Ai data set retrieval method and system based on custom DNS record

Abstract

The present invention relates to an AI data set retrieval method and system based on a custom DNS record. The method comprises: setting a custom DNS record type, i.e., an AI-DATA record, which is used for storing location information of a data set that is required by an AI model, and setting DNS server software to support the AI-DATA record; and on the basis of the topic of a user question, the AI model automatically retrieving a relevant data set by means of the AI-DATA record, wherein the AI-DATA record comprises fields such as the name of the data set, the type of the data set, and the storage location of the data set. The present invention increases the efficiency and accuracy of data set retrieval by using an AI-DATA record, thereby enabling an AI model to provide a user with required information more effectively.

Description

An AI dataset retrieval method and system based on custom DNS records Technical Field

[0001] The present invention belongs to the field of information technology, and relates to artificial intelligence (AI) models, dataset storage and retrieval technology, and domain name system (DNS), and more specifically to an AI dataset retrieval method and system based on custom DNS records. Background Art

[0002] Existing AI models require access to various datasets to answer questions related to specific topics. However, in existing systems, the dataset storage and retrieval process can be cumbersome and inefficient. Furthermore, existing DNS technology primarily targets common network services and does not address the specific needs of AI datasets.

[0003] Therefore, an improved method is needed to enable AI models to quickly and accurately obtain relevant data sets in different scenarios.

[0004] Summary of the Invention

[0005] In response to the above problems, the present invention provides an AI dataset retrieval method and system based on custom DNS records to improve the efficiency of AI application switching and searching for different types of AI models.

[0006] The technical solution adopted in the present invention is as follows:

[0007] In a first aspect, the present invention provides an AI dataset retrieval method based on a custom DNS record, comprising the following steps:

[0008] Set up a custom DNS record type, the AI-DATA record, to store the location information of the datasets required by the AI ​​model, and configure the DNS server software to support AI-DATA records.

[0009] The AI ​​model automatically retrieves relevant datasets through AI-DATA records based on the topic of the user's question.

[0010] Furthermore, the AI-DATA record includes a dataset name, a dataset type, and a storage location of the dataset.

[0011] Furthermore, the setting of the DNS server software includes modifying the existing DNS server software or creating a customized DNS server software.

[0012] Furthermore, the AI ​​model is modified to support obtaining the location of the dataset by querying the AI-DATA record.

[0013] Furthermore, the data set is stored in a distributed file system, cloud storage, or dedicated server storage; the data set is organized according to the data set type and access requirements, and a data update and synchronization strategy is implemented to ensure that the AI ​​model always uses the latest data.

[0014] Furthermore, AI-DATA records and datasets are protected from unauthorized access by implementing security measures, including access control, data encryption, and anti-tampering mechanisms, and ensuring compliance with data protection regulations to protect user privacy and data security.

[0015] Furthermore, the AI ​​model automatically retrieves relevant datasets based on the subject of the user's question through AI-DATA records, including:

[0016] The AI ​​model identifies relevant topics based on the user’s question;

[0017] The AI ​​model generates a DNS query for the corresponding AI-DATA record based on the identified topic;

[0018] The AI ​​model sends a DNS query to the DNS server;

[0019] The DNS server returns an AI-DATA record containing the dataset location to the AI ​​model, which parses it and extracts the dataset location information.

[0020] The AI ​​model loads the dataset from the storage system based on the extracted location information;

[0021] The AI ​​model uses the loaded dataset to process the user's questions and generate answers.

[0022] In a second aspect, the present invention provides an AI dataset retrieval system based on custom DNS records, characterized by comprising:

[0023] The AI-DATA record configuration module is used to set up a custom DNS record type, namely the AI-DATA record, which is used to store the location information of the dataset required by the AI ​​model and to set up the DNS server software to support AI-DATA records;

[0024] The dataset retrieval module is used to automatically retrieve relevant datasets through AI-DATA records using AI models based on the topic of the user's question.

[0025] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, the computer program is configured to be executed by the processor, and the computer program comprises instructions for executing each step in the method of the present invention.

