CN116415203A - Government information intelligent fusion system and method based on big data - Google Patents

Abstract

The invention discloses a government affair information intelligent fusion system and method based on big data, which are used for realizing the automation of big data analysis, decision support and decision execution of government affair information by integrating public information resources, thereby improving the efficiency and quality of government affair decision. The method can solve the technical problems of government information resource integration and management, government information big data analysis and government decision support.

Description

Government information intelligent fusion system and method based on big data

Technical Field

The invention relates to the technical field of government affair information fusion, in particular to an intelligent government affair information fusion system and method based on big data.

Background

The existing government information system has the following problems: on one hand, government information resources are not integrated and managed enough and unified; on the other hand, the analysis capability of the government affair information big data is weaker, so that the government affair decision support is not comprehensive enough. According to the invention, through integrating public information resources, big data analysis, decision support and automation of decision execution of government affair information are realized, so that the efficiency and quality of government affair decision are improved. The method can solve the technical problems of government information resource integration and management, government information big data analysis and government decision support. For example, in the field of social security, governments can utilize a big data government information intelligent fusion system to integrate various government information resources, analyze social security information, discover abnormal or irregular conditions in time and improve social security service efficiency and quality.

Disclosure of Invention

Therefore, the invention provides a government information intelligent fusion system and a government information intelligent fusion method based on big data, which aim to solve the problems that the government information resources are not integrated and managed sufficiently and uniformly in the existing government information system, and the government information big data analysis capability is weak, so that government decision support is not comprehensive enough.

In order to achieve the above object, the present invention provides the following technical solutions:

according to a first aspect of the embodiment of the invention, a government information intelligent fusion system based on big data is provided, and the system comprises an application layer, a service layer, a treatment layer, a convergence layer and a base layer;

the application layer is used for supporting various application scenes including a leading cockpit, a multi-role workbench, a classified service ledger, an online data report and a trusted information notice, and realizing multi-terminal access and operation management;

the service layer is used for providing data intelligent retrieval service, data intelligent recommendation service, data visualization service, trusted data circulation service, intelligent information processing service, intelligent data analysis service, internet data capture service and instant messaging service;

the treatment layer is used for integrating the capabilities of the service center and the data center, and the service center comprises: information model management, business logic management and functional logic management; the data center includes: data service management, resource catalog management and data quality rules;

The convergence layer is used for realizing interconnection and intercommunication of various data source bottom layers, sharing of various data and verification and supply of uplink trusted data through the data integration platform, the data sharing platform and the data trusted platform;

the base layer is used for realizing artificial intelligent service, trusted block chain service, big data computing service and application innovation center through integration of Internet, internet of things and intelligent networking bottom hardware facilities.

Further, the artificial intelligence service architecture specifically includes:

the intelligent application layer is used for realizing intelligent application scenes through various forms and channels, including semantic search, intelligent recommendation and expert suggestion;

the intelligent service layer is used for training various models based on machine learning/deep learning, and providing basic artificial intelligent service components and functions for upper-layer applications based on an AI general service, an AI development service and an AI customization service through an API gateway;

the basic processing layer is used for establishing a mapping relation between the structural information extracted from the basic data and entities, attributes and interrelations among the entities in the created machine learning and knowledge graph by adopting a distributed basic framework of the main flow technical platform, and providing a shared basic environment for upper intelligent service components and functions;

The data acquisition layer is used for extracting entities, attributes and interrelationships among the entities to realize unified acquisition and unified cleaning, conversion and loading for basic data of different sources and different structures, and providing high-quality data sources for an upper environment, wherein the basic data comprises structured data or unstructured data.

Further, the trusted blockchain service architecture specifically includes:

the business application layer is used for applying the block chain service to various scenes of various industries, so that various organization business applications can be abutted to the block chain platform, and the credibility and safety of business data are ensured;

the block chain platform layer is used for providing a block chain technical service platform and comprises a service management module, a channel management module and a member management module, so that the block chain network can be quickly created, conveniently managed and efficiently operated and maintained, and an enterprise-level block chain system can be provided for upper-layer applications;

the infrastructure layer is used for creating bottom layer resources which are needed to be used by the blockchain network, including node computing resources and storage resources, and is used for computing and storing data in the network;

the security management layer is used for being supported by a security system, and providing all-round security for block chain nodes, account books, intelligent contracts and upper-layer applications through innovative encryption algorithm composition.

Furthermore, the blockchain platform layer adopts a mature technical architecture, provides an interface comprising a CLI terminal, an event module, an SDK and a chain code API for application innovation center personnel, and provides blockchain services comprising identity management, account book management, transaction management, intelligent contract management, membership service, consensus service, chain code service, security and password service for upper-layer applications.

Further, the big data computing service architecture specifically includes:

the application display layer is used for providing a data model based on preset, and using data analysis, a user selects a data warehouse to perform an interactive query engine, and the specific forms comprise: intelligent retrieval of big data, intelligent data analysis, intelligent report forms, intelligent evaluation of electronic government network and the like;

the service support layer is used for providing general data service, data management and service providing capability of the data tag and effectively supporting the service of the application display layer;

the data mart layer is used for providing the capabilities of collecting, converging, calculating, developing, analyzing and establishing models of various data accessing to the big data calculation service;

the data source layer refers to original data such as relational databases, non-relational databases, logs, message queues and the like of various systems;

And the operation management layer is used for providing unified data operation and maintenance and operation management, and comprises the capabilities of cluster deployment, elastic expansion, job management and resource label management.

