Method and system for intelligently solving problems in engineering construction industry

Abstract

The invention discloses an engineering construction industry problem intelligent solution method and system, and the method comprises the steps: constructing an engineering construction industry knowledge base based on the engineering construction industry knowledge, extracting knowledge and the association relationship between the knowledge from the engineering construction industry knowledge base, and constructing an engineering construction industry knowledge association graph; converting an engineering construction problem retrieved by a user into a corresponding semantic representation through natural language processing, matching the semantic representation with knowledge nodes in the engineering construction industry knowledge association graph, determining the matched knowledge nodes, sorting the matched knowledge nodes according to the matching degree and / or importance, and storing the sorted knowledge nodes in the engineering construction industry knowledge association graph. And querying corresponding knowledge data from the engineering construction industry knowledge base according to the sorted knowledge nodes, and generating a retrieval result. Technicians can be helped to quickly find knowledge required for solving engineering construction problems, and the efficiency and accuracy of solving the engineering construction problems by the technicians can be improved.

Description

Technical Field

[0001] The present invention relates to the field of engineering construction technology, and in particular to an intelligent solution and system for problems in the engineering construction industry. Background Art

[0002] In recent years, with the rapid development of the engineering construction industry, the amount of knowledge data involved in engineering projects has exploded, encompassing information on design specifications, construction techniques, quality management, safety measures, cost control, and more. Currently, engineering construction companies generally use traditional systems such as PDM (Product Data Management) and ERP (Enterprise Resource Planning) for knowledge management. These systems primarily rely on predefined structured rules and keyword matching to store and retrieve knowledge.

[0003] However, in actual applications, when technical personnel encounter engineering construction problems, they often need to search for historical engineering cases and draw on experience to find solutions. However, the manual search process is cumbersome, not only time-consuming, but also prone to missing important information. In addition, although existing PDM, ERP and other systems provide knowledge management functions, due to their reliance on fixed structured rules, accurate keywords must be used when searching, resulting in a limited search scope and difficulty covering all possible expressions of actual problems. It is difficult for technical personnel to accurately find the knowledge needed to solve engineering construction problems. How to assist technical personnel in quickly finding the knowledge needed to solve engineering construction problems and improve the efficiency of technical personnel in solving engineering construction problems is a problem that urgently needs to be solved by existing technologies. Summary of the Invention

[0004] In order to solve at least one technical problem in the above-mentioned background technology, the present invention proposes an intelligent solution method and system for solving problems in the engineering construction industry.

[0005] To achieve the above objectives, according to one aspect of the present invention, an intelligent solution to problems in the engineering construction industry is provided, the method comprising:

[0006] Building an engineering construction industry knowledge base based on engineering construction industry knowledge, and extracting knowledge and the relationship between knowledge from the engineering construction industry knowledge base to build an engineering construction industry knowledge relationship map;

[0007] Through natural language processing, the engineering construction problems retrieved by users are converted into corresponding semantic representations, and the semantic representations are matched with the knowledge nodes in the engineering construction industry knowledge association graph to determine the matching knowledge nodes. The matching knowledge nodes are sorted according to the matching degree and / or importance, and the corresponding knowledge data are queried from the engineering construction industry knowledge base based on the sorted knowledge nodes to generate search results.

[0008] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0009] Before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results, and the user's corresponding knowledge intelligent recommendation information to the user, an encryption key is generated based on the user's identity information, the data is encrypted based on the encryption key, and then the encrypted data is sent to the user's local terminal, so that the user obtains the encryption key through a decryption authorization process at the local terminal, and then decrypts the encrypted data.

[0010] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0011] Establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the method's application examples and guidance to the user.

[0012] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0013] Generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes;

[0014] The matching of the semantic representation with the knowledge nodes in the engineering construction industry knowledge association graph to determine the matching knowledge nodes includes:

[0015] The semantic representation is matched with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

[0016] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0017] Based on the user's historical search record information, department information and project participation information, the preset demand prediction model is used to predict the user's engineering construction knowledge needs, and then the corresponding knowledge data is queried from the engineering construction industry knowledge base based on the engineering construction knowledge needs and knowledge intelligent recommendation information is generated.

