Legal regulation display method and related equipment

Abstract

The embodiment of the invention provides a legal regulation display method and related equipment, and belongs to the technical field of natural language processing. According to the embodiment of the invention, deep semantic understanding, intelligent sorting of laws and regulations, accurate positioning of specific clauses and abstract generation can be carried out on the clause query information, the whole process is highly automatic, the consulting burden of a user is greatly relieved, the working efficiency is improved, the specific clauses most related to the user problem can be directly presented, and the user experience is improved. And display is carried out in a clear and structured manner (such as abstracts and core regulation cards), so that the regulation content is clear at a glance, and rapid understanding and application are facilitated.

Description

Technical Field

[0001] This application relates to the field of natural language processing technology, and in particular to a legally mandated display method and related equipment. Background Technology

[0002] With the continuous advancement of the rule of law in China, the number of laws, regulations, rules, and normative documents has increased dramatically and they are frequently updated, forming a complex and dynamic legal system. For legal professionals, corporate compliance personnel, and the general public, quickly and accurately finding currently effective legal provisions that are highly relevant to their needs from this vast legal database presents a significant challenge.

[0003] Currently, mainstream legal retrieval systems (such as national legal databases) mainly rely on keyword matching or full-text search technology. Although these systems can return a list of regulations containing the keywords entered by the user, the search results are often based on the entire regulation. Users need to manually browse through lengthy legal texts to locate the specific clauses (legal provisions) directly related to their own issues, which is a cumbersome and inefficient process.

[0004] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0005] The main objective of this application is to propose a method and related equipment for displaying legal provisions. By introducing intelligent semantic understanding and a multi-dimensional weighted ranking model, it aims to solve the problem of low accuracy in legal retrieval in the prior art, thereby achieving accurate and efficient delivery of legal provisions.

[0006] To achieve the above objectives, one aspect of this application provides a method for displaying legal provisions, the method comprising: Semantic recognition is performed on the query information entered by the user to generate a structured query object; Retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; The regulations to be displayed are weighted and sorted in multiple dimensions using a scoring algorithm to obtain a sequence to be displayed. The sequence to be displayed is shown to the user.

[0007] In some embodiments, the step of using a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain a display sequence includes: Using a scoring algorithm, the regulations to be displayed are weighted and sorted in multiple dimensions based on at least one of the following: legal effect, legal validity, legal attribution, legal relevance, and legal citation frequency, to obtain a display sequence.

[0008] In some embodiments, the step of semantically recognizing the text query information input by the user and generating a structured query object includes: Extract the core keywords from the query information of the article; Identify the legal field to which the query information pertains; The query intent is categorized based on the query information of the aforementioned articles; Based on the legal field and query intent, complete the implicit keywords; Generate a structured query object containing the core keywords, the legal field, the query intent, and the implicit keywords.

[0009] In some embodiments, the step of using a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain a display sequence includes: The regulations to be displayed are weighted and ranked in multiple dimensions using a scoring algorithm to determine the target regulations. In the target regulations, query multiple legal provisions to be displayed that correspond to the structured query object; Calculate the correlation degree between the legal provisions to be displayed and the structured query object; Based on the order of legal relevance from high to low, a preset number of legal provisions to be displayed are determined, and the target regulations containing the legal provisions to be displayed are taken as the display sequence.

[0010] In some embodiments, the step of using a scoring algorithm to perform multi-dimensional weighted ranking of the regulations to be displayed based on at least one of the following: legal effect, legal validity, legal attribution, legal relevance, and legal citation frequency, to obtain a display sequence includes: By combining the first weight corresponding to the legal effect, the first proportion of the legal effect is determined; By combining the second weight corresponding to the legal relevance, a second proportion of the legal relevance is determined; By combining the third weight corresponding to the legal citation frequency, a second proportion of the legal citation frequency is determined; By combining the first proportion, the second proportion, the third proportion, the legal statute of limitations, and the legal attribution, the regulations to be displayed are sorted in a multi-dimensional weighted order to obtain the display sequence.

