CN116361455A - Cloud data center virtualization system based on financial information creation construction - Google Patents
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Abstract
The invention relates to the field of financial information creation equipment, and discloses a cloud data center virtualization system based on financial information creation, which comprises a planning module, an implementation module, an acceptance storage module, a management module and a cloud data center, wherein the planning module transmits engineering planning results to the implementation module, the implementation module receives data information of the planning module and then continuously gathers and transmits the data information to the management module, the management module carries out compliance check on document delivery in the project process by managing documents and business states in the information creation project, tracks and rectifies illegal problems to finally reach standards, and the management module and the cloud data center are arranged to be favorable for combining the financial information creation with the cloud data and the virtualization system, and meanwhile, the management module carries out classification and arrangement on the documents, so that the degree of informatization construction in the document professional degree and the information creation process is improved.
Description
Technical Field
The invention relates to the field of financial information creation equipment, in particular to a cloud data center virtualization system based on financial information creation.
Background
The financial creation means that the domestic replacement of software and hardware is realized by pulling and constructing a financial information technology infrastructure system through the practice of financial digitization, the aim is to solve the problem of a key technical link of the financial industry, namely, a card neck, so as to ensure the comprehensive safety of the financial field, the data center virtualization is to convert a physical data center into a digital data center by using a cloud software platform, so that a company can remotely access information and application programs, a virtual server is created from a traditional physical server in the virtualized data center, the process abstracts the physical hardware by simulating a processor, an operating system and other resources thereof with the help of a management program, the management program is software for creating and managing virtual machines, and resources such as a CPU, a memory and a storage are regarded as a pool, and the resources can be easily redistributed among the existing virtual machines or among new virtual machines.
However, the existing financial credit creation is not combined with cloud data and a virtualization system, so that resources cannot be integrated by utilizing a virtualization data center, meanwhile, the existing project management and document collaborative software of a financial institution is not suitable for credit creation project management, key elements of credit creation cannot be electronized, documents are not reasonably managed and classified, difficulty of credit creation project construction management is increased, informatization construction degree is not high in a credit creation process, and document professionality related to project projects cannot be guaranteed.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a cloud data center virtualization system based on financial credit construction, which aims to solve the problems in the background art.
The invention provides the following technical scheme: the utility model provides a cloud data center virtualization system based on financial credit construction, includes planning module, implementation module, acceptance storage module, still includes management module and cloud data center, planning module transmits the engineering planning result to implementation module, implementation module continues to gather data information and transmits to management module after receiving the data information of planning module, management module carries out compliance inspection through document and business state in the credit engineering project to document delivery in the project process, tracks and rectifies the violation problem and changes to finally reach standard, management module includes document management unit, progress management unit and inspection monitoring unit, document management unit includes text classification subunit and keyword extraction subunit, text classification subunit adopts the BERT model to classify the text, the establishment process of BERT model includes following steps:
step S01: according to the data processing rule of the BERT model, performing feature conversion on the text, and converting the text into a feature vector;
step S02: the converted characteristic values are used as input for training and testing of the model, parameters are continuously adjusted in the training process, and finally the optimal model is obtained through convergence;
step S03: at the moment, the data is subjected to feature conversion and then is processed to obtain the category to which the data belongs;
the keyword extraction subunit extracts keywords in the text by using a New-TextRank algorithm, so that different documents can be better classified, and the New-TextRank algorithm takes words in the original text as nodes and judges through co-occurrence relationsIf the two nodes corresponding words appear in the same window, the two nodes can generate an edge, if the co-occurrence relation exists between the nodes, the edge is connected and set to be 1, if the weight is not set, the value is set to be 0, after continuous iteration, each node can obtain different weight values, the keywords in the document are generated from the nodes with higher weights, and the New-TextRank algorithm formula is as follows:
the v is i 、v j In (V) i ) V is i Is a set of points of the inbound node, out (v j ) For point v j The method comprises the steps that d is a damping coefficient, a progress management unit updates and manages the project progress in real time according to data information transmitted by an implementation module, the progress management unit adopts a percentile form to reflect the project progress, a user can directly check the project progress on a progress management page, a checking and monitoring unit checks document texts after the project is finished, the checking and monitoring unit corrects the texts in the document management unit by using a self-attention mechanism-based Transformer model, so that the document texts are more specialized, document content is more standardized, the specialty is improved, the checking and monitoring unit transmits the documents to an acceptance storage module after the checking is finished, the acceptance storage module backs up document data, meanwhile, the data information is transmitted to a cloud data center, after the cloud data center receives workflow information, all the workflow information is cached in a workflow queue, the workflow is scheduled to a virtual machine generated by the data center through a scheduler, and the workflow execution time is effectively shortened by using a greedy group system and a greedy algorithm.
Furthermore, the planning module performs task decomposition, resource allocation and progress planning on projects to be up to standard of the annual credit engineering.
Furthermore, the implementation module monitors the specific implementation condition of the credit engineering project and performs risk early warning, integrates monitoring and checking progress management, and reduces the complexity of credit engineering management.