[0018] Optionally, the construction of an engineering construction industry knowledge base based on engineering construction industry knowledge includes:

[0019] The engineering construction industry knowledge is classified and organized according to the engineering project stages and professional fields to establish the engineering construction industry knowledge base, wherein the engineering construction industry knowledge includes: industry standards and specifications information, construction technology and process information, design and planning information, quality management and testing information, safety management information, cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

[0020] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0021] Before the user accesses the cloud analysis model, it is verified whether the user is in the preset whitelist. If so, the user's access request is approved; if not, the user's access request is rejected.

[0022] Optionally, the intelligent solution to the problems in the engineering construction industry also includes:

[0023] An innovative method practice platform is built to enable the users to perform method simulation, solution design and optimization analysis based on the recommended innovative method on the innovative method practice platform to form innovative solutions.

[0024] In order to achieve the above objectives, according to another aspect of the present invention, a system for intelligently solving problems in the engineering construction industry is provided, the system comprising:

[0025] A knowledge base construction module is used to construct an engineering construction industry knowledge base based on engineering construction industry knowledge, and to extract knowledge and the relationship between knowledge from the engineering construction industry knowledge base to construct an engineering construction industry knowledge relationship map;

[0026] The intelligent retrieval module is used to convert the engineering construction problems retrieved by users into corresponding semantic representations through natural language processing, match the semantic representations with the knowledge nodes in the engineering construction industry knowledge association graph, determine the matching knowledge nodes, sort the matching knowledge nodes according to the matching degree and / or importance, and query the corresponding knowledge data from the engineering construction industry knowledge base based on the sorted knowledge nodes to generate retrieval results.

[0027] Optionally, the intelligent problem-solving system for the engineering construction industry further includes:

[0028] The document encryption and authority management module is used to generate an encryption key based on the user's identity information before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results, and the user's corresponding knowledge intelligent recommendation information to the user, encrypt the data based on the encryption key, and then send the encrypted data to the user's local terminal, so that the user can obtain the encryption key through the decryption authorization process at the local terminal and then decrypt the encrypted data.

[0029] Optionally, the intelligent problem-solving system for the engineering construction industry further includes:

[0030] The innovation method fusion module is used to establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the method's application examples and guidance to the user.

[0031] Optionally, the intelligent retrieval module includes:

[0032] A vector representation generating unit, configured to generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes;

[0033] The matching unit is used to match the semantic representation with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

[0034] Optionally, the intelligent retrieval module includes:

[0035] The knowledge intelligent knowledge recommendation unit is used to predict the user's engineering construction knowledge needs based on the user's historical search record information, department information and project participation information using a preset demand prediction model, and then query the corresponding knowledge data from the engineering construction industry knowledge base based on the engineering construction knowledge needs and generate knowledge intelligent recommendation information.

[0036] Optionally, the knowledge base construction module is specifically used to classify and organize the engineering construction industry knowledge according to the engineering project stage and professional field, and establish the engineering construction industry knowledge base, wherein the engineering construction industry knowledge includes: industry standards and specifications information, construction technology and process information, design and planning information, quality management and testing information, safety management information, cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

[0037] Optionally, the document encryption and rights management module is also used to verify whether the user is in a preset whitelist before the user accesses the cloud analysis model. If so, the user's access request is approved; if not, the user's access request is rejected.

[0038] Optionally, the innovation method fusion module is also used to build an innovation method practice platform, so that the user can perform method simulation, solution design and optimization analysis based on the recommended innovation method on the innovation method practice platform to form an innovative solution.

[0039] In order to achieve the above-mentioned purpose, according to another aspect of the present invention, a computer device is also provided, including a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of intelligently solving the above-mentioned problems in the engineering construction industry are implemented.

[0040] In order to achieve the above-mentioned purpose, according to another aspect of the present invention, a computer-readable storage medium is provided, on which a computer program / instruction is stored, which, when executed by a processor, implements the steps of the intelligent solution to the above-mentioned engineering construction industry problems.

[0041] In order to achieve the above objectives, according to another aspect of the present invention, a computer program product is also provided, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned intelligent solution to the problems in the engineering construction industry.