[0026] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a computer, the various steps of the method of the present invention are implemented.

[0027] The beneficial effects of the present invention are as follows:

[0028] This invention offers significant advantages and innovations over existing technologies. By utilizing AI-DATA records, it improves the efficiency and accuracy of dataset retrieval, enabling AI models to better provide users with the information they need. Furthermore, this invention enables dynamic dataset loading and AI model integration, enhancing system flexibility and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] FIG1 is a flowchart of the steps of an AI dataset retrieval method based on custom DNS records in an embodiment of the present invention;

[0030] FIG2 is a flowchart of the steps of an AI model retrieving relevant data sets based on the subject of a user question in an embodiment of the present invention;

[0031] FIG3 is a module composition diagram of an AI dataset retrieval system based on custom DNS records in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to specific embodiments and accompanying drawings.

[0033] The present invention provides an AI dataset retrieval method based on custom DNS records, which mainly includes the following contents:

[0034] 1) AI-DATA record: A custom DNS record type used to store the location information of datasets required by AI models. AI-DATA records include fields such as the dataset name, dataset type (such as weather, health, entertainment, etc.), and the dataset's storage location (URL or IP address).

[0035] 2) DNS Server: Modify existing DNS server software (such as BIND or Microsoft DNS) or create custom DNS server software to support the new AI-DATA record type.

[0036] 3) Dataset Storage: Provide storage solutions for different types of datasets, such as distributed file systems, cloud storage, or dedicated servers. Organize datasets for easy access and ensure data is updated and synchronized.

[0037] 4) AI Models: Modify existing AI models to support querying AI-DATA records to retrieve dataset locations. Methods and techniques for implementing these modifications enable AI models to automatically retrieve relevant datasets based on the topic of user questions.

[0038] 5) Security and privacy protection: Implement security measures to prevent unauthorized access and tampering of AI-DATA records and datasets. Protect user privacy and prevent data leakage or misuse.

[0039] 6) Scalability and compatibility: Design the system to support large datasets and different types of AI models. Achieve compatibility with existing network infrastructure and technologies to allow for seamless integration in the future.

[0040] In one embodiment of the present invention, a method for retrieving an AI dataset based on a custom DNS record is provided. As shown in FIG1 , the method includes the following steps:

[0041] S101: Set a custom DNS record type, namely an AI-DATA record, to store the location information of the dataset required by the AI ​​model, and set the DNS server software to support the AI-DATA record;

[0042] S102: The AI ​​model automatically retrieves relevant datasets through AI-DATA records based on the topic of the user's question.

[0043] Among them, the AI-DATA record includes fields such as dataset name, dataset type, and dataset storage location.

[0044] The DNS server software may be a modified version of existing DNS server software (such as BIND or Microsoft DNS), or a customized DNS server software.

[0045] The data set can be stored in a distributed file system, cloud storage, or a dedicated server.

[0046] In one embodiment of the present invention, the above method further includes security measures such as access control, data encryption, and anti-tampering mechanisms to protect AI-DATA records and data sets from unauthorized access and ensure compliance with applicable data protection regulations to protect user privacy and data security.

[0047] In one embodiment of the present invention, a method for retrieving an AI dataset based on a custom DNS record is provided, the steps of which include:

[0048] a. Create and configure AI-DATA records;

[0049] b. Modify the DNS server to support AI-DATA record type;

[0050] c.Store and organize different types of data sets;

[0051] d. Modify the AI ​​model to support the ability to obtain the location of the dataset by querying the AI-DATA record;

[0052] e. Implement security measures such as access control, data encryption, and anti-tampering mechanisms to protect AI-DATA records and datasets from unauthorized access;

[0053] f. Based on the topic of the user’s question, use AI models to automatically retrieve and load relevant datasets.

[0054] Creating and configuring AI-DATA records includes determining the fields that need to be included in the record, such as the dataset name, dataset type, and the storage location of the dataset. Modifying the DNS server can be to modify existing DNS server software (such as BIND or Microsoft DNS) or to create custom DNS server software. Distributed file systems, cloud storage, or dedicated servers can be used to store and organize different types of datasets. Modifying the AI ​​model includes implementing support for obtaining the location of the dataset by querying the AI-DATA record, so that the AI ​​model can automatically retrieve and load relevant datasets based on the topic of the user's question.