[0011] In some embodiments, the step of combining the first proportion, the second proportion, the third proportion, the statute of limitations, and the legal attribution to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain the display sequence includes: The weighted score of the regulation to be displayed is determined by combining the first proportion, the second proportion, the third proportion, the statute of limitations, and the legal attribution. The regulations to be displayed are sorted according to the weighted scores to obtain the display sequence.

[0012] To achieve the above objectives, another aspect of this application provides a legally mandated display device, the device comprising: The generation module is used to perform semantic recognition on the text query information input by the user and generate a structured query object; The retrieval module is used to retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; The sorting module is used to perform multi-dimensional weighted sorting of the regulations to be displayed using a scoring algorithm to obtain the sequence to be displayed; The display module is used to display the sequence to be displayed to the user.

[0013] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0014] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a method, apparatus, electronic device, storage medium, and program product for displaying legal provisions. This solution generates a structured query object by semantically recognizing the text query information input by the user; retrieves at least one regulation corresponding to the structured query object from a legal provision information database to obtain the regulation to be displayed; uses a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain a display sequence; and displays the display sequence to the user. The embodiments of this application perform deep semantic understanding of the text query information, intelligent sorting of regulations, and precise location and summary generation of specific clauses. The entire process is highly automated, greatly reducing the user's browsing burden and improving work efficiency. It can directly present the specific legal provisions most relevant to the user's question and display them in a clear and structured manner (such as summaries and core regulation cards), making the regulatory content readily understandable and easy to quickly understand and apply. Attached Figure Description

[0017] Figure 1This is a flowchart of the legal provision display method provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S101 in the text; Figure 3 This is a schematic diagram of the structure of the legally required display device provided in the embodiments of this application; Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0020] Before providing a detailed description of the embodiments of this application, some of the nouns and terms involved in the embodiments of this application will be explained first. The nouns and terms involved in the embodiments of this application are subject to the following interpretations.

[0021] 1) Legal effect: refers to the hierarchy and degree of enforceability of laws and regulations within the legal system. It is usually determined by the issuing authority and the type of regulation, such as the constitution, laws, and administrative regulations, which have different levels of legal effect.

[0022] 2) Statute of limitations: refers to the validity and age of laws and regulations in the time dimension, including whether they have been repealed and how long ago they were last revised.

[0023] 3) Frequency of legal citation: refers to the number of times a regulation is cited by other regulations, judicial decisions or legal documents in legal practice and academic research. It is usually used as a quantitative indicator of its influence and importance.

[0024] 4) Legal relevance: refers to the degree of semantic matching and relevance between a law (legal provision) and the information queried by the user.

[0025] In related technologies, mainstream legal retrieval systems (such as national legal databases) mainly rely on keyword matching or full-text search technologies. Although these systems can return a list of regulations containing the keywords entered by the user, the search results are often based on the entire regulation. Users need to manually browse through lengthy legal texts to locate the specific clauses (legal provisions) directly related to their own issues, which is a cumbersome and inefficient process.

[0026] In view of this, this application provides a method for displaying legal provisions. This method performs deep semantic understanding of the text query information, intelligent sorting of regulations, and precise positioning and summary generation of specific clauses. The entire process is highly automated, which greatly reduces the user's search burden and improves work efficiency. It can directly present the specific legal provisions most relevant to the user's question and display them in a clear and structured manner (such as summaries and core regulation cards), making the content of the regulations clear at a glance and easy to understand and apply quickly.

[0027] The legal provision display method provided in this application relates to the field of natural language processing. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited thereto. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the legal provision display method, but is not limited to the above forms.

[0028] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0029] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0030] Figure 1 This is an optional flowchart of the legal provision display method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S101 to S104.

[0031] Step S101: Perform semantic recognition on the text query information input by the user to generate a structured query object.

[0032] User queries are typically in natural language form, such as "My company needs to treat industrial wastewater, what are the regulations?". The core task of this step is to transform vague user intent into precise, structured search instructions.

[0033] Please refer to the following: Figure 2 It illustrates a specific implementation process of step S101, including: Step S201: Extract the core keywords from the query information.

[0034] Extract the core keywords from the query. For example, from the query above, we can extract "industrial wastewater", "treatment", and "regulations".

