CN115640556B

CN115640556B - Multi-user dynamic bidding authority allocation control method and device

Info

Publication number: CN115640556B
Application number: CN202211050021.5A
Authority: CN
Inventors: 张微; 李志男; 林少伟; 马莺; 龚䶮
Original assignee: Beijing Huayixin Technology Co ltd
Current assignee: Beijing Huayixin Technology Co ltd; Lin Shaowei
Priority date: 2022-08-30
Filing date: 2022-08-30
Publication date: 2023-06-27
Anticipated expiration: 2042-08-30
Also published as: CN115640556A

Abstract

The invention discloses a multi-user dynamic bidding authority allocation control method and a device, wherein the method comprises the following steps: acquiring internal environment element information and external environment element information of data product assets on a data platform, and constructing a demand model of the data product assets; establishing a basic role authority table of each link of the full life cycle of the data product asset; acquiring a user authority individual condition and a history authority competing relationship on a data platform, and constructing an individual authority competing model of a user; determining the best matching users and the bidding permission distribution results among the best matching users in all links of the full life cycle meeting the basic role permission requirements; controlling rights of all links in the whole life cycle to obtain a rights control mode; and dynamically adjusting the competitive right allocation result and the right control mode of the user to realize the multi-user dynamic competitive right allocation control. The method of the invention realizes the data platform permission allocation and scene control by taking the data product asset as the permission object.

Description

Multi-user dynamic bidding authority allocation control method and device

Technical Field

The invention relates to the technical field of large data platform user permission distribution, in particular to a multi-user dynamic bidding permission distribution control method and device.

Background

Currently, the so-called rights allocation and control of a data platform is mainly the allocation and control of a unified role of a platform user. The main idea of the data platform permission distribution method is to directly determine the user permission or deduce more user permissions according to the relevance among users, roles and permissions, or to match the user permissions through indirect relevance elements among users, roles and permissions of platform tasks, services, working modes and the like. The disadvantage of these methods is that the user rights allocation obtained by the associated rights allocation method mainly refers to the rights allocation of the role the user is in within the data platform. User rights allocation for these methods, limited by the standardization of role rights, often lacks personalized scene adaptability and dynamic rights features.

Therefore, on the basis of the current data platform authority allocation method, the authority control method focuses on user authority management of layering/grouping/partitioning, and the targets of accurate user role division and authority dynamic control are achieved by refining/subdividing the authorities. These methods mainly include: generating a personalized configuration file according to the difference degree of external factor information such as user identity information, tasks/businesses and the like, and subdividing user rights to form a precise role; according to the specific conditions of the user, the current operation authority is authorized, and dynamic hierarchical user authority management is formed; and grading the user security by an encryption method, thereby grading the user authority. The method essentially solves the problem that the current data platform authority distribution method lacks personalized scene adaptability and dynamic authority characteristics to a certain extent by increasing fine division of the authority. However, there is a problem of centralized rights control of the current data platform to the rights control method.

Because the current data platform authority allocation and control method is a method for matching users and authorities all the time in nature, other methods have not considered the unique requirement of different authority objects for authority users in the user authority allocation and control method at present due to the limitation of the traditional technical framework. When the difference of the unique demands of different rights objects on the rights users is large, the general role rights defined by the conventional data platform rights allocation and control method cannot cover and distinguish the different demands.

In particular, the rights allocation and control of four basic roles (data owners, data producers, data users and data managers) in links such as validation, collection, storage, use, processing, transmission, provision, disclosure of the full life cycle of the data product asset on the current data platform are affected by the specific requirements of the data product asset, and the trend of multi-user dynamic bidding is provided, so that the data product asset is ensured to be matched with the best user in each link of the full life cycle. Therefore, the allocation and control of user rights around the data product asset has higher requirements for the implementation of individual bidding conditions for each user, and the bidding relationship of each user is required to have dynamic adjustment characteristics.

Disclosure of Invention

The technical problem to be solved by the invention is to provide a multi-user dynamic bidding authority allocation control method which can allocate and control authorities for specific objects. The method can be used for solving the problem that the current data platform permission distribution method lacks personalized scene adaptability and dynamic permission characteristics, solving the problem of centralized authority control of the current data platform on the permission control method, and solving the problem that when the uniqueness requirements of different permission objects on permission users are greatly different in permission distribution and control, the general role permission defined by the conventional data platform permission distribution and control method can not cover and distinguish the different requirements, in particular to the problem of data platform permission distribution and control scene which takes data product assets as permission objects.

In order to solve the technical problem, a first aspect of the embodiment of the present invention discloses a method for controlling allocation of multi-user dynamic bidding permissions, the method comprising:

s1, acquiring internal environment element information and external environment element information of a data product asset on a data platform, and constructing a demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset;

The internal environment element information comprises the structure, the content, the self value and the security privacy of the data product asset;

the external environment element information includes: application scenarios, structure and content relationships with other data product assets, market value, fluxion, and security trustworthiness;

s2, establishing a basic role authority table of each link of the full life cycle of the data product asset by using the demand model of the data product asset;

the basic role authority list comprises basic role authority requirements of data product assets on all links of the full life cycle;

s3, acquiring a user authority individual condition and a history authority competing relationship on a data platform, and constructing an individual authority competing model of the user by utilizing the user authority individual condition and the history authority competing relationship, wherein the method comprises the following steps:

extracting authority individual conditions and historical authority competing relations of a data owner, a data producer, a data user and a data manager by utilizing the authority requirements and the historical authority competing relations of all links in the full life cycle;

analyzing authority individual conditions and historical authority competing relations of the data owners, the data producers, the data users and the data managers by utilizing a data mining method to obtain competing relation data product assets and cooperative relation data product assets;