Further, the data architecture comprises:

data topic architecture: the basic subject library and the common subject library formed by means of data cleaning, standardization, scattering, reorganization and classification are basic data sources of all data applications and subject libraries around core business subjects such as personnel, documents, conferences, emergency, performance, processes and the like according to a subject-oriented modeling method of a data warehouse;

data standard system: based on an electronic government affair data standard system, expanding a provincial data standard system based on local business conditions to form a local data standard system, and servicing the data standard system, wherein each application can quickly acquire the data standard system for standard matching;

data service architecture: the capability of encapsulating and developing each platform and the data form a common and unified service system, and a unified service catalog is built, wherein the unified service catalog comprises a data interface service, an index service, a data authentication service, a tag service, a model service, an algorithm service, a metadata service and the like;

Data tag system: performing labeling processing on the core main data through means of statistics, rule processing, machine learning and the like;

data index system: an organic whole composed of a plurality of relatively independent and mutually-connected statistical indexes reflecting the overall quantity characteristics of the business;

data model architecture: general and common relation analysis models, association analysis models, machine learning models and the like, and form a systematic model catalog and market, and solidify business experience.

According to a second aspect of the embodiment of the present invention, a big data based government information intelligent fusion method is provided, the method is implemented based on the big data based government information intelligent fusion system, and the method includes:

acquiring multi-source government information resource data through a multi-source data fusion data interface, integrating and multi-source fusion processing the acquired government information resource data and establishing a government information resource library;

providing trusted government affair data capacity based on a blockchain, realizing function sharing of electronic certificates among multiple departments, storing data on a distributed blockchain, ensuring the safety of the data through an intelligent contract and a consensus mechanism, realizing multi-party data traceability through a distributed account book technology, and protecting data privacy through an application encryption technology;

And carrying out intelligent association analysis on the government affair information by adopting an artificial intelligence technology comprising machine learning, deep learning and natural language processing to obtain an association analysis result of the government affair information, wherein the association analysis result is used for providing a reference basis for government affair decision, supporting the government affair decision by utilizing an intelligent decision support system, and executing the decision through a preset rule and algorithm.

Further, the integration and multi-source fusion processing are carried out on the collected government information resource data, and the method specifically comprises the following steps:

and extracting, matching and fusing the data of different data sources, performing semantic analysis to form a new data storage format, and mining the fused data by using an AI technology and a big data technology to meet the service requirement.

Further, the intelligent association analysis is carried out on the government affair information by adopting artificial intelligence technology comprising machine learning, deep learning and natural language processing, and the intelligent association analysis method specifically comprises the following steps:

carrying out systematic classification and analysis on the government affair information according to keywords of the government affair information by utilizing a text classification algorithm, thereby obtaining a correlation analysis result between the government affair information;

clustering is carried out through text features of the government affair information by using a clustering algorithm to form clustering of the government affair information, so that correlation analysis results among the related government affair information are obtained.

According to a third aspect of an embodiment of the present invention, there is provided an electronic device including:

one or more processors;

a memory;

one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of the above.

The invention has the following advantages:

according to the government affair information intelligent fusion system and method based on the big data, the public information resource is integrated, so that the big data analysis, decision support and decision execution automation of the government affair information are realized, and the efficiency and quality of government affair decision are improved. The method can solve the technical problems of government information resource integration and management, government information big data analysis and government decision support.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It will be apparent to those of ordinary skill in the art that the drawings in the following description are exemplary only and that other implementations can be obtained from the extensions of the drawings provided without inventive effort.

Fig. 1 is a architecture diagram of a government information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 2 is an overall architecture of an artificial intelligent service in a government information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 3 is a block chain platform layer architecture diagram in the government information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 4 is a block chain platform layer operation state diagram in the government affair information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 5 is a data architecture diagram in the government information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 6 is a structure diagram of a pilot management cockpit in the government information intelligent fusion system based on big data provided in embodiment 1 of the present invention;

fig. 7 is a flowchart of a government information intelligent fusion method based on big data provided in embodiment 1 of the present invention;

fig. 8 is a schematic structural diagram of an electronic device according to embodiment 3 of the present invention.

Detailed Description

Other advantages and advantages of the present invention will become apparent to those skilled in the art from the following detailed description, which, by way of illustration, is to be read in connection with certain specific embodiments, but 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.

Example 1

In order to accelerate data open sharing, promote resource integration, promote government affair informatization level, strengthen scientific analysis decision-making ability, based on emerging technologies such as cloud computing, big data, artificial intelligence and blockchain, build "advanced, practical, open, high-efficient" credible government affair informatization platform, help comprehensive government affair informatization to fall to the ground, data asset deposit and knowledge asset accumulation, create the new mode of government affair management of fine informatization modernization.

Platform capability:

(1) Constructing a unified information platform and fusing multi-source data

Under the background of the 'Internet+' age, government affair data not only contains the existing data and information of all departments at all levels, but also needs to cover the public data such as texts, pictures, audios and videos from the Internet, and the trusted government affair informatization platform has the capability of flexibly gathering and processing multiple-source and multiple-class data.

(2) The government affair information management mechanism is standardized, and the full life cycle management and control of the data is realized

The method realizes data model standardization, data relation venation, data processing visualization and data quality quantification, and processes multi-source and multi-kind data of each department into standard and clean data asset to support daily work operation and scientific decision support.

(3) Establishing a government affair information cooperative sharing mechanism and improving information service capability

The trusted government affair data capacity based on the blockchain is provided, the electronic license is shared among multiple departments according to functions, the data are timely synchronized, privacy protection and tamper resistance are realized, and the multi-channel coordination and multi-scene use of the government affair service are supported by using the license tracing audit and the like.

(4) Strengthen information processing ability, promote intelligent level of government affair processing

The artificial intelligent processing technology is introduced to energize government affair informatization application systems in various fields, intelligent association analysis capability which is difficult to realize in a traditional technical mode is built, and the integral government data analysis capability is improved through information resource integration of social data, government affair data and the like, so that a new means is provided for effectively processing complex management problems.

