Artificial intelligence management system based on big data

Abstract

The invention discloses an artificial intelligence management system based on big data, which comprises a multi-dimensional data classification storage module, a high-security privacy and sharing module, an intelligent data acquisition module and an unstructured data processing module, and is characterized in that the high-security privacy and sharing module is connected with the multi-dimensional data classification storage module; the intelligent data acquisition module is respectively connected with the multi-dimensional data classified storage module and the high-security privacy and sharing module, and the unstructured data processing module is respectively connected with the multi-dimensional data classified storage module, the high-security privacy and sharing module and the intelligent data acquisition module. Through multi-dimensional data classified storage, high-safety privacy and sharing management, intelligent data acquisition and strong unstructured data processing capability, the convenience, safety and efficiency of the data management system are remarkably improved, and the problems of insufficient intelligent degree and complex operation in the prior art are effectively solved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence and big data technology, and specifically to an artificial intelligence management system based on big data. Background Art

[0002] With the rapid development of information technology, big data and artificial intelligence technologies are increasingly being used across all industries. Traditional enterprise business management systems often suffer from insufficient intelligence and reliance on manual operations, which seriously impacts the efficiency of enterprise work. While existing big data-based artificial intelligence management systems have improved the convenience and efficiency of data management to a certain extent, the following issues still exist:

[0003] 1. Data classification and storage are not detailed enough to meet multi-dimensional data management needs.

[0004] 2. The security of private and shared modules needs to be improved, especially in the identity authentication process.

[0005] 3. The data acquisition module does not make full use of cloud resource data and lacks an intelligent data screening mechanism.

[0006] 4. The system’s processing capabilities for unstructured data (such as images, voice, etc.) are limited, affecting the user experience.

[0007] Based on this, the present invention proposes an artificial intelligence management system based on big data, aiming to further improve the intelligence level, convenience and efficiency of the system. Summary of the Invention

[0008] In response to the shortcomings of the existing technology, the purpose of the present invention is to provide an artificial intelligence management system based on big data. Through multi-dimensional data classification storage, high-security privacy and sharing management, intelligent data acquisition and powerful unstructured data processing capabilities, the convenience, security and efficiency of the data management system are significantly improved, and the problems of insufficient intelligence and complex operation in the existing technology are effectively solved.

[0009] In order to achieve the above-mentioned purpose, the present invention is implemented through the following technical solution: an artificial intelligence management system based on big data, including a multi-dimensional data classification and storage module, a high-security privacy and sharing module, an intelligent data acquisition module and an unstructured data processing module, the high-security privacy and sharing module is connected to the multi-dimensional data classification and storage module, the intelligent data acquisition module is respectively connected to the multi-dimensional data classification and storage module and the high-security privacy and sharing module, and the unstructured data processing module is respectively connected to the multi-dimensional data classification and storage module, the high-security privacy and sharing module and the intelligent data acquisition module.

[0010] Preferably, the multi-dimensional data classification storage module implements refined classification and storage of different types of data by introducing a multi-dimensional data tag system. Each data item can be assigned multiple tags, making it easier for users to search from different angles.

[0011] Preferably, the high-security privacy and sharing module includes a multi-level identity authentication privacy platform and a dynamic rights management mechanism sharing platform. The multi-level identity authentication privacy platform includes, but is not limited to, biometric recognition technologies such as facial recognition, fingerprint recognition, and iris recognition. The dynamic rights management mechanism sharing platform adjusts data access rights in real time based on user roles.

[0012] Preferably, the intelligent data acquisition module: when the data required by the user does not exist in the system, the intelligent data acquisition module will automatically filter out the most relevant results from the massive data in the cloud; introduce machine learning algorithms, analyze historical data, predict the user's possible needs, and obtain relevant data in advance.

[0013] Preferably, the unstructured data processing module uses advanced enhanced algorithm image recognition technology to identify picture data, and uses multi-language recognition for voice data, and extracts key information through natural language processing technology.

[0014] The workflow of an artificial intelligence management system based on big data is as follows:

[0015] 1. Data storage and classification: Users log in to the system through their personal accounts, and the system automatically classifies and stores the uploaded data in multiple dimensions and adds corresponding labels.