S4, determining the best matching users and the bidding authority allocation results among the best matching users in all links of the full life cycle meeting the basic role authority requirements by utilizing the personalized authority bidding model of the users and the basic role authority requirements, wherein the step comprises the following steps:

obtaining the competitive right range between matched users of each link meeting the demand model by utilizing the user personalized authority competitive model and the basic role authority requirement;

constructing a competitive right range model of the matched user corresponding to each link of the full life cycle of the data product asset by utilizing the competitive right range;

constructing a data product asset authority matching model by using the competitive authority range model and taking the total authority matching optimization of the data product asset as a target;

determining the bidding authority allocation result of the best matching user of each link of the full life cycle meeting the basic role authority requirement by utilizing the data product asset authority matching model;

the total authority of the data product asset is matched with an optimal target, the number of matched users of each link and each basic unit in the whole life cycle of the data product asset is minimum, the competitive authority of each matched user is minimum, the gap between the cooperative authority and the role authority of each link is minimum, and the repeated authority ratio of each matched user in the cooperative authority is minimum;

S5, controlling the rights of all links in the full life cycle by utilizing the best matching users and the competing rights allocation results among the best matching users in all links in the full life cycle meeting the requirements of the rights of the basic roles to obtain a rights control mode;

s6, dynamically adjusting the competitive right distribution result and the right control mode of the user by utilizing the internal environment element information, the external environment element information, the user right individual condition and the historical right competitive relationship of the data product asset, and realizing multi-user dynamic competitive right distribution control.

In a first aspect of the embodiment of the present invention, the obtaining the internal environment element information and the external environment element information of the data product asset on the data platform, and constructing the demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset includes:

acquiring internal environment element information and external environment element information of a data product asset;

when the data product asset can directly provide the internal environment element information and the external environment element information, directly constructing a demand model of the data product asset by utilizing the internal environment element information and the external environment element information;

And acquiring a data platform history database, and constructing a demand model of the data product asset by using the data platform history database when the data product asset cannot directly provide the internal environment element information and the external environment element information.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the obtaining a data platform history database, when the data product asset cannot directly provide the internal environment element information and the external environment element information, uses the data platform history database to construct a demand model of the data product asset, and the method includes:

acquiring a data platform historical database, and mining other data product assets related to the data product assets in the data platform historical database by using a data mining method;

processing the other data product assets related to the data product asset to obtain data product assets related to the data product asset structure and content;

the structure and content related data product assets form a related dataset;

processing the related data set to obtain a data product asset basic unit; the data product asset base unit can reflect the structure and content requirements of the data product asset;

Performing structure matching on the data product asset basic units to obtain a group basic unit set;

a set of group base units meeting the structure and content requirements of the data product asset, constituting a referenceable direct internal demand base unit set; the referred direct internal demand basic unit set forms a demand model of the data product asset;

according to the application scene record, the structure and content relation record, the market value record, the fluxion record and the safe credibility record of the basic unit in the historical database of the data platform, the application scene meeting the data product asset can refer to the external demand range, the structure and content relation of the other data product asset can refer to the external demand range, the market value can refer to the external demand range, the fluxion can refer to the external demand range and the safe credibility can refer to the external demand range.

In a first aspect of the embodiment of the present invention, the establishing a basic role authority table of each link of a full life cycle of a data product asset on a data platform by using a demand model of the data product asset includes:

establishing a relation table of all links of the whole life cycle of the data product asset and the relevant authority of the data product asset by utilizing the demand model of the data product asset;

Establishing a relationship table of the relative authority of the data product asset and the basic role of the data product asset by utilizing the demand model of the data product asset;

establishing a basic role authority table of each link of the full life cycle of a data product asset by utilizing a relation table of each link of the full life cycle of the data product asset and the related authority of the data product asset and a basic role relation table of the data product asset;

if the relation table is not directly provided, utilizing a data mining method to mine the data product data asset which is close to the internal and external environment elements of the data product asset in the historical database of the data platform;

counting a relation table set of related authorities of the data product asset, which is close to the internal and external environment elements of the data product asset, and the related authorities of the data product and the asset, and a relation table set of the related authorities of the data product asset and the basic roles of the data product data asset, wherein the relation table set of the related authorities of the data product asset and the data product asset are obtained through links such as rights determining, collecting, storing, using, processing, transmitting, providing, disclosing and the like;

the specific requirements of the data product assets are converted into specific authority requirements of basic roles corresponding to links of full life cycle of the data product assets on the data platform, such as validation, collection, storage, use, processing, transmission, provision, disclosure and the like.

In a first aspect of the embodiment of the present invention, the obtaining the user right personality condition and the history right bidding relationship on the data platform, and constructing the personalized right bidding model of the user by using the user right personality condition and the history right bidding relationship includes:

and analyzing authority personality conditions and historical authority competitive relations of the data owners, the data producers, the data users and the data managers by using a data mining method to obtain competitive relation data product assets and cooperative relation data product assets.

In a first aspect of the embodiment of the present invention, the determining, by using the user personalized permission bidding model and the basic role permission requirement, a result of bidding permission allocation between a best matching user and a best matching user in each link of a full life cycle that meets the basic role permission requirement includes:

the total authority of the data product asset is matched with an optimal target, the number of matched users of each link and each basic unit in the whole life cycle of the data product asset is minimum, the competing authority of each matched user is minimum, the gap between the role authority requirements of the cooperative authority and each link is minimum, and the repeated authority ratio of each matched user in the cooperative authority is minimum.

As an optional implementation manner, in the first aspect of the embodiment of the present invention, the controlling the rights of each link in the full life cycle by using the bidding rights allocation result of the best matching user of each link in the full life cycle meeting the requirements of the rights of the basic role to obtain a rights control mode includes:

Obtaining a permission control mode by utilizing the bidding permission distribution result of the best matching user of each link of the full life cycle meeting the basic role permission requirement;

the authority control mode comprises a first authority control mode and a second authority control mode;

the first permission control mode is used for judging a user with the largest permission ratio according to the bidding permissions of the best matched users of all links meeting the requirements when the best matched user set of a certain link and a certain basic unit meeting the requirements comprises more than two users, so that the user has the permission control rights of the link and the basic unit;

and the second authority control mode controls the authority for the method of consensus voting of all users.

