Intelligent response method, system and equipment for gas industry and storage medium

Abstract

The invention discloses a gas industry intelligent response method, system and device and a storage medium, and the method comprises the steps: obtaining user input information, carrying out the intention recognition of the user input information, and determining the user intention; when the user intention is to ask a gas related question, a structured response packet corresponding to the user input information is obtained based on the gas standard knowledge base, and the structured response packet comprises standard original text reference, a technical parameter comparison table and a compliance process schematic diagram; and generating a response document corresponding to the user input information according to the structured response packet. When the user asks the gas related problem, the response document is generated by retrieving the standard original text application, the technical parameter comparison table and the compliance process schematic diagram corresponding to the information input by the user from the gas standard knowledge base, so that the problems that the existing gas standard retrieval tool is low in gas industry term recognition accuracy and high in efficiency can be effectively solved. The deviation between the retrieval result and the user demand is large, and the related standard content cannot be accurately matched.

Description

Technical Field

[0001] This invention relates to the fields of gas and artificial intelligence, and in particular to a smart response method, system, device and storage medium for the gas industry. Background Technology

[0002] In the daily operations of the gas industry, standard retrieval tools are crucial. However, the models used by traditional gas standard retrieval tools have low accuracy in recognizing gas industry terms such as "nominal diameter," "circumferential stress," "PE pipe," and "cast iron pipe." This makes it difficult for the system to understand the technical terms entered by the user, resulting in a large discrepancy between the search results and the user's needs, and an inability to accurately match relevant standard content.

[0003] Therefore, existing technologies still need improvement and development. Summary of the Invention

[0004] The technical problem to be solved by this invention is to provide a smart response method, system, device and storage medium for the gas industry, addressing the above-mentioned deficiencies of the prior art. The aim is to solve the problems of low accuracy in recognizing gas industry terms, large deviation between search results and user needs, and inability to accurately match relevant standard content in existing gas standard retrieval tools.

[0005] The technical solution adopted by this invention to solve the problem is as follows:

[0006] In a first aspect, embodiments of the present invention provide a smart response method for the gas industry, wherein the method includes:

[0007] Obtain user input information, perform intent recognition on the user input information, and determine the user intent;

[0008] When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on the user's intent and the gas standard knowledge base. The structured response package includes a standard original text reference, a technical parameter comparison table, and a compliance process diagram.

[0009] The response document corresponding to the user input information is generated based on the structured response package.

[0010] In one implementation method, performing intent recognition on the user input information to determine the user intent includes:

[0011] The user input information is preprocessed to determine the preprocessed information;

[0012] A bidirectional encoder representation model based on full-word masking extension is used to identify the intent of the preprocessed information and determine the user intent.

[0013] In one implementation method, the user input information is preprocessed to determine preprocessed information, including:

[0014] Constructing a knowledge graph in the field of gas engineering;

[0015] Based on the knowledge graph in the field of gas engineering, a semantic filtering algorithm is used to preprocess the user input information to determine the preprocessed information.

[0016] In one implementation method, obtaining a structured response package corresponding to the user input information based on the user intent and the gas standard knowledge base includes:

[0017] The user input information is identified by an improved bidirectional long short-term memory-conditional random field model to determine gas-related entities. The improved bidirectional long short-term memory-conditional random field model is achieved by adding a gas parameter weight enhancement layer to the bidirectional long short-term memory model of the bidirectional long short-term memory model.

[0018] The structured response package is obtained from the gas standard knowledge base based on the gas-related entities.

[0019] In one implementation method, obtaining the structured response package from the gas standard knowledge base based on the gas-related entity includes:

[0020] Based on the gas standard knowledge base, a paragraph-level vector indexer using a sentence-bidirectional encoder representation model combined with dynamic anchoring technology is used to construct a gas standard knowledge vector space.

[0021] Based on the gas-related entities, a response path is generated using a depth-first search algorithm based on the gas standard knowledge vector space;

[0022] The structured response package is obtained according to the response path.

[0023] In one implementation method, the gas standard knowledge base construction method includes:

[0024] Obtain a pre-built corpus of gas-related terms;

[0025] A hierarchical annotation strategy is adopted to annotate the parameters of each entity in the gas domain corpus to determine the gas standard knowledge base.

[0026] In one implementation method, generating a response document corresponding to the user input information based on the structured response package includes:

[0027] The standard clause parser based on regular expressions is used to extract the standard number, clause number, and version number information from the structured response package;

[0028] The response document is generated by combining the standard number, the clause number, and the version number according to the standard reference format.