[0055] The above method may further include implementing data update and synchronization strategies to ensure that the AI ​​model always uses the latest data and ensures compliance with applicable data protection regulations to protect user privacy and data security.

[0056] In one embodiment of the present invention, a method for retrieving an AI dataset based on a custom DNS record is provided, the method comprising the following steps:

[0057] 1. Define the structure for the AI-DATA record: Determine the fields that need to be included in the record, such as the dataset name, dataset type (such as weather, health, entertainment, etc.), and the storage location of the dataset (URL or IP address).

[0058] 2. Update DNS server software: Modify existing DNS server software (such as BIND or Microsoft DNS) or create a custom DNS server software to support the new AI-DATA record type. Currently, DNS services support record types such as A, AAAA, NS, CNAME, SOA, and MX. You can add the new AI-DATA record type based on these record types.

[0059] 3. Create and configure AI-DATA records: Create an AI-DATA record for each dataset and configure these records in the DNS server. The record should contain relevant information about the dataset, such as name, type, and storage location.

[0060] 4. Dataset storage and organization: Select appropriate data storage solutions (e.g., distributed file systems, cloud storage, or dedicated servers) and organize datasets based on dataset type and access requirements. Implement data update and synchronization strategies to ensure that AI models always use the latest data.

[0061] The specific method of organizing datasets according to dataset types and access requirements can be:

[0062] 1) Classification by data type: Different storage and processing methods are used for different data types (such as text, audio, video, etc.). For example, text data can be directly stored as text files or database records, while audio and video data may require specific file formats and codecs.

[0063] 2) Classify by topic or usage: If you have multiple datasets with different topics or usage (such as a weather forecast dataset and an entertainment-related video dataset), you can classify and store the datasets according to these topics or usage, which makes it easier to find and access them.

[0064] Among them, data update and synchronization strategies can be based on the size and type of data sets, and can perform full updates regularly, or only update the changed parts (incremental updates), or maintain real-time updates.

[0065] 5. Modify and integrate AI models: Based on the query results from AI-DATA records, modify existing AI models to support dynamic retrieval of relevant datasets. Implementing these modified methods and techniques enables the AI ​​model to automatically retrieve and load relevant datasets based on the topic of the user's question. Based on user needs, the AI ​​model provides different services. For example, if a user wants to know the current weather forecast, the AI-DATA records are used to retrieve the weather forecast information and then provide a voice broadcast. If the user wants to watch a video, the AI-DATA records are used to retrieve the corresponding information, decode the video, and play it.

[0066] The AI ​​model obtains the location of the dataset by querying the AI-DATA record. The specific steps for automatically retrieving and loading relevant datasets based on the topic of the user's question are shown in Figure 2, including:

[0067] Step S201, Topic Identification: First, the AI ​​model identifies relevant topics based on the user's question. This can be achieved through natural language processing (NLP) technologies, such as keyword extraction, topic modeling, and semantic understanding.

[0068] Step S202: Generate DNS query: Based on the identified topic, the AI ​​model generates a DNS query for the corresponding AI-DATA record. The query format should comply with the DNS protocol and include specific fields defined for the AI-DATA record.

[0069] Step S203, sending a DNS query: The AI ​​model sends a query to the DNS server via the network, for example, using socket programming or a DNS query library.

[0070] Step S204: Parse the DNS response: The DNS server returns an AI-DATA record containing the dataset location. The AI ​​model parses this response and extracts the dataset location information.

[0071] Step S205, loading the data set: Finally, the AI ​​model loads the data set from a storage system (such as a distributed file system, cloud storage, or a dedicated server) based on the obtained location information.

[0072] Step S206, processing the user's question: The AI ​​model uses the loaded data set to process the user's question and generate an answer.