The second aspect of the embodiment of the invention discloses a multi-user dynamic bidding authority allocation control device, which comprises:

the first processing module is used for acquiring the internal environment element information and the external environment element information of the data product asset on the data platform and constructing a demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset;

the second processing module is used for establishing a basic role authority table of each link of the full life cycle of the data product asset by utilizing the demand model of the data product asset;

the third processing module is configured to obtain a user authority personality condition and a history authority competition relationship on the data platform, and construct a personalized authority competition model of the user by using the user authority personality condition and the history authority competition relationship, and includes:

The fourth processing module is configured to determine, by using the personalized permission bidding model of the user and the basic role permission requirement, a best matching user and a bidding permission allocation result between the best matching users in each link of a full life cycle that meets the basic role permission requirement, where the fourth processing module includes:

The fifth processing module is used for controlling the rights of all links in the full life cycle by utilizing the best matching users and the competing rights allocation results among the best matching users in all links in the full life cycle meeting the requirements of the basic role rights to obtain a rights control mode;

and the sixth processing module is used for dynamically adjusting the competitive right distribution result and the right control mode of the user by utilizing the internal environment element information, the external environment element information, the user right personalized condition and the historical right competitive relationship of the data product asset, so as to realize the multi-user dynamic competitive right distribution control.

In a second aspect of the embodiment of the present invention, the obtaining the internal environment element information and the external environment element information of the data product asset, and constructing the demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset includes:

In a second aspect of the embodiment of the present invention, when the data product asset cannot directly provide the internal environment element information and the external environment element information, the method includes using the data platform history database to construct a demand model of the data product asset, where the demand model includes:

the structure and content related data product assets form a related dataset;

In a second aspect of the embodiment of the present invention, the establishing a basic role authority table of each link of a full life cycle of a data product asset on a data platform by using a demand model of the data product asset includes:

In a second aspect of the embodiment of the present invention, the obtaining the user right personality condition and the history right bidding relationship on the data platform, and constructing the personalized right bidding model of the user by using the user right personality condition and the history right bidding relationship includes:

In a second aspect of the embodiment of the present invention, the determining, by using the user personalized permission bidding model and the basic role permission requirement, a result of bidding permission allocation between a best matching user and a best matching user in each link of a full life cycle that meets the basic role permission requirement includes:

In a second aspect of the embodiment of the present invention, the controlling the rights of each link in the full life cycle by using the bidding rights allocation result of the best matching user of each link in the full life cycle meeting the requirements of the rights of the basic role to obtain a rights control mode includes:

The third aspect of the present invention discloses another apparatus for controlling allocation of dynamic bidding rights for multiple users, the apparatus comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to execute part or all of the steps in the multi-user dynamic race right allocation control method disclosed in the first aspect of the embodiment of the present invention.

The fourth aspect of the present invention discloses a computer storage medium, where the computer storage medium stores computer instructions, where the computer instructions are used to execute part or all of the steps in the multi-user dynamic bidding permission allocation control method disclosed in the first aspect of the present invention when the computer instructions are called.

Compared with the prior art, the embodiment of the invention has the following beneficial effects:

(1) The invention provides a multi-user dynamic bidding authority allocation control method and device, which have the advantages that the authority allocation and control is mainly the allocation and control of a unified role of a platform user, and the important solution is the authority allocation and control aiming at a specific object, unlike the current data platform. The method can be used for solving the problem that the current data platform permission distribution method lacks personalized scene adaptability and dynamic permission characteristics, and solving the problem that the general role permission defined by the traditional data platform permission distribution and control method can not cover and distinguish the different demands when the difference of the uniqueness demands of different permission objects on permission users is large, and particularly, the method aims at the data platform permission distribution and control scene taking data product assets as permission objects.

(2) Because the traditional current data platform performs authority distribution around the unified roles of platform users, when the difference of the uniqueness requirements of different authority objects on the authority users is large, the problem that the general role authorities defined by the conventional data platform authority distribution and control method can not cover and distinguish the difference requirements is more remarkable.

(3) The method caters to the authority allocation and control of four basic roles in each link of the data product asset, has the trend of multi-user dynamic bidding, and determines the authority allocation result which meets the authority requirements of the four basic roles in each link of the data product asset and meets the optimal target of the total authority matching of the data product asset through individual conditions of each user. The method has the advantages that the data product assets are better served through the bidding relation among the users, the best matched authority users of the data product assets are guaranteed, and the problem that the current data platform authority distribution method lacks personalized scene adaptability is solved.

(4) The invention solves the problem of centralized authority control of the current data platform on the authority control method, and determines the authority control authority of each link through the competing relationship among users, so that the authority users can fully exercise the corresponding authority control authority according to a certain rule.

(5) In the invention, the user authority allocation and control are dynamically adjusted according to the internal and external environment elements of the data product asset, the individual condition of each user and the dynamic change of the history bidding relationship, so as to solve the problem that the current data platform authority allocation and control method lacks dynamic authority characteristics.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic flow chart of a method for controlling allocation of multi-user dynamic bidding rights according to an embodiment of the present invention;

fig. 2 is a schematic structural diagram of a multi-user dynamic bidding authority allocation control device according to an embodiment of the present invention;

fig. 3 is a schematic structural diagram of another apparatus for controlling allocation of multi-user dynamic bidding permission according to an embodiment of the present invention.

Detailed Description

In order to make the present invention better understood by those skilled in the art, the following description will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order. Furthermore, the terms "comprise" and "have," as well as any variations thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, apparatus, article, or device that comprises a list of steps or elements is not limited to the list of steps or elements but may, in the alternative, include other steps or elements not expressly listed or inherent to such process, method, article, or device.

Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.