The platform is characterized in that:

the trusted government affair informatization platform has strict requirements on safety, stability, performance, expansibility and portability, and can ensure that the system meets the technical standards of organization and relieve the worry of the following in the operation process.

(1) Domestic and autonomous controllable

The independent control of informatization technology has risen to the national strategy, and in the scheme design and actual project development, a system platform with independent intellectual property rights is adopted to provide source codes of a technical system.

(2) Advanced and mature nature

In the scheme design and actual project development, the technology which is advanced in the industry and verified in the actual application is adopted, including database technology, middleware technology, component technology, distributed computing technology and the like, and each link in the system construction and development process follows relevant international and national mainstream technical standards.

(3) Extensibility and maintainability

The system has good openness, and a sufficient expansion interface is arranged in consideration of possible expansion of the existing and future business and expansion of the system in design. The system is convenient to maintain and easy to manage, a visual management interface is provided, and a part of users are allowed to set.

(4) Stability and reliability

The system can perform uninterrupted stable operation for 24 hours throughout the day, single faults do not affect the operation and use of other modules, and the fault modules can be ensured to be repaired in time. Meanwhile, the construction of the system is carefully customized according to the actual demands of users, so that the system has good maturity and verifiability in the overall technical framework and the application logic structure, and the stability of the system is ensured.

(5) Security and confidentiality

On the basis of fully utilizing the existing safety conditions, the system safety is ensured in design and development, and the whole system has good safety management function.

The embodiment of the invention provides a government information intelligent fusion system based on big data, and the system architecture is shown in figure 1.

Platform architecture

1. Overall architecture

The trusted government affair informatization platform adopts a five-layer secondary system mode to carry out overall architecture design according to the design thought of standard unification, technical opening, information sharing, application coordination and service integration. The five layers include an application layer, a service layer, a treatment layer, a convergence layer and a base layer, and the two-layer system includes a safety guarantee system and a standard specification system. The overall architecture is shown in fig. 1.

(1) Application layer

The method is applied to the application scenes such as a pilot cockpit, a multi-role workbench, a classified service ledger, an online data report, a trusted information bulletin and the like. The application architecture of one network and multiple ends is adopted to support unified data, unified configuration and unified authority management, and realize multi-terminal access and operation management.

(2) Service layer

And providing data intelligent retrieval service, data intelligent recommendation service, data visualization service, trusted data circulation service, intelligent information processing service, intelligent data analysis service, internet data capture service and instant messaging service.

(3) Treatment layer

The service center and the data center are integrated, and the credible government affair informatization work quality improvement and innovation capability is supported together. The service center includes: information model management, business logic management and functional logic management; the data center includes: data service management, resource inventory management, and data quality rules. The system also comprises various data resources such as a model library, a basic library, a subject library, a thematic library, an application library and the like.

(4) Convergence layer

Through the data integration platform, the data sharing platform and the data trusted platform, interconnection and intercommunication of various data source bottom layers, sharing of various data and verification and supply of uplink trusted data are realized.

(5) Base layer

The artificial intelligent service, the trusted block chain service, the big data computing service and the application innovation center are externally realized through integration of the Internet, the Internet of things and the intelligent networking bottom hardware facilities.

2. Artificial intelligence service

The government affair data has the characteristics of multiple sources, abundant content, non-uniform format and larger unstructured data occupation, and the artificial intelligent service fully digs government affair data resources by relying on intelligent processing technologies such as knowledge graph, natural language processing and the like, and provides technical services such as information extraction, accurate analysis, comprehensive search, intelligent recommendation, trend research and judgment, logic reasoning and the like for various management works.

(1) Artificial intelligence application scenario

The development process of artificial intelligence is essentially a process of continuous liberation of human brain, and more knowledge work is gradually replaced by machines, and the development of various artificial intelligence application scenes is accompanied by further liberation of machine productivity. The artificial intelligence is extensive and various in application, and is embodied in the aspects of accurate analysis, intelligent recommendation, trend research and judgment, logic reasoning and the like of various scenes.

(1) And (3) accurate analysis:

government systems have accumulated considerable data, but these data do not have value, and many large data require significant labor costs. The fundamental reason of the phenomenon is that the mode of heavy convergence light analysis is ubiquitous in the construction process, technical measures such as machine learning, knowledge graph, natural language processing and the like are lacked in technical processing, the combination of application scenes and actual work is not tight, the analysis means lack of professional methodology guidance, knowledge base extraction and the like are lacked in information resources, and the accuracy and the fine analysis of big data are limited, so that the potential value of the big data is greatly reduced.

(2) And (3) comprehensive searching:

the comprehensive search is embodied in the aspects of accurate understanding of search intention and information relevance processing, so that the required information cannot be acquired in a fast-forward and accurate and comprehensive manner in a scene lacking scene context. The objects searched are more and more complex, the objects searched before are mainly text, and the searched content comprises pictures, sounds, codes, videos, design materials and the like. The granularity of searches is also becoming increasingly diverse. The existing search not only can make chapter-level search, but also can make paragraph-level, sentence-level and vocabulary-level search, and can implement cross-media comprehensive and association search.

(3) Intelligent recommendation:

intelligent recommendations behave in many ways, such as: based on the scene recommendation, a scene graph is established, and accurate recommendation based on the scene graph is realized. The data+algorithm+system is used as a core, and the knowledge and open semantic knowledge base accumulation which are arranged by the field expert are combined to provide the real-time content personalized intelligent recommendation service for the user.

(4) Intelligent interpretation:

the interpretability of intelligent systems is embodied in many specific tasks, including interpreting procedures, interpreting results, interpreting relationships, interpreting facts. The policy trend prediction analysis, trend research and judgment and other application scenes can be realized.

(5) Deep relationship reasoning:

deep relationship reasoning aims at finding and mining deep and hidden relationships. The application scenes such as knowledge and knowledge, automatic decomposition and the like can be realized.