[0016] 2. Private and shared management: Users can classify data as private or shared based on their needs. Private data is accessible only to the user, while shared data is granted different access permissions based on user roles.

[0017] 3. Data acquisition and analysis: The user enters a query command, and the system extracts keywords through the information acquisition module and performs semantic analysis based on the context. The analysis module searches the shared platform based on the extracted keywords. If no relevant data is found, the system obtains it from the cloud through the intelligent data acquisition module.

[0018] 4. Result feedback and storage: After the query results are returned to the user, the system automatically classifies and stores the newly acquired data according to the set rules and updates the corresponding labels; users can choose to set the new data to private or shared status.

[0019] Preferably, in step 1, the system needs to verify the user's identity to ensure that only authorized users can access it.

[0020] Preferably, the data in step 1 includes text, pictures, voice, etc.

[0021] Preferably, step 3 directly extracts keywords from text data. For image data, if the image clarity is low, the system uses an enhancement algorithm to improve the clarity before recognition, extracting key information (such as text, object features, etc.) from the image. For voice data, the system determines whether the voice is Mandarin. If it is Mandarin, it is directly converted to text data to extract keywords from the voice. If it is not Mandarin, recognition is not performed.

[0022] The present invention has the following beneficial effects:

[0023] 1. Improve data management efficiency: Significantly improve data management efficiency through multi-dimensional data classification storage and intelligent data acquisition.

[0024] 2. Enhance system security: Adopt multi-level authentication and dynamic permission management to ensure data security.

[0025] 3. Improve user experience: Support multi-language voice recognition and low-resolution image recognition to meet diverse user needs.

[0026] 4. Promote resource sharing: Promote resource sharing and collaboration between departments or enterprises through flexible sharing mechanisms.

[0027] In summary, the present invention effectively solves the problems existing in the existing technology by introducing multi-dimensional data classification, high-security privacy and sharing management, intelligent data acquisition and powerful unstructured data processing capabilities, and has high practical value and promotion significance. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments;

[0029] Figure 1 It is a structural block diagram of the present invention. DETAILED DESCRIPTION

[0030] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below in conjunction with specific implementation methods.

[0031] Reference Figure 1, this specific embodiment adopts the following technical solution: an artificial intelligence management system based on big data, including a multi-dimensional data classification and storage module 1, a high-security privacy and sharing module 2, an intelligent data acquisition module 3 and an unstructured data processing module 4, the high-security privacy and sharing module 2 is connected to the multi-dimensional data classification and storage module 1, the intelligent data acquisition module 3 is respectively connected to the multi-dimensional data classification and storage module 1 and the high-security privacy and sharing module 2, and the unstructured data processing module 4 is respectively connected to the multi-dimensional data classification and storage module 1, the high-security privacy and sharing module 2, and the intelligent data acquisition module 3.

[0032] It is worth noting that the multi-dimensional data classification storage module 1 implements refined classification and storage of different types of data by introducing a multi-dimensional data tag system. Each data item can be assigned multiple tags, making it easier for users to search from different angles.

[0033] It is worth noting that the high-security privacy and sharing module 2 includes a multi-level identity authentication privacy platform and a dynamic rights management mechanism sharing platform. The multi-level identity authentication privacy platform includes but is not limited to biometric recognition technologies such as face recognition, fingerprint recognition, and iris recognition. The dynamic rights management mechanism sharing platform adjusts data access rights in real time based on user roles.

[0034] It is worth noting that the intelligent data acquisition module 3: when the data required by the user does not exist in the system, the intelligent data acquisition module will automatically filter out the most relevant results from the massive data in the cloud; introduce machine learning algorithms, analyze historical data, predict the user's possible needs, and obtain relevant data in advance.

[0035] Furthermore, the unstructured data processing module 4 uses advanced enhanced algorithm image recognition technology for image data recognition, which can improve the recognition success rate even if the image clarity is low. For voice data, multi-language recognition is performed and key information is extracted through natural language processing technology.

[0036] The workflow of an artificial intelligence management system based on big data is as follows:

[0037] Step 1: Data storage and classification

[0038] 1.1 User login:

[0039] Users log in to the system through their personal accounts.

[0040] The system authenticates user identities to ensure that only authorized users can access the system.

[0041] 1.2 Data upload:

[0042] Users upload different types of data (such as text, pictures, voice, etc.).