[0029] Secondly, embodiments of the present invention also provide a smart response system for the gas industry, wherein the smart response system for the gas industry includes:

[0030] The intent recognition module is used to acquire user input information, perform intent recognition on the user input information, and determine the user intent.

[0031] The data retrieval module is used to obtain a structured response package corresponding to the user input information based on the user intent and the gas standard knowledge base when the user intent is to ask a gas-related question. The structured response package includes standard text references, technical parameter comparison tables, and compliance process diagrams.

[0032] The document generation module is used to generate a response document corresponding to the user input information based on the structured response package.

[0033] Thirdly, embodiments of the present invention also provide a terminal, the terminal including a memory and one or more processors; the memory stores one or more programs; the programs include instructions for executing the intelligent response method for the gas industry as described above; the processor is used to execute the programs.

[0034] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing a plurality of instructions, wherein the instructions are adapted to be loaded and executed by a processor to implement any of the above-described intelligent response methods for the gas industry.

[0035] The beneficial effects of this invention are as follows: In this embodiment, the invention acquires user input information, identifies the user's intent, and determines the user's intent. When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on the gas standard knowledge base. This structured response package includes standard text citations, technical parameter comparison tables, and compliance process diagrams. A response document corresponding to the user's input information is generated based on the structured response package. Because this invention retrieves the corresponding standard text application, technical parameter comparison tables, and compliance process diagrams from the gas standard knowledge base to generate a response document when a user asks a gas-related question, it effectively solves the problems of low accuracy in recognizing gas industry terminology, large discrepancies between search results and user needs, and inability to accurately match relevant standard content in existing gas standard retrieval tools. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a flowchart illustrating the intelligent response method for the gas industry provided in this embodiment of the invention.

[0038] Figure 2 This is a schematic diagram illustrating the specific implementation process of the intelligent response method for the gas industry provided in this embodiment of the invention.

[0039] Figure 3 This is a schematic diagram of the internal modules of the intelligent response system for the gas industry provided in an embodiment of the present invention.

[0040] Figure 4 This is a schematic diagram of the terminal provided in the embodiment of the present invention. Detailed Implementation

[0041] This invention discloses a smart response method, system, device, and storage medium for the gas industry. To make the objectives, technical solutions, and effects of this invention clearer and more explicit, the invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention.

[0042] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0043] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0044] In the daily operations of the gas industry, standard retrieval tools are crucial. However, the models used by traditional gas standard retrieval tools have low accuracy in recognizing gas industry terms such as "nominal diameter," "circumferential stress," "PE pipe," and "cast iron pipe." This makes it difficult for the system to understand the technical terms entered by the user, resulting in a large discrepancy between the search results and the user's needs, and an inability to accurately match relevant standard content.

[0045] To address the aforementioned shortcomings of existing technologies, this invention provides an intelligent response method for the gas industry. The method acquires user input information, performs intent recognition on the input, and determines the user's intent. When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is retrieved based on a gas standard knowledge base. This structured response package includes standard text citations, technical parameter comparison tables, and compliance process diagrams. A response document corresponding to the user's input information is then generated based on the structured response package. Because this invention retrieves the corresponding standard text applications, technical parameter comparison tables, and compliance process diagrams from the gas standard knowledge base to generate the response document when a user asks a gas-related question, it effectively solves the problems of low accuracy in recognizing gas industry terminology, large discrepancies between search results and user needs, and inability to accurately match relevant standard content in existing gas standard retrieval tools.

[0046] Exemplary method:

[0047] like Figure 1 As shown, the method includes:

[0048] Step S100: Obtain user input information, perform intent recognition on the user input information, and determine the user intent.

[0049] like Figure 2As shown, user input information refers to the information entered by the user on a terminal device that has this method loaded, used for interaction with the device. The terminal device acquires the user input information and processes it using the intelligent gas industry response system loaded on the terminal device. This includes intent recognition of the user input information to determine whether the user's intent is casual conversation, understanding a problem, or asking a gas-related question. Different actions are taken based on the determined user intent. If the user input information is for casual conversation, then the system guides the conversation accordingly.

[0050] In one implementation, performing intent recognition on the user input information to determine the user intent includes:

[0051] Step S101: Preprocess the user input information to determine the preprocessed information;

[0052] Step S102: Use a bidirectional encoder representation model based on full-word masking extension to perform intent recognition on the preprocessed information and determine the user intent.

[0053] Specifically, user input information is preprocessed to remove irrelevant words, ensuring the purity of the user's inquiry intent and improving the accuracy of intent recognition. A bidirectional encoder representation model with full-word masking extension (BERT-wwm-ext pre-trained model) is used to learn domain text standards based on gas-related knowledge graphs or gas industry dictionaries to complete the pre-training process. The pre-trained bidirectional encoder representation model with Euclidean full-word masking extension is then used to recognize intent from the preprocessed information to determine the user's intent.