(2) Artificial intelligence service architecture

The artificial intelligence service is divided into a knowledge service system layer, a domain knowledge graph layer and a domain knowledge acquisition layer by relying on the front technologies of knowledge graph, cognitive intelligence and the like. The overall architecture is shown in fig. 2 as follows:

(1) intelligent application layer:

through multiple forms and channels, the intelligent application scene is realized. Such as semantic searches, intelligent recommendations, expert advice, etc.

(2) Intelligent service layer:

Training various models based on machine learning/deep learning, and providing basic artificial intelligent service components and functions for upper-layer applications based on AI general services, AI development services and AI customization services through an API gateway.

(3) Base treatment layer:

and establishing a mapping relation between the structural information extracted from the basic data and entities, attributes and interrelationships among the created machine learning and knowledge graph by adopting a distributed basic framework of the mainstream technical platform. Providing a common base environment for upper intelligent service components and functions.

(4) Data acquisition layer:

the method is aimed at extracting entities, attributes and interrelationships among the entities from basic data (including structured data or unstructured data) with different sources and different structures to realize unified acquisition, unified cleaning, conversion and loading, and provides high-quality data sources for upper environments.

2. Trusted blockchain service

(1) Concept and features of blockchain

Blockchain (Blockchain) is a series of well-established organic combinations that perform distributed efficient logging of ledger-like critical information and provide sophisticated scripts to support different business logic. In a typical blockchain system, data is generated and stored in blocks and concatenated in a time sequence into a chained data structure. All nodes participate in data validation, storage, and maintenance of the blockchain system in common. The creation of a new block usually needs to be confirmed by most nodes of the whole network, and broadcast to each node to realize the whole network synchronization, and then the new block cannot be changed or deleted. Externally, the blockchain system should have the following features:

(1) Multiparty write, co-maintenance:

the billing participants of the blockchain consist of a plurality of entities that are not fully in agreement of interest and, during different billing periods, are dominated by different participants to initiate billing, while other participants will co-verify the accounting information initiated by the dominant.

(2) Public standing book:

the ledger of the blockchain system record is in a state where all participants are allowed access, and in order to verify the validity of the blockchain recorded information, the billing participants must have the ability to access the information content and ledger history. But public ledgers refer to the disclosure of accessibility and do not represent disclosure of information itself. Therefore, the privacy protection capability such as zero knowledge proof, homomorphic encryption, threshold encryption and the like is designed and applied to the field of blockchain so as to solve the problem that the validity of information can be verified through ciphertext operation.

(3) Decentralizing:

the blockchain should be a system that does not rely on a single trust center, and the blockchain itself can create trust between participants when processing data that involves only in-chain closed systems. However, in some cases, such as in the scenario of identity management, external data is inevitably introduced, and these data require trust endorsements by trusted third parties, where for different types of data, their trust should originate from different trusted third parties, rather than relying on a single trust center. In this case, the blockchain itself does not create trust, but rather acts as a carrier of trust.

(4) Non-tamperable:

as a most remarkable feature of the blockchain, non-tamper-resistance is a necessary condition of the blockchain system, not a sufficient condition, and many hardware-based technologies can also implement write-once, read-many times and tamper-proof, and typical examples are a write-once optical disc. The non-tamperable cryptographic-based hashing algorithm of the blockchain, and the feature that multiple parties maintain together, but at the same time due to this feature.

(2) Trusted blockchain service architecture

The trusted blockchain service passes through the business application layer, the blockchain platform layer, the infrastructure layer, and the security management capabilities. Providing a simple and easy to use blockchain service.

(1) Business application layer:

the blockchain service can be applied to various scenes of various industries, such as electronic archives, intellectual property rights and catalogue blockchains, so that various organization business applications can interface with a blockchain platform to ensure the credibility and safety of business data.

(2) Blockchain platform layer:

the provided blockchain technical service platform comprises service management, channel management, member management and other modules, and helps you to quickly create, conveniently manage and efficiently operate and maintain a blockchain network, and provides an enterprise-level blockchain system for upper-layer applications.

(3) Infrastructure layer:

the bottom layer resources needed to be used for creating the blockchain network comprise node computing resources, storage resources and the like, and are used for computing and storing data in the network.

(4) Security management capability:

the system is supported by a security system, and is formed by an innovative encryption algorithm, so that omnibearing security assurance is provided for block chain nodes, account books, intelligent contracts and upper-layer applications.

(3) Block chain platform layer technical architecture

The blockchain platform layer adopts a mature technical architecture, provides interfaces such as CLI terminals, event modules, SDKs, chain code APIs and the like for application innovation center personnel, and provides blockchain services such as identity management, account book management, transaction management, intelligent contract management and the like for upper-layer applications, as shown in fig. 3, and is specifically as follows:

(1) identity management:

the user registration certificate and the private key thereof are obtained and used for identity verification, message signature, signature verification and the like.

(2) And (3) account book management:

various ways are provided for querying and saving ledger data, such as querying block data for a specified block number.

(3) Transaction management:

and constructing and sending a signature proposal message request endorsement, checking legal request transaction ordering, packaging into blocks, and submitting an account book after verifying the transaction.

(4) Intelligent contract management:

and writing an intelligent contract program based on the chain code API, installing and instantiating the chain code, and requesting to execute the operation of changing the state by calling the chain code.

From the bottom layer perspective, the blockchain technology platform provides membership services, consensus services, chain code services, security and password services, and the like, as follows.

(1) Membership service:

the CA node provides member login registration service, receives application and authorizes new user certificates, private keys and the like, and manages the life cycle of the identity certificates. And carrying out authority management operations such as authentication on resource entities such as members and the like based on the identity certificate, wherein the members in the same object have a commonly trusted root certificate.

