login days of the user in a preset second time period away from the current time, login time each day and a third list of data in the database called during login each day;
correcting the login time of each day based on the data in the third list and a preset comparison table of calling data and time, and determining third effective time; the method comprises the following specific steps: counting a third total calling time for calling the data in the third list, and taking the login time of each day as a third effective time when the third total calling time is greater than or equal to the login time of each day; when the third total calling time is less than or equal to the login time every day, taking the third total calling time as a third effective time;
determining the activity of the user based on the third effective time of the current user, the sum of the third effective times of all the users, the login days of the current user and the days corresponding to the preset second 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; d0 days corresponding to the second time period; b iskA third validity time for a kth user; n is the number of users of the big data platform; epsilon1、ε2Is a preset weight;
when the activity degree is equal to zero, dividing the user into a frozen user;
when the activity is greater than zero but less than a first threshold value, classifying the user as a semi-frozen user;
when the activity degree is greater than or equal to the first threshold value but less than the second threshold value, dividing the users into common users;
when the activity degree is greater than or equal to a second threshold value, dividing the users into active users; preferably, the second threshold may be determined according to an average value of the liveness of all users of the platform and a maximum value of the user liveness, and more specifically, may be an average value of both the average value of the liveness of all users of the platform and the maximum value of the user liveness. In addition, the first threshold value may be preset, or may be determined to be half of an average value of liveness of all users of the platform.
The working principle and the beneficial effects of the technical scheme are as follows:
the users are classified based on the login days and the effective login time each day, the classification accuracy is guaranteed, in addition, the effective time is introduced, the login time is corrected through the data called when the users log in each time, the influence of the no-operation time of the users on the classification is eliminated, and the classification is more accurate and objective.
The present invention also provides a user management system, which is applied to a plurality of big data platforms 2, as shown in fig. 2, and includes:
the unified user management server 1 is in communication connection with the big data platform 2 respectively;
as shown in fig. 3, the unified subscriber management server 1 includes:
the first construction module 11 is used for constructing mirror image user management modules 13 corresponding to the big data platforms;
the second construction module 12 is used for sequentially acquiring the first user information of each big data platform 2 and constructing a plurality of mirror image user sub-modules 14 under the mirror image user management module 13 corresponding to the big data platform; the mirror image user sub-module 14 corresponds to the first user information of the big data platform 2 one by one;
a query module 15, for querying the mirror user management module 13 of the other big data platform when receiving the second user information query of one big data platform,
an obtaining module 16, configured to obtain a mirror image user sub-module 14 corresponding to the second user information;
and the generating module 17 is used for generating temporary user information on the big data platform 2 based on the mirror user sub-module 14.
The working principle and the beneficial effects of the technical scheme are as follows:
the big data platform network for education constructs each big data platform in province/city/county level, and realizes a unified user identity and PKI digital authentication management system through a unified user management server: the platform provides different informationized services for all education participants according to different identities and performs unified management; thereby greatly improving the pertinence and maintainability of the system and effectively reducing the complexity of the system; meanwhile, the system adopts a Web single sign-on scheme based on PKI and adopts bidirectional authentication to ensure the legal identities of the user and the authentication server. The two-stage authorization mechanism and the SSO proxy are used, the coupling of the single sign-on system and the Web application is reduced, and the user can safely and effectively realize 'one-time sign-on and free switching'. And single sign-on and unified authentication of province, city and county education cloud platform users on the national platform are supported. The method specifically comprises the following steps: the unified user management server mirrors the user information of each big data platform to the corresponding mirror image user management module, when a user logs in each big data platform and the big data platform fails to determine that the user is a registered user in the user information of the big data platform, a user inquiry is sent to the unified user management server, the user management server is unified, the mirror image user management modules corresponding to other big data platforms are inquired, the corresponding mirror image user sub-modules are inquired, temporary user information is generated on the big data platform based on the mirror image user sub-modules, and the user logs in the big data platform.
The user management system of the invention realizes the unified management of users among all big data education platforms.