The invention discloses a multi-user dynamic bidding authority allocation control method, which can construct a specific demand model of a data product asset according to internal and external environment elements of the data product asset, establish four basic role authority tables of links such as the right confirming, collecting, storing, using, processing, transmitting, providing and disclosing of the whole life cycle of the data product asset on a data platform, and convert the specific demands of the data product asset into specific authority requirements of four basic roles corresponding to the whole life cycle of the data product asset on the data platform; analyzing authority individual conditions and historical authority competing relations of all users, constructing an individual authority competing model of all users, synthesizing the individual authority competing model of all users and four basic role authority requirements, deducing the competing authority range between users and all links which meet the requirements preliminarily, further constructing a competing authority range formula of the preliminarily matched users corresponding to all links and basic units of the data product asset, constructing a data product asset authority matching model with the total authority matching of the data product asset as an optimal target, and determining competing authority allocation results between users and all links and basic units which meet the four basic role authority requirements; controlling the rights of each link according to the rights required by the four types of basic roles, the best matching of each basic unit with users and the competing rights distribution results among the users; and dynamically adjusting user authority allocation and control according to the internal and external environment elements of the data product asset, the individual condition of each user and the dynamic change of the historical bidding relationship.

Example 1

Referring to fig. 1, fig. 1 is a flow chart of a multi-user dynamic bidding permission distribution control method disclosed in an embodiment of the present invention:

s3, acquiring a user authority individual condition and a historical authority competing relationship on a data platform, and constructing an individual authority competing model of the user by utilizing the user authority individual condition and the historical authority competing relationship;

s4, determining the best matching users and the bidding authority allocation results among the best matching users in all links of the full life cycle meeting the basic role authority requirements by utilizing the personalized authority bidding model of the users and the basic role authority requirements;

Optionally, the acquiring the internal environment element information and the external environment element information of the data product asset, and constructing a demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset, includes:

Optionally, the method includes, when the data product asset cannot directly provide the internal environment element information and the external environment element information, constructing a demand model of the data product asset by using the data platform history database:

the structure and content related data product assets form a related dataset;

Optionally, the establishing a basic role authority table of each link of the full life cycle of the data product asset on the data platform by using the demand model of the data product asset includes:

Optionally, the acquiring the user authority personality condition and the history authority bidding relationship on the data platform and constructing the personalized authority bidding model of the user by using the user authority personality condition and the history authority bidding relationship includes:

Optionally, the determining, by using the user personalized permission bidding model and the basic role permission requirement, the best matching user and the bidding permission allocation result between the best matching users in all links of the full life cycle meeting the basic role permission requirement includes:

Optionally, the controlling the rights of each link in the full life cycle by using the bidding rights allocation result of the best matching user in each link in the full life cycle meeting the requirements of the rights of the basic role to obtain a rights control mode includes:

Example two

Assuming that the data product asset a is the object of user rights allocation and control, the internal and external environmental elements of the data product asset a are classified into two types, an internal environmental element and an external environmental element. The internal environment elements of the user authority allocation and control of the data product asset A comprise the structure, the content, the self value, the security privacy and the like of the data product asset A. External environmental elements for user rights allocation and control of data product asset a include application scenarios, structural and content relationships with other data product assets, market value, fluxion, security trustworthiness, etc.

Accordingly, a specific demand model of the data product asset is constructed. When data product asset A can directly provide internal and external environmental element requirements, then a specific requirement model of data product asset A is directly built.

When the data product asset A cannot directly provide the internal and external environmental element requirements, then it is necessary to infer the internal and external environmental element requirement ranges of the data product asset A indirectly through the data platform history database.

And digging out other data product assets B(s) related to the data product asset A in a data platform historical database by adopting a data mining method such as clustering, gray correlation analysis, apriori algorithm and the like according to the structure and the content requirement (s=1, 2.,. The data product asset A is named as n). The parts of the other datase:Sub>A product assets B(s) that meet the structural and content requirements of the datase:Sub>A product asset ase:Sub>A are further mined, and these structural contents are extracted and built uniformly into ase:Sub>A datase:Sub>A set { PB-ase:Sub>A (d) } (d=1, 2. The datase:Sub>A set PB-A (d) is further statistically partitioned into ase:Sub>A series of base units PB-ase:Sub>A (d) reflecting the structure and content requirements of datase:Sub>A product asset A according to the structure and content requirements of datase:Sub>A product asset A. The structure of these base units is analytically matched with the content to yield a set of m groups of base units { pb-a (l) } m, (l, m=1, 2,.. The n.) that can meet the structure and content requirements of the data product asset a. The m-group set of base units { pb-a (l) } m that satisfy the structure and content requirements of data product asset A is referred to as the referenceable direct internal requirement base unit set group of data product asset A.

Accordingly, for the base units pb-a (l) in the m-group base unit set { pb-a (l) } m, the structure satisfying the data product asset a may be determined to refer to the internal demand range { st (pb-a (l)) } m, the content may refer to the internal demand range { co (pb-a (l)) } m, the self value may refer to the internal demand range { ov (pb-a (l)) } m, the security may refer to the internal demand range { pr (pb-a (l)) } m, and the self value may refer to the internal demand range { pr (pb-a (l)) according to the structure record st (pb-a (l)), the content record co (pb-a (l)), the self value of the base unit pb-a (l) in the data platform history database.

Accordingly, for the basic units pb-a (l) in the m-group basic unit set { pb-a (l) } m, according to the application scene record as (pb-a (l)) of the basic units pb-a (l) in the data platform history database, the structure and content relationship record rc (pb-a (l)) with other data product assets, the market value record mv (pb-a (l)), the fluxwell record cr (pb-a (l)), the security credibility record sc (pb-a (l)), the application scene meeting the data product asset a can be determined to refer to the external demand range { as (pb-a (l)) } m, the structure and content relationship with other data product assets can refer to the external demand range { rc (pb-a (l)) } m, the market value can refer to the external demand range { mv (pb-a (l)) } m, the fluxwell can refer to the external demand range { cr (pb-a (l)), the security credibility record sc (pb-a (l)), and the external demand range { pb-a (pb-a)) } m.