(2) Consensus service:

and simulating and executing proposal information through an Endorser endorsement node, requesting endorsing signatures such as simulation execution results, submitting the endorsement to an Orderer node consensus component to sort and package the transactions, and then submitting the transactions to a Committer billing node to verify the transactions and submit an account book. And a P2P network communication mechanism is provided based on a Gossip message protocol, so that efficient data distribution and state synchronization are realized, and the consistency of a node account book is ensured.

(3) Chain code service:

the method is characterized in that the method is based on a container to provide isolated running environment execution chain codes, supports chain code programs (intelligent contracts) developed by multiple languages, has good expandability, provides a perfect mirror image file warehouse management mechanism, and supports quick environment deployment and test.

(4) Security and password service:

the security and password service is packaged into a BCCSP component, and the BCCSP component provides service functions of generating a secret key, signing and verifying a message, encrypting and decrypting, obtaining a hash function and the like, has the characteristic of a pluggable component, and can expand a customized password security service algorithm (such as national password and the like).

As shown in FIG. 4, the blockchain platform tier operational state includes Client nodes, CA nodes, endorser endorsement nodes, committer billing nodes, leader master nodes, orderer ordering nodes, and the like.

(4) Blockchain and new technology fusion

Blockchain technology can be used as a bottom support for data security, data trust services (data consistency) in the traditional informatization field, and provides independent, trusted data services and software services for underlying big data analysis and cloud computing applications. The blockchain can be further extended to business applications such as energy management, intelligent manufacturing, supply chain management, digital asset transaction and the like by combining with new generation information technologies such as the Internet of things and artificial intelligence, and the optimization and innovation of energy business are promoted.

(1) Blockchain and big data:

because the blockchain technique adopts an incremental data storage method, the data in the blockchain is increased along with the time, so that the block has the relevant characteristic of big data.

The distributed storage characteristic of the block data is reflected in the data storage of the large-scale peer nodes, through a regular data consensus process, the data consistency of the peer nodes is realized, the anti-attack capability of the data is realized, and the security of core data can be enhanced.

In the specific application process, the block chain technology can be used for enhancing the safety of data in three stages of data in-chain, uplink and out-chain, and improving the credibility of the data.

(2) Blockchain and cloud computing:

currently, the mainstream technology platform uses blockchain technology as a novel data service technology in the cloud platform, namely 'blockchain as service', and provides data service and intelligent contract service outwards in a unified manner. The blockchain technology can be combined with each layer of cloud computing, shared resources and service platforms are provided by utilizing the cloud computing, the service quality of the blockchain is greatly improved, and meanwhile, the safety and service reliability of a cloud environment are improved.

In a basic resource layer, the blockchain technology is combined with the resource pool technology, so that on one hand, the data storage capacity and the consensus operation efficiency of the blockchain service can be improved, and on the other hand, the trusted authentication of access resources in a cloud environment can be realized, and the trusted and traceable resource management and control can be realized.

In the platform service layer, the blockchain technology is used as an effective service authentication means, so that the credible authentication of different services in the PaaS platform can be realized, the consistency of the respective service calling processes is ensured, and the safety of the service calling processes is improved.

In a software service layer, the blockchain intelligent contract technology is used as an effective authorization means, so that authorized software authorization using functions can be realized, the service functions of a software calling process chain are enhanced, the automatic execution capability is improved, and the operation efficiency is improved.

(3) Blockchain and thing networking:

the decentralization characteristic of the block chain provides a method for self-management of the Internet of things, so that the Internet of things equipment can be helped to understand the relationship among different equipment, and decentralization control of the distributed Internet of things is realized.

The blockchain technology can improve the equipment security in the internet of things environment. By utilizing the non-tamperable and traceable characteristics of the blockchain technology, the trusted authentication of the access equipment is realized, so that the equipment safety in the Internet of things environment is improved.

Blockchain technology may enhance the communication security of devices in the internet of things. By utilizing an asymmetric encryption algorithm and a consensus mechanism in the block chain, slicing management of a communication channel is realized, and the efficiency and the safety of data transmission are improved.

By using the blockchain technology at the equipment layer, the network layer, the service layer and the application layer, the channel slice management capability and the data transmission security capability in the communication process of the Internet of things equipment are improved.

(4) Blockchain and artificial intelligence:

with the enhancement of hardware computing capability and the development of data storage means, the artificial intelligence technology has become a general core technology and can be widely applied to different fields. The traceability and non-tamperability of data supported by the blockchain technology is the basis of data analysis and data mining in the artificial intelligence technology, and is the core guarantee most needed by the artificial intelligence technology at present. Because only the analysis and learning algorithm based on the trusted data has the meaning of data analysis, the blockchain is tightly combined with the upper artificial intelligence technology in a manner of supporting the bottom layer data.

Intelligence in blockchain technology is embodied in both the area of intelligent contracts and time series data analysis. The safe, efficient and accurate execution of intelligent contracts is the core of intelligent technology, and the scene analysis capability and the intelligent judgment capability of artificial intelligence are combined to improve the contract execution efficiency. In the field of time sequence data analysis, the credibility of data analysis is improved through time sequence and non-tamper property of block data, and the learning of the data mining process is accelerated.

3. Big data computing service

The management and application of big data is an important challenge facing the internet age: the data volume generated by each link in each field is larger, the data variety is more and more, and the data generation speed is faster and faster. Conventional data processing techniques, such as stand-alone storage, relational databases have failed to address these new large data problems.

The big data computing service adopts a mature and stable distributed computing technology, fully utilizes the computing and storage capacity of the clusters, and completes the processing of mass data. The system supports distributed computing, distributed data storage, distributed memory computing and distributed stream data computing, has the capability of carrying out rapid customization development according to the service requirement in the follow-up, helps governments to rapidly construct a mass data information processing system, and is used for analyzing and mining mass information data in real time and non-real time.