In one embodiment, the unified subscriber management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on a big data platform corresponding to a mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module into a mirror image user management module corresponding to a big data platform corresponding to temporary user information or not based on the first historical login condition and the second historical login condition, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated into the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated into the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to a mirror image user management module corresponding to a big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, wherein the determining comprises:
analyzing the first historical login condition, and acquiring the first login times of the user in a preset first time period from the current time, the first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on the data in the first list, a preset call data and time comparison table, and determining a first effective time, which is specifically as follows: counting first total calling time for calling data in the first list, and taking the first login time as first effective time when the first total calling time is greater than or equal to first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as a first effective time;
correcting the second login time based on the data in the second list, the preset calling data and the comparison table of the time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as a second effective time;
determining the preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein the calculation formula is as follows:
wherein P is a preference value; n is a radical of1The number of the first login times is the first login number; n is a radical of2The second login times; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the first list during the ith login; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to a mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
The working principle and the beneficial effects of the technical scheme are as follows:
the unified user management module analyzes the big data platforms preferred by the user according to the actual login conditions of the user on each big data platform; and then, the user information is migrated, relatively speaking, the large data platform directly queries the user information of the large data platform to realize that the user logs in faster than that of the large data platform by unifying the user management servers, and through the migration of the user information, the speed of logging in the large data platform preferred by the user is improved, and the intellectualization of user management is realized.
In one embodiment, the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; the user account takes the name of the user list and the user name in the user list as the login name.
The working principle and the beneficial effects of the technical scheme are as follows:
the first user with high-level authority is a class principal, the user list is a class student list, and the user accounts for all students are simultaneously set in batches by taking classes as a unit according to the user list, so that the account setting speed is increased; furthermore, the user list may be filled with specific information of each user, or may be supplemented when the user account logs in for the first time.
In one embodiment, when a user account logs in for the first time, the big data platform performs the following operations:
acquiring handwriting of a login name input by a user for multiple times;
performing feature extraction on the handwriting to obtain handwriting features;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when a user account logs in after the initial model is trained and converged.
The working principle and the beneficial effects of the technical scheme are as follows:
when the user logs in, the user only needs to input the handwriting of the login name with the handwriting input equipment to finish the login without memorizing the password, the complicated operation that needs to be found back after forgetting the password is avoided, the characters, figures, characters and the like identified by the user input handwriting through an ORC (Optical Character Recognition) identification technology are taken as the login name, and the order of strokes information when the user writes the handwriting is taken as the password, and the order of strokes information comprises: one or more of the type of the strokes, the sequence among the types of the strokes and the parameter information of the strokes are combined into a login password; the parameter information of each stroke includes: the handwriting intensity parameter comprises a position relation parameter of a starting point, an end point, a preset number of sampling points in the middle of the starting point and the end point of each stroke, and/or a handwriting intensity parameter 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.
In one embodiment, the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying users based on historical login conditions, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of a unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server migrates the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in a mirror image user management module and a frozen user management module of a mirror image user management module except for the mirror image user management module corresponding to the big data platform in the active user, a general user, a semi-frozen user and the unified user management server are sequentially inquired, login information which is input and output when the user logs in is verified, and then the user login is completed.
The working principle and the beneficial effects of the technical scheme are as follows:
the method has the advantages that users are classified, login speed of active users is improved during login, login experience of the active users is improved, in addition, the frozen users are moved out of the big data platform and placed to the unified user management server, storage space of the big data platform is made free, operation efficiency of the big data platform is improved, and meanwhile the users cannot be lost.