[0073] 6. Security and Privacy Protection: Implement security measures such as access control, data encryption, and anti-tampering mechanisms to protect AI-DATA records and datasets from unauthorized access. Ensure compliance with applicable data protection regulations to protect user privacy and data security.

[0074] 7. Scalability and compatibility: Design the system to support multiple datasets and different types of AI models. Ensure compatibility with existing network infrastructure and technologies to allow for easy expansion and integration of new features in the future.

[0075] 8. Application Scenarios and Use Cases: The effectiveness of the present invention has been demonstrated in real-world application scenarios. For example, in a customer support environment, using the present invention's approach, an AI model can automatically load weather, health, and entertainment-related datasets based on customer questions, providing fast and accurate responses.

[0076] In one embodiment of the present invention, an AI dataset retrieval system based on custom DNS records is provided, as shown in FIG3 , which includes:

[0077] The AI-DATA record configuration module is used to set up a custom DNS record type, namely the AI-DATA record, which is used to store the location information of the dataset required by the AI ​​model and to set up the DNS server software to support AI-DATA records;

[0078] The dataset retrieval module is used to automatically retrieve relevant datasets through AI-DATA records using AI models based on the topic of the user's question.

[0079] The specific implementation process of each module refers to the above description of the method of the present invention.

[0080] Another embodiment of the present invention provides a computer device (computer, server, smart phone, etc.), which includes a memory and a processor, wherein the memory stores a computer program, the computer program is configured to be executed by the processor, and the computer program includes instructions for executing each step in the method of the present invention.

[0081] Another embodiment of the present invention provides a computer-readable storage medium (such as ROM / RAM, magnetic disk, optical disk), wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a computer, the steps of the method of the present invention are implemented.

Claims

1. An AI dataset retrieval method based on custom DNS records, characterized in that: The following steps are involved: Set up a custom DNS record type, AI-DATA record, to store the location information of the dataset required by the AI ​​model, and set up the DNS server software to support AI-DATA records; The AI ​​model automatically retrieves relevant datasets through AI-DATA records based on the topic of the user's question.

2. The method according to claim 1, characterized in that The AI-DATA record includes a data set name, a data set type, and a storage location of the data set.

3. The method according to claim 1, characterized in that The setting of the DNS server software includes modifying the existing DNS server software or creating a customized DNS server software.

4. The method according to claim 1, characterized in that: The AI ​​model is modified to support obtaining the location of the dataset by querying the AI-DATA record.

5. The method according to claim 1, characterized in that: The data sets are stored in distributed file systems, cloud storage, or dedicated server storage. The data sets are organized according to data set types and access requirements, and data update and synchronization strategies are implemented to ensure that the AI ​​model always uses the latest data.

6. The method according to claim 1, characterized in that Protect AI-DATA records and data sets from unauthorized access and ensure compliance with data protection regulations to protect user privacy and data security by implementing security measures, including access control, data encryption, and anti-tampering mechanisms.

7. The method according to claim 1, characterized in that The AI ​​model automatically retrieves relevant datasets through AI-DATA records based on the topic of the user's question, including: The AI ​​model identifies relevant topics based on the user’s question; The AI ​​model generates a DNS query for the corresponding AI-DATA record based on the identified topic; The AI ​​model sends a DNS query to the DNS server; The DNS server returns an AI-DATA record containing the location of the dataset to the AI ​​model, which parses it and extracts the location information of the dataset. The AI ​​model loads the dataset from the storage system based on the extracted location information; The AI ​​model uses the loaded dataset to process the user's questions and generate answers.

8. An AI dataset retrieval system based on custom DNS records, characterized in that: include: AI-DATA record configuration module, which is used to set up a custom DNS record type, namely AI-DATA record, which is used to store the location information of the data set required by the AI ​​model, and to set up the DNS server software to support AI-DATA record; The dataset retrieval module is used to automatically retrieve relevant datasets through AI-DATA records using AI models based on the topic of the user's question.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, the computer program is configured to be executed by the processor, and the computer program comprises instructions for executing the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a computer, the method according to any one of claims 1 to 7 is implemented.

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