[0054] In one implementation, the user input information is preprocessed to determine preprocessed information, including:

[0055] Step S1011: Construct a knowledge graph for the field of gas engineering;

[0056] Step S1012: Based on the knowledge graph of the gas engineering field, a semantic filtering algorithm is used to preprocess the user input information to determine the preprocessed information.

[0057] Specifically, a knowledge graph in the gas engineering field is a data representation that structures various knowledge within the gas field, including various entities (such as gas-related entities, gas types, etc.) and their relationships (such as the relationship between gas-related entities and gas types and characteristics). In this embodiment, a knowledge graph in the gas engineering field (including standard identifiers such as PE100 and X80 steel grades) is constructed. Based on this knowledge graph, a semantic filtering algorithm is used to preprocess user input information, removing words irrelevant to the gas field to obtain preprocessed information. In one implementation, a gas field knowledge graph combined with a conditional random field model can be used to achieve sequence labeling and feature extraction of material information, obtaining gas-related vocabulary; based on this gas-related vocabulary, irrelevant words in the user input information are removed to obtain preprocessed information.

[0058] Preprocessing user input information also includes: building a pressure value detection algorithm based on digital pattern matching, supporting automatic conversion and verification of MPa and kPa units, and issuing warning labels for user input information that exceeds the standard threshold (such as exceeding the design pressure by 1.5 times).

[0059] like Figure 1 As shown, the method further includes:

[0060] Step S200: When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on the user's intent and the gas standard knowledge base. The structured response package includes standard text references, technical parameter comparison tables, and compliance process diagrams.

[0061] Specifically, the Gas Standards Knowledge Base is a database that compiles relevant standards and specifications in the gas industry. This includes original standard references, technical parameter comparison tables, compliance process diagrams, and technical guidelines and principles for gas industry design, construction, operation, and management. When a user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on the user's intent and the Gas Standards Knowledge Base. For example, if the user's input intent is determined to be to obtain information about cast iron pipes, then based on this intent, the original standard references, technical parameter comparison tables, and compliance process diagrams for cast iron pipes are retrieved from the Gas Standards Knowledge Base, and a structured response package is generated.

[0062] In one implementation, the method for constructing the gas standard knowledge base includes:

[0063] Obtain a pre-built corpus of gas-related terms;

[0064] A hierarchical annotation strategy is adopted to annotate the parameters of each entity in the gas domain corpus to determine the gas standard knowledge base.

[0065] Specifically, the gas industry corpus integrates structured data from various gas technology standards, customer service dialogue records, and work order systems to construct a database encompassing 12 typical scenarios (covering standard queries, construction specifications, equipment maintenance, etc.). Based on this corpus, a hierarchical annotation strategy is employed: first-level annotations distinguish technical standard-related inquiries, second-level annotations refine these to six subcategories, and third-level annotations extract key entity parameters, forming a gas standard knowledge base containing over 720 annotated data entries. This base integrates original standard texts, technical parameters, compliance flowcharts, and a library of typical cases.

[0066] In one implementation, a structured response packet corresponding to the user input information is obtained based on the user intent and the gas standard knowledge base, including:

[0067] Step S201: Entity recognition is performed on the user input information using an improved bidirectional long short-term memory-conditional random field model to determine gas-related entities. The improved bidirectional long short-term memory-conditional random field model is achieved by adding a gas parameter weight enhancement layer to the bidirectional long short-term memory model in the bidirectional long short-term memory-conditional random field model.

[0068] Step S202: Obtain the structured response package from the gas standard knowledge base according to the gas-related entities.

[0069] In summary, this embodiment employs an improved Bidirectional Long Short-Term Memory-Conditional Random Field (BiLSTM-CRF) model to perform entity recognition and disambiguation on user input information, obtaining gas-related entities. Based on these entities, it then retrieves the corresponding structured response packets from the gas standard knowledge base. The BiLSTM-CRF model combines the advantages of Bidirectional Long Short-Term Memory networks and Conditional Random Fields, effectively processing contextual information in sequential data. This embodiment adds a gas parameter weight enhancement layer to the Bidirectional Long Short-Term Memory model of the BiLSTM-CRF model, weighting numerical features such as pressure values ​​and pipe diameter, making the model more focused on key gas parameters, thereby improving the accuracy and quality of semantic understanding.