In one embodiment, ranking users based on historical login conditions includes:
analyzing the historical login condition, and acquiring login days of the user in a preset second time period away from the current time, login time each day and a third list of data in the database called during login each day;
correcting the login time of each day based on the data in the third list and a preset comparison table of calling data and time, and determining third effective time; the method comprises the following specific steps: counting a third total calling time for calling the data in the third list, and taking the login time of each day as a third effective time when the third total calling time is greater than or equal to the login time of each day; when the third total calling time is less than or equal to the login time every day, taking the third total calling time as a third effective time;
determining the activity of the user based on the third effective time of the current user, the sum of the third effective times of all the users, the login days of the current user and the days corresponding to the preset second 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; d0 days corresponding to the second time period; b iskA third validity time for a kth user; n is the number of users of the big data platform; epsilon1、ε2Is a preset weight;
when the activity degree is equal to zero, dividing the user into a frozen user;
when the activity is greater than zero but less than a first threshold value, classifying the user as a semi-frozen user;
when the activity degree is greater than or equal to the first threshold value but less than the second threshold value, dividing the users into common users;
when the activity degree is greater than or equal to a second threshold value, dividing the users into active users; preferably, the second threshold may be determined according to an average value of the liveness of all users of the platform and a maximum value of the user liveness, and more specifically, may be an average value of both the average value of the liveness of all users of the platform and the maximum value of the user liveness. In addition, the first threshold value may be preset, or may be determined to be half of an average value of liveness of all users of the platform.
The working principle and the beneficial effects of the technical scheme are as follows:
the users are classified based on the login days and the effective login time each day, the classification accuracy is guaranteed, in addition, the effective time is introduced, the login time is corrected through the data called when the users log in each time, the influence of the no-operation time of the users on the classification is eliminated, and the classification is more accurate and objective.
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 user management method is applied to a plurality of big data platforms and is characterized by comprising the following steps:
constructing a unified user management server, and respectively connecting the unified user management server with the big data platform in a communication way;
the unified user management server performs the following operations:
constructing a mirror image user management module corresponding to each big data platform;
sequentially acquiring first user information of each big data platform, and constructing a plurality of mirror image user sub-modules under a mirror image user management module corresponding to the big data platform; the mirror image user sub-modules correspond to the first user information of the big data platform one by one;
querying the mirror user management modules of other big data platforms when receiving a second user information query of one big data platform,
acquiring the mirror image user sub-module corresponding to the second user information;
and generating temporary user information on the big data platform based on the mirror image user sub-module.
2. The user management method of claim 1, wherein the unified user management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on the big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on the big data platform corresponding to the mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated to the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, including:
analyzing the first historical login condition, and acquiring a first login frequency of the user in a preset first time period from the current time, a first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on a comparison table of data in the first list, preset calling data and time, and determining a first effective time, wherein the specific steps are as follows: counting first total calling time for calling data in the first list, and taking the first login time as the first effective time when the first total calling time is greater than or equal to the first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as the first effective time;
correcting the second login time based on a comparison table of data in a second list, preset calling data and time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to the second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as the second effective time;
determining a preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein a calculation formula is as follows:
wherein P is the preference value; n is a radical of1The number of the first login times is the first login number; n is a radical of2The second login times are obtained; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the first list during the ith login; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
3. The user management method of claim 1, wherein the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; and the user account takes the name of the user list and the user name in the user list as login names.
4. The user management method of claim 3, wherein when the user account logs in for the first time, the big data platform performs the following operations:
acquiring handwriting of the login name input by the user for multiple times;
extracting the characteristics of the handwriting to obtain handwriting characteristics;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when the user account logs in after the initial model is trained and converged.
5. The user management method of claim 1, wherein the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying the users based on the historical login condition, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of the unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server transfers the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in the mirror image user management module and the freezing user management module of the mirror image user management module except for the large data platform corresponding to the active user, the general user, the semi-freezing user and the unified user management server is inquired in sequence, login information which is input and output when the user logs in is verified, and then the user login is completed.
6. A user management system applied to a plurality of big data platforms is characterized by comprising:
the unified user management server is respectively in communication connection with the big data platform;
the unified user management server includes:
the first construction module is used for constructing mirror image user management modules corresponding to the big data platforms;
the second construction module is used for sequentially acquiring the first user information of each big data platform and constructing a plurality of mirror image user sub-modules under the mirror image user management module corresponding to the big data platform; the mirror image user sub-modules correspond to the first user information of the big data platform one by one;
the query module is used for querying the mirror image user management modules of other big data platforms when receiving a second user information query of one big data platform,
the acquisition module is used for acquiring the mirror image user sub-module corresponding to the second user information;
and the generation module is used for generating temporary user information on the big data platform based on the mirror image user sub-module.