(1) Big data computing service architecture

The big data computing service adopts a mode of four layers and operation management to carry out overall architecture design. "four layers" include application presentation, service support, data marts, and data sources, "operations management" provides centralized data operations, operations management for large data computing services.

(1) Application display layer:

providing a data model based on preset, using data analysis, a user can select a data warehouse to perform an interactive query engine, and the specific forms comprise: big data intelligent retrieval, intelligent data analysis, intelligent report forms, intelligent evaluation of electronic government networks and the like.

(2) Service support layer:

the universal data service, data management and data tag service providing capability is provided, and effective service support is carried out on the application display layer.

(3) Data mart layer:

the method provides the capabilities of collection, aggregation, calculation, development, analysis and model establishment of various data access to the big data calculation service.

(4) Data source layer:

the system mainly refers to original data such as relational databases, non-relational databases, logs, message queues and the like of various systems.

(5) Operation management:

the operation management provides unified data operation and maintenance, operation management, including cluster deployment, elastic expansion, operation management and resource label management.

(2) Data architecture

The data system mainly surrounds data application requirements and service scenes, and forms a systematic, common and universal data structure for the whole data resources through means of classification, organization, summarization, calculation and the like, so as to provide core production data for data application. As shown in fig. 5, mainly includes the following:

(1) Data topic architecture:

the basic subject database and the common subject database are formed by means of data cleaning, standardization, scattering, reorganization, classification and the like around the core business subjects of personnel, documents, conferences, emergencies, performance, flows and the like according to the subject-oriented modeling method of the data warehouse, and are basic data sources of all data applications and subject databases.

(2) Data standard system:

based on the electronic government affair data standard system, the provincial data standard system is expanded based on the local business condition to form a local data standard system, the data standard system is served, and each application can quickly acquire the data standard system for standard matching.

(3) Data service architecture:

the capability of each platform and the data are packaged and developed to form a common and unified service system, and a unified service catalog is built, wherein the unified service catalog comprises a data interface service, an index service, a data authentication service, a label service, a model service, an algorithm service, a metadata service and the like.

(4) Data tag system:

labeling the core main data (such as people, documents and the like) by means of statistics, rule processing, machine learning and the like;

(5) data index system:

The system is an organic whole formed by a plurality of relatively independent and mutually-connected statistical indexes reflecting the overall quantity characteristics of the business.

(6) Data model architecture:

general and common relation analysis models, association analysis models, machine learning models and the like, and form a systematic model catalog and market, and solidify business experience.

(3) Data visualization

The data visualization construction provides the secondary data, algorithm, training, model and service full-flow visualization capability for the artificial intelligent service, and can realize quick construction of the visual data presentation page.

And (3) data visualization construction:

a rich variety of visualization components: rich visualization components are provided, including commonly used data charts, graphs, controls, and the like.

Professional level geographic information visualization: the effects of drawing geographic tracks, geographic flying lines, thermodynamic distribution, region blocks, 3D earth and the like are supported, and the multilayer superposition of geographic data is supported.

Graphical editing interface: the free configuration and layout of the components can be completed by dragging, the visual large screen can be easily built without programming, and the size of the large screen can be freely customized according to the resolution of the throwing equipment.

A variety of data sources support: and the seamless integrated data warehouse service, the data lake exploration, the relational database, the object storage service and the like support local CSV, online APIs and private cloud data inside enterprises.

The pilot management cockpit has intuitiveness, comprehensiveness, convenience, multidimensional property and configurability, can greatly assist government managers to know relevant decision information, grasp main problems and main aspects of the problems, and early warn potential problems, so that the government can better realize external service and management targets.

The design of the cockpit system needs to pay attention to the key business index system, and the contents of the three aspects of the internal flow structure and the external module structure are specifically described as follows, as shown in fig. 6.

(1) Intuitiveness of

The page entering the cockpit is just like entering the automobile cockpit, various graphical interfaces such as pressure dial plates and the like are displayed in front of the page, and specific data of various key indexes in the operation process of government affairs are reflected by the graphics unlike the automobile cockpit, so that a manager can more intuitively and comprehensively know the specific conditions of the key indexes in the government affairs in a dynamic mode, and further, the next decision is conveniently and quickly made.

(2) Configurability of

The pilot cockpit can be flexibly configured through the data visualization construction platform, proper graphics are selected to display specific indexes to be understood according to user habits, one graphic can reflect various indexes, one index can be in a mode of realizing intersection of multiple graphic displays, and configuration is more flexible.

(3) Convenience of use

After the configuration of the leading cockpit is finished, the configurations can be stored, and the configuration can be realized only by one-step operation in order to check the display conditions of various indexes under the configuration, thereby truly realizing the design idea that the operation of a user is more convenient.

(4) Comprehensive performance

The pilot cockpit fully considers the best acceptance number of people to the graphics, six graphics can be configured on the first layer, the same index, different conditions and the second layer display of different graphics can be formed on the basis of each graphic, and the user can master each index in the department and the department more comprehensively.

(5) Multidimensional character

The pilot cockpit really realizes different operations of multiple users and different authorities, and each authority user can configure graphics suitable for the user, so that each management layer can check service operation indexes concerned by the user, and the multi-user, multi-authority, multi-graphics and multi-index multi-dimensional operation is realized technically and in an implementation manner.

Example 2

Corresponding to the above embodiment 1, this embodiment proposes a big data based government information intelligent fusion method, which is implemented based on the big data based government information intelligent fusion system described in the above embodiment 1, as shown in fig. 7, and includes:

S100, acquiring multi-source government information resource data through a multi-source data fusion data interface, integrating and multi-source fusion processing the acquired government information resource data, and establishing a government information resource library.