[0035] Step S202: Identify the legal domain to which the article query information belongs.

[0036] Based on the extracted keywords, the legal field to which the query belongs can be identified. For example, the query can be identified as belonging to the field of "water pollution prevention" under "environmental protection".

[0037] Step S203: Classify the query intent of the text query information.

[0038] Determine the user's query purpose. For example, is the query for "compliance requirements," "legal liability," "approval process," or "penalty standards"? In this example, it can be categorized as "compliance requirements query."

[0039] Step S204: Based on the legal field and query intent, complete the hidden keywords.

[0040] Based on the identified legal domains and query intents, a domain knowledge graph is used to complete the keywords that users may be interested in but have not explicitly stated. For example, keywords such as "discharge permit," "emission standards," "sewage treatment facilities," and "environmental impact assessment" are completed.

[0041] Step S205: Generate a structured query object containing core keywords, legal field, query intent, and implicit keywords.

[0042] All the above information is integrated into a structured data object. This structured object lays a solid foundation for subsequent accurate retrieval.

[0043] Step S102: Retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed.

[0044] This embodiment primarily enables the rapid identification of all candidate regulations that may be relevant to the query from a vast regulatory database.

[0045] Based on the core and implicit keywords in the structured object, Boolean or TF-IDF searches are performed on the titles, abstracts, and full texts of regulations. A semantic model (such as BERT) is used to convert the structured query object (or its textual representation) and the titles / abstracts of all regulations into vectors. The most relevant batch of regulations is recalled by calculating vector similarity (such as cosine similarity). The recalled regulations are then filtered to narrow the search scope. Finally, the results from these multiple recall methods are merged and deduplicated to form the final list of regulations to be displayed.

[0046] Step S103: Use a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain the display sequence.

[0047] First, use a multi-dimensional weighted scoring model to calculate the comprehensive score of each regulation.

[0048] The scoring model includes at least the following dimensions: Legal effect: Assign fixed scores according to the type of regulation. For example: Constitution (100 points), Law (90 points), Administrative Regulation (80 points), Departmental Regulation (60 points), etc.

[0049] Legal relevance: Use a semantic model to calculate the semantic similarity between the user query and the title and abstract of the regulation, and normalize it to 0-100 points.

[0050] Legal citation frequency: Count the number of times the regulation is cited, and use a logarithmic function to calculate the score to avoid the influence of extreme values.

[0051] Legal timeliness: Calculate the timeliness coefficient. The rules are as follows: If the regulation has been repealed, the coefficient is 0; otherwise, calculate the year difference Y between its last revision date and the current date. If Y <= 3, the coefficient is 1.0; 3 < Y <= 5, the coefficient is 0.9; 5 < Y <= 10, the coefficient is 0.7; Y > 10, the coefficient is 0.5.

[0052] Legal attribution / scope coefficient: Assign a coefficient according to the scope of application. National regulations are 1.0, provincial regulations are 0.8, municipal regulations are 0.6, and industry regulations are 0.7.

[0053] The formula for calculating the comprehensive score is: Comprehensive score = (Effect score × W_effect + Relevance score × W_relevance + Citation score × W_citation) × Timeliness coefficient × Scope coefficient. Where, W_effect, W_relevance, and W_citation are the preset first weight, second weight, and third weight, and W_effect + W_relevance + W_citation = 1. For example, it can be set as W_effect = 0.5, W_relevance = 0.4, W_citation = 0.1 to emphasize the effect and relevance.

[0054] Sort all the regulations to be displayed in descending order according to the comprehensive score, and initially obtain a sorted list. Select the top N (for example, the first 5) regulations with the highest scores from the sorted list as the target regulations and enter the next stage of fine processing.

[0055] To achieve the precision of the results, the system traverses and analyzes each target regulation at the clause level. This process includes: ① Split the whole regulation into clauses.

[0056] ② For each clause, use a semantic model to calculate its semantic relevance to the original user query or the structured query object.

[0057] ③ Each regulation retains the K (e.g., 3) most relevant clauses. For example, in the Water Pollution Prevention and Control Law, these might be Article 20 (Discharge Permit), Article XX (Emission Standards), etc.