[0043] The system automatically identifies the data type and assigns it to the corresponding processing module.

[0044] 1.3 Multi-dimensional classification storage:

[0045] The system classifies data in multiple dimensions according to preset rules.

[0046] For example:

[0047] According to the source of data (internally generated or externally imported).

[0048] According to data type (text, picture, voice, etc.).

[0049] According to the purpose of data (business reports, customer information, etc.).

[0050] Each data item is assigned multiple tags to facilitate subsequent retrieval. Tags may include: data date, department classification, and keyword extraction results.

[0051] 1.4 Label processing:

[0052] The system automatically generates labels for each data item. For example:

[0053] For text data, keywords are extracted and used as labels.

[0054] For image data, key information is extracted as labels through image recognition technology.

[0055] For voice data, key information is extracted as labels through speech-to-text technology.

[0056] 1.5 Storage Operations:

[0057] The data is stored in the multi-dimensional data classification storage module according to the classification results.

[0058] The system records the storage location of the data and related metadata (such as storage time, storage path, etc.).

[0059] Step 2: Privacy and Sharing Management

[0060] 2.1 Private status settings:

[0061] The user chooses to keep the data private.

[0062] Private data can only be accessed by the person himself.

[0063] The system activates a multi-level identity authentication mechanism (such as face recognition, fingerprint recognition, iris recognition, etc.) to ensure data security.

[0064] 2.2 Sharing status settings:

[0065] The user chooses to make the data shared.

[0066] The sharing platform introduces a dynamic permission management mechanism: data access permissions are adjusted in real time based on user roles. For example, ordinary employees can only view certain data, while administrators can edit or delete data.

[0067] 2.3 Permission Adjustment:

[0068] Users can adjust the privacy or sharing status of data at any time as needed.

[0069] Adjustment operations must be authenticated to ensure security.

[0070] 2.4 Logging:

[0071] The system records each change in data status (such as from private to shared).

[0072] Record access history for auditing and tracking purposes.

[0073] Step 3: Data acquisition and analysis

[0074] 3.1 User input query command:

[0075] The user enters a query command (such as a keyword, image, or voice) through the interface. The system receives the command and passes it to the information acquisition module.

[0076] 3.2 Information acquisition module processing:

[0077] For text data, keywords are extracted directly.

[0078] For image data: If the image clarity is low, the system uses an enhancement algorithm to improve the clarity before recognition. This extracts key information from the image (such as text, object features, etc.).

[0079] For voice data: determine whether the voice is Mandarin. If it is Mandarin, directly convert it into text data; if it is not Mandarin, it cannot be recognized.

[0080] Extract keywords from speech.

[0081] 3.3 Semantic Analysis:

[0082] The analysis module performs semantic analysis on the extracted keywords in combination with the context to generate a description of the user's actual needs.

[0083] 3.4 Sharing Platform Search: The system searches the sharing platform based on the requirement description. If relevant data is found, the results are returned directly.

[0084] 3.5 Cloud Data Acquisition:

[0085] If no relevant data is found on the shared platform, the intelligent data acquisition module kicks in, filtering the most relevant data from the massive cloud data. Machine learning algorithms are used to predict potential user needs and acquire relevant data in advance.

[0086] 3.6 Result feedback: Feedback the relevant search data to the user.

[0087] Step 4: Result feedback and storage

[0088] 4.1 New Data Storage:

[0089] After the query results are returned, the system automatically stores the newly acquired data in the multi-dimensional data classification storage module.

[0090] New data is classified and stored according to the set rules, and the corresponding labels are updated.

[0091] 4.2 Status settings:

[0092] Users can choose to make new data private or shared.

[0093] If set to private, a multi-level authentication mechanism is enabled.

[0094] If it is set to shared state, the dynamic permission management mechanism is started.

[0095] 4.3 Logging:

[0096] The system records the storage location, storage time and status settings of new data.

[0097] Record the user's operation history to facilitate subsequent auditing.

[0098] 4.4 Notification function:

[0099] If the new data involves a specific department or user, the system can notify the relevant personnel via email, text message, etc.