Through the interface of multisource data fusion, deep and comprehensive fusion processing of data and information of different government data sources is achieved. The data of different data sources are extracted, matched and fused together, semantic analysis is carried out, a new data storage format is formed, and the fused data is mined again by utilizing an AI technology and a big data technology so as to meet the service requirement. For example, the internet text data and the existing government affair data are fused to extract accurate government affair information, and a richer and clearer intelligent application scene of the government affair is constructed according to the government affair information.

Multisource data fusion refers to integrating data from different data sources into a unified data set to provide more accurate and complete information. It requires valuable information to be extracted from the multi-source data and incorporated into a complete database to provide more accurate information.

The data interface of the multi-source data fusion comprises: network data interfaces, database data interfaces, file data interfaces, structured data interfaces, and the like.

The processing procedure of the multi-source data fusion comprises the following steps: data cleansing, data format conversion, data extraction, data conversion, data aggregation, etc.

The result of the multi-source data fusion processing is a unified and queriable database, which can provide more accurate information for users, thereby improving the working efficiency. For example, the government can integrate the data of each department into a joint database through a multi-source data fusion mode, so that comprehensive government information can be known in a more accurate mode, and more efficient management can be realized.

And S200, providing trusted government data capacity based on a blockchain, realizing job-based sharing of electronic certificates among multiple departments, storing data on a distributed blockchain, ensuring the safety of the data through an intelligent contract and a consensus mechanism, realizing multi-party data traceability through a distributed ledger wall technology, and protecting data privacy through an application encryption technology.

Data processing of the blockchain component is accomplished using blockchain techniques. The intelligent integration system is used for constructing a trusted intelligent integration system of big data government affair information so as to protect the data security and privacy of citizens.

The function of the blockchain component is:

1. By storing the data on the distributed blockchain, the integrity, non-tamper ability and traceability of the data are protected, and the data leakage, tampering and falsification are effectively prevented.

2. The security of the data is ensured through the intelligent contract and the consensus mechanism, and the data can be effectively prevented from being illegally tampered, leaked or stolen.

3. The multi-party data traceability can be realized through the distributed account book technology, so that the reliability of the data is ensured.

4. By applying encryption techniques, the privacy of the data can be more effectively protected.

5. By providing a powerful data analysis function, information can be more effectively analyzed and acquired, thereby improving government efficiency.

The technical choice is made according to the requirements of government information, such as ethernet, hyperledecrfabric, risple, corda.

S300, performing intelligent association analysis on government affair information by adopting an artificial intelligence technology comprising machine learning, deep learning and natural language processing to obtain an association analysis result of the government affair information, wherein the association analysis result is used for providing a reference basis for government affair decision, supporting the government affair decision by utilizing an intelligent decision support system, and executing the decision through a preset rule and algorithm.

Intelligent association analysis of government information can be realized by adopting artificial intelligence technology combining machine learning, deep learning and natural language processing. For example, a text classification algorithm is used to systematically classify and analyze the government information according to the keywords of the government information, so as to obtain the relevance analysis between the government information. In addition, the intelligent association analysis of the government information uses a clustering algorithm to cluster through text features of the government information so as to form a cluster of the government information, thereby acquiring the association analysis among the related government information. The result of the association analysis is the ability to discover associations between government information and to help form a reference basis for policy decisions.

The specific functions executed by each step in the government information intelligent fusion method based on big data provided by the embodiment of the invention are described in detail in the above embodiment 1, so that redundant description is omitted here.

Example 3

An embodiment of the present invention proposes an electronic device, and fig. 8 is a schematic entity structure of the electronic device provided by the present invention, where the electronic device may include: processor 1010, memory 1020, input/output interface 1030, communication interface 1040, and communication bus 1050, wherein processor 1010, memory 1020, input/output interface 1030, and communication interface 1040 communicate with each other via communication bus 1050. One or more programs are stored in the memory 1020 and configured to be executed by the one or more processors 1010, the one or more programs configured to perform the NLP recognition and knowledge base construction method described in the above embodiments.

Example 4

In correspondence with the above-described embodiments, the present embodiment proposes a computer storage medium, in which one or more program instructions are included, the one or more program instructions being configured to be intelligently fused by a government information based on big data to perform the method as in embodiment 1.

While the invention has been described in detail in the foregoing general description and specific examples, it will be apparent to those skilled in the art that modifications and improvements can be made thereto. Accordingly, such modifications or improvements may be made without departing from the spirit of the invention and are intended to be within the scope of the invention as claimed.

Claims (10)

1. The government affair information intelligent fusion system based on big data is characterized by comprising an application layer, a service layer, a treatment layer, a convergence layer and a base layer;

the application layer is used for supporting various application scenes including a leading cockpit, a multi-role workbench, a classified service ledger, an online data report and a trusted information notice, and realizing multi-terminal access and operation management;

the service layer is used for providing data intelligent retrieval service, data intelligent recommendation service, data visualization service, trusted data circulation service, intelligent information processing service, intelligent data analysis service, internet data capture service and instant messaging service;

The treatment layer is used for integrating the capabilities of the service center and the data center, and the service center comprises: information model management, business logic management and functional logic management; the data center includes: data service management, resource catalog management and data quality rules;

the convergence layer is used for realizing interconnection and intercommunication of various data source bottom layers, sharing of various data and verification and supply of uplink trusted data through the data integration platform, the data sharing platform and the data trusted platform;

the base layer is used for realizing artificial intelligent service, trusted block chain service, big data computing service and application innovation center through integration of Internet, internet of things and intelligent networking bottom hardware facilities.