7. The user management system of claim 6, wherein the unified user management server further performs the following operations:
acquiring a first historical login condition of a user corresponding to the temporary user information on the big data platform corresponding to the temporary user information;
acquiring a second historical login condition of a user corresponding to the temporary user information on the big data platform corresponding to the mirror image user sub-module corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, and synchronously migrating the first user information of the big data platform corresponding to the mirror image user management module before the mirror image user sub-module is migrated to the big data platform corresponding to the mirror image user management module after the mirror image user sub-module is migrated when the mirror image user sub-module is migrated to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information;
determining whether to migrate the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information based on the first historical login situation and the second historical login situation, including:
analyzing the first historical login condition, and acquiring a first login frequency of the user in a preset first time period from the current time, a first login time in each login and a first list for calling data in the database;
analyzing the second historical login condition, and acquiring a second login frequency of the user in a preset first time period from the current time, a second login time in each login and a first list for calling data in the database;
correcting the first login time based on a comparison table of data in the first list, preset calling data and time, and determining a first effective time, wherein the specific steps are as follows: counting first total calling time for calling data in the first list, and taking the first login time as the first effective time when the first total calling time is greater than or equal to the first login time; when the first total calling time is less than or equal to the first login time, taking the first total calling time as the first effective time;
correcting the second login time based on a comparison table of data in a second list, preset calling data and time, and determining second effective time; the method comprises the following specific steps: counting second total calling time for calling the data in the second list, and taking the second login time as second effective time when the second total calling time is greater than or equal to the second login time; when the second total calling time is less than or equal to the second login time, taking the second total calling time as the second effective time;
determining a preference value of the user for the big data platform corresponding to the temporary user information relative to the big data platform corresponding to the mirror image user sub-module based on the first login times, the second login times, the first valid time and the second valid time, wherein a calculation formula is as follows:
wherein P is the preference value; n is a radical of1The number of the first login times is the first login number; n is a radical of2The second login times are obtained; t isiThe first effective time when logging in the ith time; t is tjThe second effective time of the j login; deltaiQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the first list during the ith login; gamma rayjQuerying a preset data quantity and a relation coefficient determined by a relation coefficient table according to the data quantity in the second list during j-th login; alpha is a preset frequency influence weight; beta is a preset time influence weight;
and when the preference value is greater than a preset preference threshold value, migrating the mirror image user sub-module to the mirror image user management module corresponding to the big data platform corresponding to the temporary user information.
8. The user management system of claim 6, wherein the big data platform performs the following operations:
acquiring a user list input by a first user with high-level authority;
opening a plurality of user accounts based on the user list; and the user account takes the name of the user list and the user name in the user list as login names.
9. The user management system of claim 8, wherein upon a first login of the user account, the big data platform performs the following operations:
acquiring handwriting of the login name input by the user for multiple times;
extracting the characteristics of the handwriting to obtain handwriting characteristics;
inputting the handwriting characteristics into a preset initial model, and obtaining a neural network model for password judgment when the user account logs in after the initial model is trained and converged.
10. The user management system of claim 9, wherein the big data platform performs the following operations:
acquiring historical login conditions of a user corresponding to the first user information;
classifying the users based on the historical login condition, and classifying the users into active users, general users, semi-frozen users and frozen users;
migrating the user information of the frozen user to a frozen user management module of the unified user management server; when the user of the frozen user logs in again through any big data platform, the unified user management server transfers the user information in the frozen user management module to the big data platform which logs in again;
when a user logs in, user information in the mirror image user management module and the freezing user management module of the mirror image user management module except for the large data platform corresponding to the active user, the general user, the semi-freezing user and the unified user management server is inquired in sequence, login information which is input and output when the user logs in is verified, and then the user login is completed.
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