Furthermore, the document management unit classifies and manages the documents by adopting a naive Bayesian method, establishes the relationship between the document characteristics and the document categories by adopting a decision tree model and a naive Bayesian model, judges the categories of the new documents by utilizing the model, and manages the new documents according to the categories.
Furthermore, the acceptance storage module is used for checking and accepting the compliance of the credit document and summarizing and storing reporting data required by project reporting.
Furthermore, the implementation module adopts a key chain method to manage the engineering progress.
The invention has the technical effects and advantages that:
1. the invention is beneficial to combining financial credit creation with cloud data and a virtualization system by arranging the management module and the cloud data center, improves the utilization rate of hardware resources, improves the reliability of a server and an application program, ensures service continuity, classifies and sorts the documents by the management module, corrects the text of the documents by the inspection and monitoring unit, reduces the difficulty of credit creation engineering construction management, and improves the professional degree of the documents and the informationized construction degree in the credit creation process.
Drawings
Fig. 1 is a diagram of a cloud data center virtualization system based on financial information creation according to the present invention.
Fig. 2 is a flow chart of a cloud data center virtualization system based on financial credit construction.
Fig. 3 is a flowchart of the BERT model building of the present invention.
Detailed Description
The embodiments of the present invention will be clearly and completely described below with reference to the drawings in the present invention, and the configurations of the structures described in the following embodiments are merely examples, and the cloud data center virtualization system based on financial information creation according to the present invention is not limited to the structures described in the following embodiments, and all other embodiments obtained by a person having ordinary skill in the art without making any creative effort are within the scope of the present invention.
As used herein, the terms "module," "system" and the like are intended to include a computer-related entity, either hardware, firmware, a combination of hardware and software, or software in execution. For example, a module may be, but is not limited to: a process running on a processor, an object, an executable, a thread of execution, a program, and/or a computer. By way of example, both an application running on a computing device and the computing device can be a module. One or more modules may be located in one process and/or thread of execution, and one module may be located on one computer and/or distributed between two or more computers.
The invention provides a cloud data center virtualization system based on financial information creation construction, which comprises a planning module, an implementation module, an acceptance storage module, a management module and a cloud data center, wherein the planning module transmits an engineering planning result to the implementation module, the implementation module receives data information of the planning module and then continuously gathers and transmits the data information to the management module, the management module carries out compliance check on document delivery in an information creation engineering project through managing the document and business state in the project process, tracks and rectifies illegal problems to finally reach standards, the management module comprises a document management unit, a progress management unit and a verification monitoring unit, the document management unit comprises a text classification subunit and a keyword extraction subunit, the text classification subunit classifies texts by adopting a BERT model, and the establishment process of the BERT model comprises the following steps:
step S01: according to the data processing rule of the BERT model, performing feature conversion on the text, and converting the text into a feature vector;
step S02: the converted characteristic values are used as input for training and testing of the model, parameters are continuously adjusted in the training process, and finally the optimal model is obtained through convergence;
step S03: at the moment, the data is subjected to feature conversion and then is processed to obtain the category to which the data belongs;
the keyword extraction subunit extracts keywords in a text by using a New-TextRank algorithm, so that different documents can be better classified, the New-TextRank algorithm takes words in the original text as nodes, edges between the nodes are judged through co-occurrence relations, if the words corresponding to the two nodes appear in the same window, the two nodes can generate an edge, if the co-occurrence relations exist between the nodes, the edges are connected and set to be 1, no weight is assigned to be 0, after continuous iteration, different weight values can be obtained for each node, the keywords in the document are generated from the nodes with higher weight, and the New-TextRank algorithm formula is as follows:
the v is i 、v j In (V) i ) V is i Is a set of points of the inbound node, out (v j ) For point v j The method comprises the steps that d is a damping coefficient, a progress management unit updates and manages the project progress in real time according to data information transmitted by an implementation module, the progress management unit adopts a percentile form to reflect the project progress, a user can directly check the project progress on a progress management page, a checking and monitoring unit checks document texts after the project is finished, the checking and monitoring unit corrects the texts in the document management unit by using a self-attention mechanism-based Transformer model, so that the document texts are more specialized, document content is more standardized, the specialty is improved, the checking and monitoring unit transmits the documents to an acceptance storage module after the checking is finished, the acceptance storage module backs up document data, meanwhile, the data information is transmitted to a cloud data center, after the cloud data center receives workflow information, all the workflow information is cached in a workflow queue, the workflow is scheduled to a virtual machine generated by the data center through a scheduler, and the workflow execution time is effectively shortened by using a greedy group system and a greedy algorithm.
In a preferred embodiment, the planning module performs task decomposition, resource allocation and progress planning on projects to reach standards of the annual credit engineering.
In a preferred embodiment, the implementation module monitors the specific implementation condition of the credit engineering project and performs risk early warning, integrates monitoring and checking progress management, and reduces the complexity of credit engineering management.