[0058] ④ Aggregate the results of clause-level location according to the original target regulations. At this point, each target regulation is associated with its most relevant specific clauses. The system ultimately generates a "sequence to be displayed" that is organized by regulation but has been finely located down to the specific clauses. This sequence not only considers the overall weight of the regulations but also incorporates the relevance at the clause level, ensuring the accuracy of the final output.

[0059] Step S104: Display the sequence to be displayed to the user.

[0060] The sorted and positioned results are presented to the user in a clear, user-friendly, and structured manner. For example, the sequence to be displayed could be: ① Use a Large Language Model (LLM) to automatically generate a summary of the key points of the query results, quickly conveying core compliance information.

[0061] ② Display each core regulation in card format according to the order of the sequence to be displayed.

[0062] Each card includes: the title of the regulation, its level of legal force (e.g., "Law"), its status of validity (e.g., "Currently in force"), the date of last revision, and a comprehensive score. Below or inside the card, a list clearly displays the relevant legal provision numbers and a summary of the content. ③Prohibited, newly issued, or soon-to-be-effective regulations should be clearly marked with eye-catching visual labels.

[0063] The solution illustrated in this application, through intelligent processing of the entire process from semantic understanding to multi-dimensional quantitative sorting, and then to precise positioning at the clause level, ultimately achieves accurate, authoritative, timely, and user-friendly display of legal retrieval results.

[0064] In some examples, users query "regulations related to corporate carbon emission management". The system parses the query, generates a structured object containing core keywords "corporate", "carbon emission", and "management", legal terms "environmental protection" and "climate change", intent "compliance requirements", and completes implicit keywords such as "carbon emission trading", "emissions reporting", and "verification".

[0065] Example content: Environmental Protection Law of the People's Republic of China (Law level, revised in 2014, currently in effect) - Priority: 90 points Interim Regulations on the Administration of Carbon Emission Trading (Administrative Regulation, to be implemented in 2024, currently in effect) - Priority: 80 points "Guidelines for Verification of Enterprise Greenhouse Gas Emission Reports (Trial)" (Departmental Regulation, issued in 2021) - Priority: 60 points Smart Summary: According to the latest regulations, enterprises with an annual carbon emission of 26,000 tons of CO2 equivalent should be included in the national carbon emission trading market and fulfill their emission reporting obligations in accordance with Article 12 of the Interim Regulations on the Administration of Carbon Emission Trading.

[0066] The solution illustrated in this application, through intelligent processing of the entire process from semantic understanding to multi-dimensional quantitative sorting, and then to precise positioning at the clause level, ultimately achieves accurate, authoritative, timely, and user-friendly display of legal retrieval results.

[0067] In some examples, users query "regulations related to corporate carbon emission management." The system parses the query, generates a structured object containing core keywords such as "corporate," "carbon emission," and "management," legal terms such as "environmental protection" and "climate change," and the intent "compliance requirements," while also supplementing with implicit keywords such as "carbon emission trading," "emissions reporting," and "verification." Multiple recalls may include regulations such as the Environmental Protection Law, the Interim Regulations on the Management of Carbon Emission Trading, and the Guidelines for Verification of Corporate Greenhouse Gas Emission Reports.

[0068] Scoring of regulations: Environmental Protection Law (Law, revised in 2014): Effectiveness 90, Relevance 85, Citations 32, Timeliness Coefficient 0.7, Scope 1.0 → Overall Score approximately 57.54.

[0069] Interim Regulations on the Administration of Carbon Emission Trading (Administrative Regulations, effective in 2024): Effectiveness 80, Relevance 95, Citation Score 15, Timeliness Coefficient 1.0, Scope 1.0 → Higher overall score (e.g., 80+).

[0070] "Guidelines for Verification of Enterprise Greenhouse Gas Emission Reports" (Departmental Regulations, issued in 2021): Validity 60, Relevance 90, Citation score 10, Timeliness coefficient 1.0, Scope 1.0 → Overall score is moderate.

[0071] After sorting, the above three regulations were identified as the target regulations.