[0070] In one implementation, obtaining the structured response package from the gas standard knowledge base based on the gas-related entity includes:

[0071] Step S2021: Based on the gas standard knowledge base, a paragraph-level vector indexer using a sentence-bidirectional encoder representation model combined with dynamic anchoring technology is used to construct a gas standard knowledge vector space.

[0072] Step S2022: Based on the gas-related entities, a response path is generated using a depth-first search algorithm based on the gas standard knowledge vector space;

[0073] Step S2023: Obtain the structured response package according to the response path.

[0074] Specifically, the Sentence-Bio Encoder Representation Model (SBERT) paragraph-level vector indexer is a tool that uses the SBERT representation model to calculate paragraph vectors and build an index, enabling rapid retrieval and matching of relevant paragraphs. Dynamic anchoring technology, by setting anchor tags and connection tags, allows for quick navigation from anchor tags to connection tags during indexing, thus accelerating the indexing process. This embodiment, based on a gas standard knowledge base, uses the SBERT representation model combined with dynamic anchoring technology to construct a gas standard knowledge vector space. The gas standard knowledge vector space transforms the content in the gas standard knowledge base, such as technical specifications, safety standards, and usage guidelines for gas equipment, into vector form. After constructing the gas standard knowledge vector space, a depth-first search algorithm is used to generate response paths based on gas-related entities. Based on these response paths, structured response packages corresponding to gas-related entities are retrieved from the gas standard knowledge vector space. Experimental results show that on a test set containing over 5000 standard clauses, this embodiment reduces the average retrieval response time to 2.87 seconds, a 2.2-fold improvement in efficiency compared to traditional keyword matching.

[0075] In one implementation, during the indexing process, a conflict detection algorithm is set up to address the multi-standard conflict problem in gas engineering design. Based on engineering parameters, the algorithm intelligently recommends the optimal standard combination and generates a citation list with traceability codes. In actual testing, on a test set containing over 3000 gas standards, the system's average response time was reduced to 2.8 seconds, and the citation accuracy was improved by 22% compared to traditional keyword matching.

[0076] Step S300: Generate a response document corresponding to the user input information based on the structured response package.

[0077] In simple terms, the structured response package includes the structured response packages corresponding to the gas-related entities in the user's input information, such as the original standard text, technical parameters, and compliance flowcharts for those entities. Information is extracted from the structured response package and a response document is generated according to a preset format.

[0078] In one implementation, generating a response document corresponding to the user input information based on the structured response packet includes:

[0079] Step S301: Use a standard clause parser based on regular expressions to extract the standard number, clause number, and version number information from the structured response package;

[0080] Step S302: Generate the response document by combining the standard number, the clause number, and the version number information according to the standard reference format.

[0081] Specifically, a standard clause parser based on regular expressions is used to automatically extract standard numbers, clause numbers, and version information from the structured response package. This information is then combined with a template engine to generate a pre-defined specification citation format, ensuring the compliance of the response document, improving its standardization and credibility, facilitating user tracing and access to the original standards, and ensuring information accuracy and timeliness. Actual testing shows that the citation generation accuracy rate can reach 99.2%.

[0082] This embodiment employs a bidirectional encoder representation model based on full-word masking extension for domain text representation learning at the bottom layer, a bidirectional long short-term memory-conditional random field model for fine-grained element extraction of standard clauses at the middle layer, and a reinforcement learning algorithm to optimize standard citation path planning at the top layer. Furthermore, the introduction of a gas standard knowledge base and dynamic context embedding enables the method in this embodiment to achieve a recognition rate of 92.6% for professional terms such as gas leak detection and pipeline stress analysis.

[0083] Based on the above embodiments, the present invention also provides an intelligent response system for the gas industry, such as... Figure 3 As shown, the system includes:

[0084] Intent recognition module 01 is used to acquire user input information, perform intent recognition on the user input information, and determine the user intent;

[0085] The data retrieval module 02 is used to obtain a structured response package corresponding to the user input information based on the user intent and the gas standard knowledge base when the user intent is to ask a gas-related question. The structured response package includes standard original text references, technical parameter comparison tables, and compliance process diagrams.

[0086] The document generation module 03 is used to generate a response document corresponding to the user input information based on the structured response package.

[0087] Based on the above embodiments, the present invention also provides a terminal, the principle block diagram of which can be as follows: Figure 4As shown, the terminal includes a processor, memory, network interface, and display screen connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides the environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a smart response method for the gas industry. The display screen can be an LCD screen or an e-ink screen.

[0088] Those skilled in the art will understand that Figure 4 The schematic diagram shown is only a partial structural diagram related to the present invention and does not constitute a limitation on the terminal to which the present invention is applied. A specific terminal may include more or fewer components than shown in the figure, or combine certain components, or have different component arrangements.