In a preferred embodiment, the document management unit classifies and manages the documents by adopting a naive bayes method, establishes a relationship between the document characteristics and the document categories by adopting a decision tree model and a naive bayes model, judges the categories of the new documents by using the model, and manages the new documents according to the categories.
In a preferred embodiment, the acceptance storage module performs inspection and acceptance on the compliance of the credit document, and performs summary storage on reporting materials required by project reporting.
In a preferred embodiment, the implementation module manages engineering progress using a keychain approach.
In this embodiment, it should be specifically explained that the difference between this implementation and the prior art is mainly that this embodiment is provided with a management module and a cloud data center, and can combine financial creation with cloud data and a virtualization system, so as to improve the utilization rate of hardware resources, improve the reliability of servers and application programs, ensure service continuity, and sort and arrange documents by the management module, and correct the text of the documents by checking and monitoring units, thereby reducing the difficulty of creation engineering construction management, and improving the professional degree of the documents and the informationized construction degree in the creation process.
Finally: the foregoing description of the preferred embodiments of the invention is not intended to limit the invention to the precise form disclosed, and any such modifications, equivalents, and alternatives falling within the spirit and principles of the invention are intended to be included within the scope of the invention.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.
In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a read-only memory, a random access memory, a magnetic disk or an optical disk.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. The utility model provides a cloud data center virtualization system based on financial information creation, includes planning module, implementation module, acceptance storage module, its characterized in that: the system comprises a project management module, a project management module and a cloud data center, wherein the project management module is used for transmitting project planning results to the project implementation module, the project implementation module is used for receiving data information of the project module and then continuously summarizing and transmitting the data information to the project management module, the project management module is used for managing documents and business states in a credit engineering project, conducting compliance checking on document delivery in the project process, tracking and rectifying illegal problems to finally reach standards, the project management module comprises a document management unit, a progress management unit and a verification monitoring unit, the document management unit comprises a text classification subunit and a keyword extraction subunit, the text classification subunit is used for classifying texts by adopting a BERT model, and the establishment process of the BERT model comprises the following steps:
step S01: according to the data processing rule of the BERT model, performing feature conversion on the text, and converting the text into a feature vector;
step S02: the converted characteristic values are used as input for training and testing of the model, parameters are continuously adjusted in the training process, and finally the optimal model is obtained through convergence;
step S03: at the moment, the data is subjected to feature conversion and then is processed to obtain the category to which the data belongs; the keyword extraction subunit extracts keywords in a text by using a New-TextRank algorithm, so that different documents can be better classified, the New-TextRank algorithm takes words in the original text as nodes, edges between the nodes are judged through co-occurrence relations, if the words corresponding to the two nodes appear in the same window, the two nodes can generate an edge, if the co-occurrence relations exist between the nodes, the edges are connected and set to be 1, no weight is assigned to be 0, after continuous iteration, different weight values can be obtained for each node, the keywords in the document are generated from the nodes with higher weight, and the New-TextRank algorithm formula is as follows:
the v is i 、v j In (V) i ) V is i Is a set of points of the inbound node, out (v j ) For point v j The method comprises the steps that d is a damping coefficient, a progress management unit carries out real-time update management on project progress according to data information transmitted by an implementation module, the progress management unit adopts a percentage form to reflect the project progress, a user can directly check the project progress on a progress management page, a checking and monitoring unit checks document texts after the project is finished, the checking and monitoring unit corrects the texts in the document management unit by using a self-attention mechanism-based Transformer model, so that the document texts are more specialized, the document content is more standardized, the expertise is improved, the checking and monitoring unit transmits the documents to an acceptance storage module after the checking is finished, the acceptance storage module backs up document data and simultaneously transmits the data information to a cloud data center, and after the cloud data center receives workflow information, all the workflow information is transmittedThe workflow is cached in a workflow queue, the workflow is scheduled to a virtual machine generated by a data center for processing through a scheduler, and the execution time of the workflow is effectively shortened by utilizing an ant colony system and a greedy algorithm.
2. The cloud data center virtualization system based on financial credit construction of claim 1, wherein: and the planning module performs task decomposition, resource allocation and progress planning on projects to be up to standard of the annual credit engineering.
3. The cloud data center virtualization system based on financial credit construction of claim 1, wherein: the implementation module monitors the specific implementation condition of the credit engineering project and performs risk early warning, integrates monitoring and checking progress management, and reduces the complexity of credit engineering management.
4. The cloud data center virtualization system based on financial credit construction of claim 1, wherein: the document management unit classifies and manages the documents by adopting a naive Bayesian method, establishes the relationship between the document characteristics and the document categories by adopting a decision tree model and a naive Bayesian model, judges the categories of the new documents by utilizing the model, and manages the new documents according to the categories.
5. The cloud data center virtualization system based on financial credit construction of claim 1, wherein: and the acceptance storage module is used for inspecting and accepting the compliance of the credit document and summarizing and storing reporting data required by project reporting.
6. The cloud data center virtualization system based on financial credit construction of claim 1, wherein: the implementation module adopts a key chain method to manage the engineering progress.
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