[0072] Identify the most relevant legal provisions among various regulations, such as Article 12 in the "Interim Regulations on the Administration of Carbon Emission Trading" (entry thresholds and reporting obligations for enterprises to be included in the trading market).

[0073] The generated summary reads: "According to the latest regulations, enterprises must be included in the national carbon emission trading market and fulfill their emission reporting obligations in accordance with the Interim Regulations on the Administration of Carbon Emission Trading." Regulatory card sequence: The card for the "Interim Regulations on the Administration of Carbon Emission Trading" (highest priority), item 12 below.

[0074] The following are the relevant principle clauses from the Environmental Protection Law of the People's Republic of China card.

[0075] The following are the specific verification requirements clauses in the "Guidelines for Verification of Corporate Greenhouse Gas Emissions Reports" card.

[0076] Steps S101 to S104 of this embodiment involve semantic recognition of the user-inputted query information to generate a structured query object; retrieving at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; using a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain a display sequence; and displaying the display sequence to the user. This embodiment of the application, from deep semantic understanding of the query information to intelligent sorting of regulations, and then to precise location and summary generation of specific clauses, is highly automated throughout the entire process. This greatly reduces the user's search burden, improves work efficiency, and directly presents the specific legal provisions most relevant to the user's question in a clear and structured manner (such as summaries and core regulation cards), making the regulatory content readily understandable and easy to quickly understand and apply.

[0077] Please see Figure 3 This application also provides a legal provision display device that can implement the above-described method. The device includes: The generation module 31 is used to perform semantic recognition on the text query information input by the user and generate a structured query object; The retrieval module 32 is used to retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; The sorting module 33 is used to perform multi-dimensional weighted sorting of the regulations to be displayed using a scoring algorithm to obtain the sequence to be displayed; Display module 34 is used to display the sequence to be displayed to the user. In some embodiments, the sorting module 33 is used to use a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed based on at least one of the legal effect, legal validity, legal attribution, legal relevance, and legal citation frequency, to obtain a display sequence.

[0078] In some embodiments, the generation module 31 is configured to: Extract the core keywords from the query information of the article; Identify the legal field to which the query information pertains; The query intent is categorized based on the query information of the aforementioned articles; Based on the legal field and query intent, complete the implicit keywords; Generate a structured query object containing the core keywords, the legal field, the query intent, and the implicit keywords.

[0079] In some embodiments, the sorting module 33 is used for: The regulations to be displayed are weighted and ranked in multiple dimensions using a scoring algorithm to determine the target regulations. In the target regulations, query multiple legal provisions to be displayed that correspond to the structured query object; Calculate the correlation degree between the legal provisions to be displayed and the structured query object; Based on the order of legal relevance from high to low, a preset number of legal provisions to be displayed are determined, and the target regulations containing the legal provisions to be displayed are taken as the display sequence.

[0080] In some embodiments, the sorting module 33 is used for: By combining the first weight corresponding to the legal effect, the first proportion of the legal effect is determined; By combining the second weight corresponding to the legal relevance, a second proportion of the legal relevance is determined; By combining the third weight corresponding to the legal citation frequency, a second proportion of the legal citation frequency is determined; By combining the first proportion, the second proportion, the third proportion, the legal statute of limitations, and the legal attribution, the regulations to be displayed are sorted in a multi-dimensional weighted order to obtain the display sequence.

[0081] In some embodiments, the sorting module 33 is used for: The weighted score of the regulation to be displayed is determined by combining the first proportion, the second proportion, the third proportion, the statute of limitations, and the legal attribution. The regulations to be displayed are sorted according to the weighted scores to obtain the display sequence.

[0082] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0083] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0084] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0085] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 401 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 402 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 402 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401 using the methods described in the embodiments of this application. Input / output interface 403 is used to implement information input and output; The communication interface 404 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 405 transmits information between various components of the device (e.g., processor 401, memory 402, input / output interface 403, and communication interface 404); The processor 401, memory 402, input / output interface 403 and communication interface 404 are connected to each other within the device via bus 405.