2. The intelligent government affair information fusion system based on big data according to claim 1, wherein the artificial intelligence service architecture specifically comprises:

the intelligent application layer is used for realizing intelligent application scenes through various forms and channels, including semantic search, intelligent recommendation and expert suggestion;

the intelligent service layer is used for training various models based on machine learning/deep learning, and providing basic artificial intelligent service components and functions for upper-layer applications based on an AI general service, an AI development service and an AI customization service through an API gateway;

The basic processing layer is used for establishing a mapping relation between the structural information extracted from the basic data and entities, attributes and interrelations among the entities in the created machine learning and knowledge graph by adopting a distributed basic framework of the main flow technical platform, and providing a shared basic environment for upper intelligent service components and functions;

the data acquisition layer is used for extracting entities, attributes and interrelationships among the entities to realize unified acquisition and unified cleaning, conversion and loading for basic data of different sources and different structures, and providing high-quality data sources for an upper environment, wherein the basic data comprises structured data or unstructured data.

3. The intelligent government information fusion system based on big data according to claim 1, wherein the trusted blockchain service architecture specifically comprises:

the business application layer is used for applying the block chain service to various scenes of various industries, so that various organization business applications can be abutted to the block chain platform, and the credibility and safety of business data are ensured;

the block chain platform layer is used for providing a block chain technical service platform and comprises a service management module, a channel management module and a member management module, so that the block chain network can be quickly created, conveniently managed and efficiently operated and maintained, and an enterprise-level block chain system can be provided for upper-layer applications;

The infrastructure layer is used for creating bottom layer resources which are needed to be used by the blockchain network, including node computing resources and storage resources, and is used for computing and storing data in the network;

the security management layer is used for being supported by a security system, and providing all-round security for block chain nodes, account books, intelligent contracts and upper-layer applications through innovative encryption algorithm composition.

4. The intelligent government information fusion system based on big data according to claim 3, wherein the blockchain platform layer adopts a mature technical architecture, provides an interface comprising a CLI terminal, an event module, an SDK and a chain code APl for application innovation center personnel, and provides blockchain services comprising identity management, account book management, transaction management, intelligent contract management, membership services, consensus services, chain code services, security and password services for upper-layer applications.

5. The intelligent government affair information fusion system based on big data according to claim 1, wherein the big data computing service architecture specifically comprises:

the application display layer is used for providing a data model based on preset, and using data analysis, a user selects a data warehouse to perform an interactive query engine, and the specific forms comprise: intelligent retrieval of big data, intelligent data analysis, intelligent report forms, intelligent evaluation of electronic government network and the like;

The service support layer is used for providing general data service, data management and service providing capability of the data tag and effectively supporting the service of the application display layer;

the data mart layer is used for providing the capabilities of collecting, converging, calculating, developing, analyzing and establishing models of various data accessing to the big data calculation service;

the data source layer refers to original data such as relational databases, non-relational databases, logs, message queues and the like of various systems;

and the operation management layer is used for providing unified data operation and maintenance and operation management, and comprises the capabilities of cluster deployment, elastic expansion, job management and resource label management.

6. The intelligent government information fusion system based on big data according to claim 1, wherein the data architecture comprises:

data topic architecture: the basic subject library and the common subject library formed by means of data cleaning, standardization, scattering, reorganization and classification are basic data sources of all data applications and subject libraries around core business subjects such as personnel, documents, conferences, emergency, performance, processes and the like according to a subject-oriented modeling method of a data warehouse;

Data standard system: based on an electronic government affair data standard system, expanding a provincial data standard system based on local business conditions to form a local data standard system, and servicing the data standard system, wherein each application can quickly acquire the data standard system for standard matching;

data service architecture: the capability of encapsulating and developing each platform and the data form a common and unified service system, and a unified service catalog is built, wherein the unified service catalog comprises a data interface service, an index service, a data authentication service, a tag service, a model service, an algorithm service, a metadata service and the like;

data tag system: performing labeling processing on the core main data through means of statistics, rule processing, machine learning and the like;

data index system: an organic whole composed of a plurality of relatively independent and mutually-connected statistical indexes reflecting the overall quantity characteristics of the business;

data model architecture: general and common relation analysis models, association analysis models, machine learning models and the like, and form a systematic model catalog and market, and solidify business experience.

7. A big data based government information intelligent fusion method, the method is realized based on the big data based government information intelligent fusion system according to any one of claims 1-6, the method comprises:

Acquiring multi-source government information resource data through a multi-source data fusion data interface, integrating and multi-source fusion processing the acquired government information resource data and establishing a government information resource library;

providing trusted government affair data capacity based on a blockchain, realizing function sharing of electronic certificates among multiple departments, storing data on a distributed blockchain, ensuring the safety of the data through an intelligent contract and a consensus mechanism, realizing multi-party data traceability through a distributed account book technology, and protecting data privacy through an application encryption technology;

and carrying out intelligent association analysis on the government affair information by adopting an artificial intelligence technology comprising machine learning, deep learning and natural language processing to obtain an association analysis result of the government affair information, wherein the association analysis result is used for providing a reference basis for government affair decision, supporting the government affair decision by utilizing an intelligent decision support system, and executing the decision through a preset rule and algorithm.

8. The intelligent government affair information fusion method according to claim 7, wherein the integration and multi-source fusion processing are carried out on the collected government affair information resource data, and the method specifically comprises the following steps:

and extracting, matching and fusing the data of different data sources, performing semantic analysis to form a new data storage format, and mining the fused data by using an AI technology and a big data technology to meet the service requirement.

9. The intelligent government affair information fusion method according to claim 7, wherein the intelligent association analysis of government affair information is carried out by adopting artificial intelligence technology comprising machine learning, deep learning and natural language processing, and the intelligent association analysis method specifically comprises the following steps:

carrying out systematic classification and analysis on the government affair information according to keywords of the government affair information by utilizing a text classification algorithm, thereby obtaining a correlation analysis result between the government affair information;

clustering is carried out through text features of the government affair information by using a clustering algorithm to form clustering of the government affair information, so that correlation analysis results among the related government affair information are obtained.

10. An electronic device, the electronic device comprising:

one or more processors;

a memory;

one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs configured to perform the method of any of claims 7-9.

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