Optionally, establishing four types of basic role authority tables of links of full life cycle of the data product asset on the data platform, such as validation, collection, storage, use, processing, transmission, provision, disclosure and the like:

the full life cycle of the data product asset a includes links of rights, collection, storage, use, processing, transmission, provision, disclosure, etc. These links are labeled LI (a, k), where k represents the number of the validation, collection, storage, use, processing, transmission, provision, disclosure links, corresponding to numbers 1-8, respectively.

The four basic roles of data product asset a include data owner, data producer, data consumer, and data manager. These roles are labeled RO (a, g), where g represents the numbers of the data owner, the data producer, the data consumer, and the data manager, corresponding to numbers 1-4, respectively.

The rights associated with data product asset a include, but are not limited to: management rights, administration rights, transaction rights, ownership rights, production processing rights, and usage rights. The management rights include, but are not limited to, storage, query access, management related encryption rights, platform user rights allocation rights, access management rights, management related destruction rights, disposal rights, management rights, acquisition rights, service registration rights, and related income rights; the governance rights include, but are not limited to, administrative rights, jurisdictional restrictions rights, security rights, open rights, authentication rights, validation rights, authorization rights, and related revenue rights; the trade rights include, but are not limited to, trade control rights, trade enforcement rights, pricing bargained rights, assessment rights, multiple trade rights, distribution rights, circulation rights; ownership includes, but is not limited to, intellectual property rights, upload rights, security privacy rights, limit exclusion rights, modify change rights, transfer share rights, destroy rights, related revenue rights, dominant property allocation rights; production processing rights include, but are not limited to, intellectual property rights, processing rights, participation property distribution rights, and related revenue rights; usage rights include, but are not limited to, access rights, use rights, copy rights. Marking the rights as LA (A, (i, j)), wherein i represents the numbers of management rights, administration rights, transaction rights, ownership rights, production processing rights and use rights, and the numbers correspond to numbers 1-6 respectively; j represents the number of the specific authority respectively included in the management right, the administration right, the transaction right, the ownership, the production processing right and the use right, and the numbers are numbered sequentially from 1.

According to the full life cycle, four types of basic roles, related rights and marks thereof of the data product asset A, the established four types of basic role rights tables of links of the full life cycle, collection, storage, use, processing, transmission, provision, disclosure and the like of the data product asset A are LI-RO (A, k, g), and the relationship tables of the links of the right, collection, storage, use, processing, transmission, provision, disclosure and the like and the related rights of the data product asset A are LI-LA (A, k, (i, j)), and the relationship tables of the related rights of the data product asset A and the four types of basic roles of the data product asset A are LA-RO (A, (i, j), g). Wherein, each item value corresponding to each table can be 1 or 0, the relation is 1 if the relation is related, and the relation is 0 if the relation is uncorrelated.

The method is different from the traditional direct association method of business links and roles, in the process, the function of the related rights of the data product asset A is fully reflected, so that four basic role rights tables of links such as the right confirming, collecting, storing, using, processing, transmitting, providing and disclosing of the full life cycle of the data product asset on the data platform are established, and the rights tables are changed according to the specific conditions of the data product asset A.

In the method, the relation table LI-LA (A, k, (i, j)) of links such as right, collection, storage, use, processing, transmission, provision, disclosure and the like and the related rights of the data product asset A, and the relation table LA-RO (A, (i, j), g) of the related rights of the data product asset A and four basic roles of the data product asset A can be directly provided by a task right proposer of the data product asset A.

If no directly provided relationship table is available, it will be derived from the data platform history database. The specific method comprises the following steps: and mining the data product asset B (t) which is relatively close to the internal and external environment elements of the data product asset A in a data platform historical database by adopting a data mining method such as clustering, factor analysis and the like (t=1, 2. A set of relational tables { LI-LA (B (t), k, (i, j)) } for links of the statistical data product asset B (t) that are rights to the data product asset B by links of validation, collection, storage, use, processing, transmission, provision, disclosure, etc., and a set of relational tables { LA-RO (B (t), (i, j), g) } for the four basic roles of the data product asset B. For example: and calculating the inter-group distance and the intra-group distance through systematic clustering, and finding out the data product assets which are closer to the internal and external environment elements of the data product assets, namely are classified into the same category through a clustering algorithm in a historical database of the data platform, so as to obtain a corresponding relation table set. According to statistics, the two relation table sets are unified into two representative relation tables which are respectively used as relation tables LI-LA (A, k, (i, j)) of links of data product asset A, such as validation right, collection, storage, use, processing, transmission, providing, disclosure and the like, and related rights of the data product asset A, and relation tables LA-RO (A, (i, j), g) of related rights of the data product asset A and four basic roles of the data product asset A, so that four basic role rights tables LI-RO (A, k, g) of links of full life cycle of the data product asset on a data platform are obtained.

Optionally, the specific requirements of the data product asset are converted into specific authority requirements of four basic roles corresponding to the full life cycle of the data product asset on the data platform, wherein the four basic roles include validation, collection, storage, use, processing, transmission, provision, disclosure and the like.

Determining that the structure of the data product asset A is satisfied can refer to an internal demand range { st (pb-a (l)) } m, the content can refer to an internal demand range { co (pb-a (l)) } m, the self value can refer to an internal demand range { ov (pb-a (l)) } m, and the security privacy can refer to an internal demand range { pr (pb-a (l)) } m; it can be determined that the application scenario satisfying the data product asset a can refer to the external demand range { as (pb-a (l)) } m, the structure and content relationship with other data product assets can refer to the external demand range { rc (pb-a (l)) } m, the market value can refer to the external demand range { mv (pb-a (l)) } m, the fluxion can refer to the external demand range { cr (pb-a (l)) } m, and the security reliability can refer to the external demand range { sc (pb-a (l)) } m.