[0086] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0087] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0088] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0089] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0090] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0091] The legal provision display method, apparatus, electronic device, storage medium, and program product provided in this application embodiment perform semantic recognition on the text query information input by the user to generate a structured query object; retrieve at least one regulation corresponding to the structured query object from the legal provision information database to obtain the regulation to be displayed; use a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain a display sequence; and display the display sequence to the user. This application embodiment performs deep semantic understanding of the text query information, intelligent sorting of regulations, and precise location and summary generation of specific clauses. The entire process is highly automated, greatly reducing the user's search burden and improving work efficiency. It can directly present the specific legal provisions most relevant to the user's question and display them in a clear and structured manner (such as summaries and core regulation cards), making the regulatory content easy to understand and apply quickly.

[0092] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0093] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0094] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0095] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0096] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0097] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0098] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0099] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0100] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0101] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0102] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A legally prescribed display method, characterized in that, The method includes: Semantic recognition is performed on the query information entered by the user to generate a structured query object; Retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; The regulations to be displayed are weighted and sorted in multiple dimensions using a scoring algorithm to obtain a sequence to be displayed. The sequence to be displayed is shown to the user.

2. The method according to claim 1, characterized in that, The step of using a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain the display sequence includes: Using a scoring algorithm, the regulations to be displayed are weighted and sorted in multiple dimensions based on at least one of the following: legal effect, legal validity, legal attribution, legal relevance, and legal citation frequency, to obtain a display sequence.

3. The method according to claim 1, characterized in that, The step of semantically recognizing the user-inputted query information and generating a structured query object includes: Extract the core keywords from the query information of the article; Identify the legal field to which the query information pertains; The query intent is categorized based on the query information of the aforementioned articles; Based on the legal field and query intent, complete the implicit keywords; Generate a structured query object containing the core keywords, the legal field, the query intent, and the implicit keywords.

4. The method according to claim 1, characterized in that, The step of using a scoring algorithm to perform multi-dimensional weighted sorting of the regulations to be displayed to obtain the display sequence includes: The regulations to be displayed are weighted and ranked in multiple dimensions using a scoring algorithm to determine the target regulations. In the target regulations, query multiple legal provisions to be displayed that correspond to the structured query object; Calculate the correlation degree between the legal provisions to be displayed and the structured query object; Based on the order of legal relevance from high to low, a preset number of legal provisions to be displayed are determined, and the target regulations containing the legal provisions to be displayed are taken as the display sequence.

5. The method according to claim 2, characterized in that, The method utilizes a scoring algorithm to perform multi-dimensional weighted ranking of the regulations to be displayed based on at least one of the following: legal effect, legal validity, legal attribution, legal relevance, and legal citation frequency, to obtain a display sequence, including: By combining the first weight corresponding to the legal effect, the first proportion of the legal effect is determined; By combining the second weight corresponding to the legal relevance, a second proportion of the legal relevance is determined; By combining the third weight corresponding to the legal citation frequency, a second proportion of the legal citation frequency is determined; By combining the first proportion, the second proportion, the third proportion, the legal statute of limitations, and the legal attribution, the regulations to be displayed are sorted in a multi-dimensional weighted order to obtain the display sequence.

6. The method according to claim 5, characterized in that, The process of combining the first proportion, the second proportion, the third proportion, the statute of limitations, and the legal attribution to obtain a multi-dimensional weighted sort of the regulations to be displayed, including: The weighted score of the regulation to be displayed is determined by combining the first proportion, the second proportion, the third proportion, the statute of limitations, and the legal attribution. The regulations to be displayed are sorted according to the weighted scores to obtain the display sequence.

7. A legally mandated display device, characterized in that, The device includes: The generation module is used to perform semantic recognition on the text query information input by the user and generate a structured query object; The retrieval module is used to retrieve at least one regulation corresponding to the structured query object from the legal information database to obtain the regulation to be displayed; The sorting module is used to perform multi-dimensional weighted sorting of the regulations to be displayed using a scoring algorithm to obtain the sequence to be displayed; The display module is used to display the sequence to be displayed to the user.

8. An electronic device, characterized in that, The electronic device / computer apparatus includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 6.

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