[0100] This specific implementation utilizes big data and artificial intelligence technologies. A multi-dimensional data classification and storage module enables refined management of different data types, with multiple tags attached to each data item for rapid retrieval. A highly secure privacy and sharing module combines multi-level authentication and dynamic permissions management to ensure data security and flexibility. An intelligent data acquisition module utilizes machine learning algorithms to predict user needs and retrieve relevant data from the cloud, enhancing the system's intelligence.

[0101] Furthermore, the unstructured data processing module utilizes advanced image enhancement algorithms and natural language processing technologies to effectively identify low-resolution images and multilingual audio data, extracting key information to support efficient data analysis and querying. Through the collaborative work of these four core modules, the overall system achieves efficient data storage, secure sharing, intelligent access, and convenient management, significantly improving user experience and data management efficiency.

[0102] Example 1: User A needs to find a document and enters the keyword "annual report" into the system. The system first searches the shared platform. If no relevant data is found, it automatically retrieves eligible annual reports from the cloud and stores them in the shared platform for other users to reference.

[0103] Example 2: User B uploads a blurry picture. The system successfully identifies the content after improving the picture clarity through an image enhancement algorithm, and stores it in a classified manner on a private platform to ensure data security.

[0104] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence management system based on big data, characterized in that: The system comprises a multi-dimensional data classification storage module (1), a high-security privacy and sharing module (2), an intelligent data acquisition module (3) and an unstructured data processing module (4), wherein the high-security privacy and sharing module (2) is connected to the multi-dimensional data classification storage module (1), the intelligent data acquisition module (3) is respectively connected to the multi-dimensional data classification storage module (1) and the high-security privacy and sharing module (2), and the unstructured data processing module (4) is respectively connected to the multi-dimensional data classification storage module (1), the high-security privacy and sharing module (2) and the intelligent data acquisition module (3).

2. The big data-based artificial intelligence management system according to claim 1, characterized in that: The multi-dimensional data classification storage module (1) realizes refined classification storage of different types of data by introducing a multi-dimensional data tag system; each data item can be attached with multiple tags, which facilitates user retrieval from different angles.

3. The big data-based artificial intelligence management system according to claim 1, characterized in that: The dynamic rights management mechanism sharing platform adjusts data access rights in real time according to user roles.

4. The big data-based artificial intelligence management system according to claim 1, characterized in that: The intelligent data acquisition module (3) described above: when the data required by the user does not exist in the system, the intelligent data acquisition module will automatically filter out the most relevant results from the massive data in the cloud; introduce machine learning algorithms, analyze historical data, predict the user's possible needs, and obtain relevant data in advance.

5. The big data-based artificial intelligence management system according to claim 1, characterized in that: The unstructured data processing module (4) uses advanced enhanced algorithm image recognition technology to identify picture data; for voice data, it uses multi-language recognition and natural language processing technology to extract key information.

6. The big data-based artificial intelligence management system according to claim 1, characterized in that: The workflow is as follows: (1) Data storage and classification: Users log in to the system through their personal accounts, and the system automatically classifies and stores the uploaded data in multiple dimensions and adds corresponding tags; (2) Private and shared management: Users can classify data as private or shared according to their needs; private data is only accessible to the user, while shared data is granted different access rights based on the user role; (3) Data acquisition and analysis: The user enters a query command, and the system extracts keywords through the information acquisition module and performs semantic analysis based on the context. The analysis module searches the shared platform based on the extracted keywords. If no relevant data is found, the intelligent data acquisition module obtains data from the cloud. (4) Result feedback and storage: After the query results are returned to the user, the system automatically classifies and stores the newly acquired data according to the set rules and updates the corresponding labels; the user can choose to set the new data to private or shared status.

7. The big data-based artificial intelligence management system according to claim 6, characterized in that: In step (1), the system needs to verify the user's identity to ensure that only authorized users can access.

8. The big data-based artificial intelligence management system according to claim 6, characterized in that: The data in step (1) includes text, pictures, and voice data.

9. The big data-based artificial intelligence management system according to claim 6, characterized in that: The step (3) directly extracts keywords for text data; for image data: if the image clarity is low, the system uses an enhancement algorithm to improve the clarity before recognition; extracts key information from the image; for voice data: determines whether the voice is Mandarin; if it is Mandarin, directly converts it into text data to extract keywords from the voice; if it is not Mandarin, it cannot be recognized.

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