Four basic role authority tables LI-RO (A, k, g) of links such as confirmation, collection, storage, use, processing, transmission, provision, disclosure and the like of the full life cycle of the data product asset A on the data platform are established.

According to the corresponding relation between links such as the internal demand range and the external demand range and the full life cycle of the data product asset A, including the links such as the right, collection, storage, use, processing, transmission, provision, disclosure and the like and four types of basic roles, the specific right requirements of four types of basic roles RO (A, g) corresponding to the full life cycle of the data product asset A on the data platform are marked as LI-RO-dr (A, k, g, { pb-a (l) } m by filling the links such as the internal demand range and the external demand range into the four types of basic role rights tables LI-RO (A, k, g) of the full life cycle of the data product asset A on the data platform. Where dr is each referenceable internal demand range and each referenceable external demand range.

Establishing a personalized authority competing model of each user by analyzing authority individual conditions and historical authority competing relations of each user, establishing a quasi-data product asset authority matching model corresponding to a primary matching user and competing authority range, and determining the optimal matching users and competing authority distribution results among links meeting four basic role authority requirements by taking the optimal total authority matching of data product assets as a target;

Optionally, analyzing authority individual condition and historical authority competing relationship of each user to construct individual authority competing model of each user

The personalized authority competition model of each user is divided into a personalized authority condition model of each user and an authority competition model of each user.

And extracting authority individual conditions ppc (eu (z), O) of each user eu (z) (z=1, 2,..n) and a historical authority competing relationship hccr (eu (z), O) according to user authority distribution results corresponding to all data product assets O in the historical database of the data platform. The authority personality condition ppc (eu (z), O) of each user eu (z) (z=1, 2,) is defined as including the historical four basic roles RO (O, g) -eu (z), the historical authority HLA (O, (i, j)) -eu (z) corresponding data product asset O and the internal and external requirements dr (O) of the data product asset O. Can be directly extracted from the historical user rights allocation results. The authority individual condition of each user is formatted into an individual authority condition model F (ppc (eu (z), O)) of each user through a word cloud extraction and other formatting statistical methods.

Wherein the historical authority competing relationship of each user refers to that a certain data product asset Q historically determines the specific authority requirements LI-RO (Q, k, g) of four basic roles RO (Q, g) of LI (Q, k) in collection, storage, use, processing, transmission, provision, disclosure and the like of a full life cycle, and determines that each link deduced to preliminarily meet the requirements matches the cooperative action sy (euc (e), LI-RO (Q, k, g) or strives for independent fi (e), LI-RO (Q, k, g) existing between the users euc (e), wherein each link deduced to preliminarily meet the requirements matches the user euc (e) belonging to eu (z). The above bidding relation of each user is used for bidding a model E (hccr (E), Q) for the historical authority of a certain data product asset Q of each user by a formatting statistical method such as word cloud extraction.

The relationship hccr (eu (z), O) of each user corresponding to all the history data product assets O is known from the history authority race pattern E (hccr (eu (z), O)) of all the history data product assets O of each user. The bid relationship of data product asset A with all of the historical data product assets O is analyzed by comparison. The data product assets with the internal environment elements and the external environment elements being close to each other are called competitive relationship data product assets through data mining methods such as clustering and factor analysis, and the data product assets with the internal environment elements and the external environment elements having complementarity are called cooperative relationship data product assets.

Assuming that the data product asset a has a competing relationship with the historical data product asset C, the competing relationship between the same authority users of the data product asset a and the historical data product asset C is the same, and the historical authority competing pattern E (hccr (E), C)) of each user of the historical data product asset C is the authority competing pattern E (ccr (E), a) of each user of the data product asset a. E (ccr (euc (E), a))=e (hccr (euc (E), C)), i.e., [ sy (euc (E), LI-RO (a, k, g)), fi (euc (E), LI-RO (a, k, g)) ] = [ sy (euc (E), LI-RO (C, k, g)), fi (euc (E), LI-RO (C, k, g)) ].

Assuming that data product asset A has a cooperative relationship with historical data product asset C, the competing relationship between data product asset A and the same user of historical data product asset C is reversed, and the historical rights competing model E (hccr (E), C)) for each user of historical data product asset C is reversed from the rights competing model E (ccuc (E), A) for each user of data product asset A. E (hccr (euc (E), a)) = "E (hccr (euc (E), C)), i.e., [ sy (euc (E), LI-RO (a, k, g)), fi (euc (E), LI-RO (a, k, g)) ] = [ fi (euc (E), LI-RO (C, k, g)), sy (euc (E), LI-RO (C, k, g)) ].

Optionally, the personalized authority competition model of each user and four basic role authority requirements are synthesized, and the competition authority ranges of the users and the users who are matched with each link of the preliminary meeting requirements are deduced:

according to the personalized rights condition model F (ppc (eu (z), O)) of each user eu (z), the rights personalized conditions ppc (eu (z), O) of each user eu (z) (z=1, 2..n), include the historical four basic roles RO (O, g) -eu (z), history authority HLA (O, (i, j)) -eu (z) and internal and external requirements dr (O) of the data product asset O.

The rights race model E (ccr (E), A)) for each user according to the data product asset A includes the synergy sy (euc (E), LI-RO (A, k, g)) or striving for independent relationships fi (euc (E), LI-RO (A, k, g)) that exist between users euc (E) that meet the rights requirement LI-RO (A, k, g).

The specific authority requirements of four basic roles RO (A, g) of four types of links of data product asset A such as validation, collection, storage, use, processing, transmission, provision, disclosure and the like on the data platform are marked as LI-RO-dr (A, k, g, { pb-a (l) } m.

And judging which users have personalized authority conditions meeting the user authority requirements of the basic units pb-a (l) in the links according to the personalized authority condition model of each user in the sets, and taking all user sets meeting the user authority requirements of the links of the pb-a (l) m as alternative user sets AUS (LI (A, k) and pb-a (l) m of the links.