[0089] In one implementation, the terminal's memory stores one or more programs, and these programs are configured to be executed by one or more processors, and the programs contain instructions for performing a smart response method for the gas industry.

[0090] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0091] In summary, this invention discloses an intelligent response method, system, device, and storage medium for the gas industry. The method acquires user input information, identifies the user's intent, and determines the user's intent. When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on a gas standard knowledge base. This structured response package includes standard text citations, technical parameter comparison tables, and compliance process diagrams. A response document corresponding to the user's input information is generated based on the structured response package. Because this invention retrieves the corresponding standard text applications, technical parameter comparison tables, and compliance process diagrams from the gas standard knowledge base to generate the response document when a user asks a gas-related question, it effectively solves the problems of low accuracy in recognizing gas industry terminology, large discrepancies between search results and user needs, and inability to accurately match relevant standard content in existing gas standard retrieval tools.

[0092] It should be understood that the application of the present invention is not limited to the examples above. Those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims.

Claims

1. A smart response method for the gas industry, characterized in that, The method includes: Obtain user input information, perform intent recognition on the user input information, and determine the user intent; When the user's intent is to ask a gas-related question, a structured response package corresponding to the user's input information is obtained based on the user's intent and the gas standard knowledge base. The structured response package includes a standard original text reference, a technical parameter comparison table, and a compliance process diagram. The response document corresponding to the user input information is generated based on the structured response package.

2. The intelligent response method for the gas industry according to claim 1, characterized in that, Perform intent recognition on the user input information to determine the user intent, including: The user input information is preprocessed to determine the preprocessed information; A bidirectional encoder representation model based on full-word masking extension is used to identify the intent of the preprocessed information and determine the user intent.

3. The intelligent response method for the gas industry according to claim 2, characterized in that, The user input information is preprocessed to determine preprocessed information, including: Constructing a knowledge graph in the field of gas engineering; Based on the knowledge graph in the field of gas engineering, a semantic filtering algorithm is used to preprocess the user input information to determine the preprocessed information.

4. The intelligent response method for the gas industry according to claim 1, characterized in that, Based on the user intent and the gas standard knowledge base, a structured response package corresponding to the user input information is obtained, including: The user input information is identified by an improved bidirectional long short-term memory-conditional random field model to determine gas-related entities. The improved bidirectional long short-term memory-conditional random field model is achieved by adding a gas parameter weight enhancement layer to the bidirectional long short-term memory model of the bidirectional long short-term memory model. The structured response package is obtained from the gas standard knowledge base based on the gas-related entities.

5. The intelligent response method for the gas industry according to claim 4, characterized in that, The structured response package is obtained from the gas standard knowledge base based on the gas-related entities, including: Based on the gas standard knowledge base, a paragraph-level vector indexer using a sentence-bidirectional encoder representation model combined with dynamic anchoring technology is used to construct a gas standard knowledge vector space. Based on the gas-related entities, a response path is generated using a depth-first search algorithm based on the gas standard knowledge vector space; The structured response package is obtained according to the response path.

6. The intelligent response method for the gas industry according to claim 1, characterized in that, The method for constructing the gas standard knowledge base includes: Obtain a pre-built corpus of gas-related terms; A hierarchical annotation strategy is adopted to annotate the parameters of each entity in the gas domain corpus to determine the gas standard knowledge base.

7. The intelligent response method for the gas industry according to claim 1, characterized in that, Generate a response document corresponding to the user input information based on the structured response package, including: The standard clause parser based on regular expressions is used to extract the standard number, clause number, and version number information from the structured response package; The response document is generated by combining the standard number, the clause number, and the version number according to the standard reference format.

8. A smart response system for the gas industry, characterized in that, The system includes: The intent recognition module is used to acquire user input information, perform intent recognition on the user input information, and determine the user intent; The data retrieval module is used to obtain a structured response package corresponding to the user input information based on the user intent and the gas standard knowledge base when the user intent is to ask a gas-related question. The structured response package includes standard text references, technical parameter comparison tables, and compliance process diagrams. The document generation module is used to generate a response document corresponding to the user input information based on the structured response package.

9. A terminal, characterized in that, The terminal includes a memory and one or more processors; the memory stores one or more programs; the programs contain instructions for executing the smart response method for the gas industry as described in any one of claims 1-7; the processors are used to execute the programs.

10. A computer-readable storage medium storing a plurality of instructions thereon, characterized in that, The instructions are loaded and executed by the processor to implement the steps of the intelligent response method for the gas industry as described in any one of claims 1-7.

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