According to the authority race model of each user of the data product asset A, further judging the race relation and the corresponding authority of each user corresponding to the same basic unit pb-a (l) in each link user set AUS (LI (A, k), { pb-a (l) } m), wherein the race relation and the corresponding authority of each user corresponding to different links LI (A, k) of the same basic unit pb-a (l) are the race relation and the corresponding authority of each user corresponding to different links LI (A, k), and the race relation and the corresponding authority of the same link LI (A, k) of the different basic units pb-a (l) are the same.

The three types of relations are compared and analyzed, and matching users of all links which initially meet the requirements are screened out, wherein the specific method is as follows: the users with competition relationship in the same basic unit pb-a (l) in the same link LI (A, k) are divided into different groups, and the users with cooperation and relationship are divided into the same alternative group AG (LI (A, k), pb-a (l)); the users with competition relationship in different links LI (A, k) of the same basic unit pb-a (l) are divided into different groups, and the users with cooperation and relationship are divided into the same alternative group AG (LI' (A, k), pb-a (l)); the users with competition relationship in the same link LI (A, k) of different basic units pb-a (l) are divided into different groups, and the users with cooperation and relationship are divided into the same alternative group. According to the requirement of the data product asset A on the user bidding relation, the users in each alternative group AG (LI (A, k), pb-a (l)) can be called as all links matching users which preliminarily meet the requirement; or the intersection of each alternative group AG (LI (A, k), pb-a (l)) and the corresponding each alternative group AG (LI' (A, k), pb-a (l)) is called as each link matching user which preliminarily meets the requirement; the intersection of each alternative group AG (LI (A, k), pb-a (l)), each corresponding alternative group AG (LI '(A, k), pb-a (l)), and each corresponding alternative group AG (LI (A, k), pb-a' (l)) is referred to as each link matching user that preliminarily satisfies the requirements.

According to the bidding relation and corresponding authority of each user corresponding to the same link LI (A, k) of the same basic unit pb-a (l), the bidding relation and corresponding authority of each user corresponding to different links LI (A, k) of the same basic unit pb-a (l), the bidding relation and corresponding authority of each user corresponding to the same link LI (A, k) of different basic unit pb-a (l), and each link matching user ag (LI (A, k), pb-a (l)) which preliminarily meets the requirement is marked with the bidding authority CA (ag (LI (A, k), pb-a (l)). Because each link matching user meeting the requirement preliminarily is an alternative group or an intersection of alternative groups, the users are usually a plurality of alternative groups, and the bidding authorities of different alternative groups are integrated, so that the bidding authority range CA (ag (LI (A, k), { pb-a (l) } m) of each link matching user ag (LI (A, k), pb-a (l)) meeting the requirement preliminarily can be obtained.

Optionally, according to the matching users of each link meeting the requirement preliminarily and the bidding authority ranges among the matching users, constructing the bidding authority ranges of the primary matching users corresponding to each link and each basic unit of the data product asset:

the bidding authority range CA (ag (LI (A, k), { pb-a (l) } m) of the users ag (LI (A, k), pb-a (l)) is matched according to the links which preliminarily meet the requirements, and refers to a set of authority allocations corresponding to the bidding relation of the matched users ag (LI (A, k), pb-a (l)) of the basic units pb-a (l) corresponding to the links LI (A, k) and the basic units pb-a (l) corresponding to the other links LI (A, k) which preliminarily meet the requirements.

According to the bidding authority range CA (AG (LI (A, k)) of each link matching user AG (LI (A, k)) of each pb-a (l)) which initially meets the requirement, each link of the data product asset, the bidding authority range formula PAS { AG (A, k) } of the primary matching user corresponding to each basic unit, and { pb-a (l) } m, CA (AG (LI (A, k), { pb-a (l) } m) of each primary matching user are constructed.

Constructing a data product asset authority matching model by taking the optimal total authority matching of the data product asset as a target, and determining each link meeting the authority requirements of four basic roles, each basic unit optimally matching users and bidding authority allocation results among the users;

the optimal target of the total authority matching of the data product asset A is that the number of matched users of all links LI (A, k) and all basic units pb-a (l) of the data product asset A is minimum, the competing authority range is minimum in the competing authority range of all matched users of all links LI (A, k) and all basic units pb-a (l) of the data product asset A, the cooperative authority range and the repeated authority ratio of the range of the cooperative authority, which has minimum gap with the requirements of LI-RO-dr (A, k, g, { pb-a (l) } m) of four basic role authorities of all links, is minimum.

The total authority matching optimal targets of the data product assets A are established as conditional functions, and the data product asset authority matching models are jointly established according to the competitive authority range formulas PAS { AG (A, k), { pb-a (l) } m) of primary matching users corresponding to each link and each basic unit of the established data product assets, wherein CA (AG (LI (A, k), { pb-a (l) } m) is an optimal link matching user set meeting requirements, and further links meeting four basic role authority requirements, the best matching users of each basic unit and the competitive authority allocation results PAR { BAG (LI (A, k), { pb-a (l) } m), BCA (BAG (LI (A, k), { pb-a (l) } m) are obtained, and BCA (BAG (LI (A, k), { pb-a (l) } m) is an optimal link matching user set meeting requirements.

Optionally, controlling the rights of each link according to each link required by the rights of four types of basic roles, the best matching of each basic unit with users and the competing rights allocation result between the users;

and according to the obtained links meeting the requirements of four basic role rights, each basic unit is optimally matched with users and the bidding rights allocation results PAR { BAG (LI (A, k), { pb-a (l) } m) }, BCA (BAG (LI (A, k), { pb-a (l) } m) }.

Setting two authority control modes, namely, when a certain link meeting the requirements and an optimal matching user set BAG (LI (A, k), { pb-a (l) } m) of a certain basic unit comprise two or more users, determining control authority according to the method of meeting the competing authority BCA (BAG (LI (A, k), { pb-a (l) } m) of each link optimal matching user, judging the user with the largest competing authority ratio in the optimal matching user set to have the authority control authority of the link and the basic unit, and secondly, organizing the authority control authority of the link meeting the requirements and the optimal matching user set BAG (LI (A, k), { pb-a (l) } m) of the certain basic unit by all users, determining the control authority according to the method of reaching the consensus voting result, and finally determining the authority control authority of the link and the basic unit according to the vote ratio.

Optionally, the user rights allocation and control are dynamically adjusted according to the internal and external environmental elements of the data product asset, the individual condition of each user and the dynamic change of the history race relationship.

When the internal and external environment elements, the individual condition of each user and the historical authority competition relationship of the data product asset A change, the user authority allocation and control are dynamically adjusted by repeating the steps.

Example III

Referring to fig. 2, fig. 2 is a schematic structural diagram of a multi-user dynamic bidding permission distribution control device according to an embodiment of the present invention:

the first processing module S301 is configured to acquire internal environment element information and external environment element information of a data product asset on a data platform, and construct a demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset;

the second processing module S302 is configured to establish a basic role authority table of each link in the full life cycle of the data product asset by using the demand model of the data product asset;

the third processing module S303 is configured to obtain a user authority personality condition and a history authority competition relationship on the data platform, and construct a personalized authority competition model of the user by using the user authority personality condition and the history authority competition relationship;

a fourth processing module S304, configured to determine, by using the personalized rights competitive model of the user and the basic role rights requirement, a best matching user and a competitive rights allocation result between the best matching users in each link of the full life cycle that meets the basic role rights requirement;

A fifth processing module S305, configured to control rights of each link in the full life cycle by using the best matching user and the competing rights allocation result between the best matching users in each link in the full life cycle that meets the requirements of the rights of the basic roles, so as to obtain a rights control mode;

and a sixth processing module S306, configured to dynamically adjust the user' S bidding permission allocation result and permission control mode by using the internal environment element information, the external environment element information, the user permission personality condition, and the historical permission bidding relationship of the data product asset, so as to implement multi-user dynamic bidding permission allocation control.

Example IV

Referring to fig. 3, fig. 3 is a schematic structural diagram of another multi-user dynamic bidding permission distribution control device according to an embodiment of the present invention. As shown in fig. 3, the apparatus may include:

a memory 401 storing executable program codes;

a processor 402 coupled with the memory 401;

the processor 402 invokes executable program codes stored in the memory 401 for performing the steps in the multi-user dynamic race right allocation control method described in the first and second embodiments.

The apparatus embodiments described above are merely illustrative, in which the modules illustrated as separate components may or may not be physically separate, and the components shown as modules may or may not be physical, i.e., may be located in one place, or may be distributed over multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.

From the above detailed description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course by means of hardware. Based on such understanding, the foregoing technical solutions may be embodied essentially or in part in the form of a software product that may be stored in a computer-readable storage medium including Read-Only Memory (ROM), random-access Memory (Random Access Memory, RAM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), one-time programmable Read-Only Memory (OTPROM), electrically erasable programmable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic disc Memory, tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

Finally, it should be noted that: the embodiment of the invention discloses a multi-user dynamic bidding authority allocation control method and device, which are disclosed by the embodiment of the invention only for illustrating the technical scheme of the invention, but not limiting the technical scheme; although the invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that; the technical scheme recorded in the various embodiments can be modified or part of technical features in the technical scheme can be replaced equivalently; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.

Claims

1. A method for controlling allocation of multi-user dynamic bidding rights, the method comprising:

2. The method for controlling allocation of multi-user dynamic bidding rights according to claim 1, wherein the obtaining the internal environment element information and the external environment element information of the data product asset on the data platform, and constructing the demand model of the data product asset according to the internal environment element information and the external environment element information of the data product asset, comprises:

acquiring internal environment element information and external environment element information of data product assets on a data platform;

3. The multi-user dynamic bidding permission distribution control method of claim 2, wherein the obtaining a data platform history database, when the data product asset cannot directly provide the internal environment element information and the external environment element information, constructs a demand model of the data product asset by using the data platform history database, the method comprising:

the structure and content related data product assets form a related dataset;

4. The method for controlling allocation of multi-user dynamic bidding rights according to claim 1, wherein the creating a basic role rights table for each link of a full life cycle of a data product asset on a data platform by using a demand model of the data product asset comprises:

counting a relation table set of the related rights of the data product asset and the basic roles of the data product data asset by determining, collecting, storing, using, processing, transmitting, providing and disclosing the related rights of the links and the data product and the assets of the data product asset;

The specific requirements of the data product assets are converted into specific authority requirements corresponding to basic roles of the full life cycle of the data product assets on the data platform, namely, the steps of determining, collecting, storing, using, processing, transmitting, providing and disclosing.

5. The method for controlling allocation of multi-user dynamic bidding rights according to claim 1, wherein the step of obtaining the user rights personality and historical rights bidding relationships on the data platform and constructing a personalized rights bidding model of the user by using the user rights personality and historical rights bidding relationships comprises:

6. The method for controlling allocation of multi-user dynamic bidding rights according to claim 1, wherein determining the best matching users and the bidding rights allocation results between the best matching users in each link of the full life cycle meeting the basic role rights requirement by using the user personalized rights bidding model and the basic role rights requirement comprises:

7. The method for controlling allocation of multi-user dynamic bidding permissions according to claim 1, wherein the controlling the permissions of all links in the full life cycle by using the bidding permissions allocation result of the best matching user of all links in the full life cycle meeting the permission requirement of the basic role to obtain a permission control mode includes:

8. A multi-user dynamic bidding permission allocation control device, the device comprising:

9. A multi-user dynamic bidding permission allocation control device, the device comprising:

a memory storing executable program code;

a processor coupled to the memory;

the processor invokes the executable program code stored in the memory to perform the multi-user dynamic race right allocation control method of any one of claims 1-7.

10. A computer storage medium storing computer instructions which, when invoked, are operable to perform the multi-user dynamic race right allocation control method of any one of claims 1-7.