[0042] The beneficial effects of the present invention are:

[0043] An embodiment of the present invention constructs an engineering construction industry knowledge base based on engineering construction industry knowledge, extracts knowledge and the relationship between knowledge from the engineering construction industry knowledge base, constructs an engineering construction industry knowledge association map, and then converts the engineering construction problems retrieved by users into corresponding semantic representations through natural language processing, matches the semantic representations with the knowledge nodes in the engineering construction industry knowledge association map, determines the matching knowledge nodes, sorts the matching knowledge nodes according to the matching degree and / or importance, and queries the corresponding knowledge data from the engineering construction industry knowledge base according to the sorted knowledge nodes and generates search results. In this way, technical personnel can accurately and efficiently obtain the knowledge required to solve engineering construction problems, which helps to improve the efficiency and accuracy of technical personnel in solving engineering construction problems. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0045] Figure 1 This is a flow chart of an intelligent solution to problems in the engineering construction industry according to an embodiment of the present invention;

[0046] Figure 2 This is a functional diagram of the system according to an embodiment of the present invention;

[0047] Figure 3 This is a schematic diagram of constructing a knowledge base for the engineering construction industry according to an embodiment of the present invention;

[0048] Figure 4 This is a schematic diagram of intelligent retrieval according to an embodiment of the present invention;

[0049] Figure 5 This is a schematic diagram of document security control according to an embodiment of the present invention;

[0050] Figure 6 This is a schematic diagram of the integration of innovative methods according to an embodiment of the present invention;

[0051] Figure 7 This is a structural diagram of an intelligent problem-solving system for the engineering construction industry according to an embodiment of the present invention;

[0052] Figure 8 Schematic diagram of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0054] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0055] It should be noted that the terms "including" and "having" and any variations thereof in the specification and claims of the present invention and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or are inherent to these processes, methods, products or apparatuses.

[0056] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments of the present invention can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0057] This invention addresses the challenges faced by engineering and construction companies in knowledge transfer, document confidentiality, and employee innovation. Specifically, it addresses the challenges faced by new employees in acquiring knowledge and improves knowledge retrieval efficiency; ensures the security of local enterprise documents during storage, interaction, and transmission; enhances employee innovation, promotes enterprise innovation and development, and strengthens enterprise competitiveness in the engineering and construction industry.

[0058] The present invention provides an intelligent enterprise knowledge base software system, which is mainly composed of a knowledge base construction module, an intelligent retrieval module, a document encryption and authority management module, and an innovative method fusion module. Figure 2 As shown, the main functions of the intelligent enterprise knowledge base software system of the present invention include: knowledge base construction, intelligent retrieval, document encryption and decryption verification, and innovative method application.

[0059] The knowledge base construction module is used to collect a wide range of knowledge from the engineering and construction industry, including industry standards and specifications, internal company specifications, calculations, modification notices, and historical error cases. This module utilizes established or open-source knowledge base frameworks for storage, categorizing and organizing knowledge by project phase, professional field, and other dimensions. Data mining and machine learning techniques are used to extract key information, construct a knowledge graph, and establish relationships between knowledge.

[0060] Intelligent Retrieval Module: Integrates natural language processing (NLP) technology to convert user-entered natural language queries into computer-understandable semantic representations through steps such as lexical analysis, syntactic analysis, and semantic understanding. Based on the constructed knowledge graph, it efficiently searches the knowledge base, matching the semantic representations with knowledge nodes in the knowledge graph, quickly locating relevant knowledge nodes, and ranking search results based on relevance and importance. Furthermore, based on multi-dimensional information such as the user's historical query history, department, and project participation, it leverages machine learning algorithms to predict user needs and provide intelligent recommendations.

[0061] Document Encryption and Permissions Management Module: During local document storage, documents are encrypted using the AES algorithm. A unique encryption key is generated for each document and bound to the user's identity. When interacting with the cloud-based large model, a strict whitelisting mechanism is implemented, ensuring that only specific requests that have passed enterprise security certification are whitelisted for interaction with the large model. The large model implements access control for decrypted documents based on user permissions. During document downloads, whether downloaded locally or from the cloud, documents remain encrypted, requiring repeated decryption and authorization processes when accessed from other devices.

[0062] Innovation Method Integration Module: This module digitally models innovation methods such as first principles, brainstorming, the 40 inventive principles in TRIZ theory, 76 standard solutions to physical contradictions, as well as fishbone diagrams, the Little Man method, cause-and-effect analysis, and the 5W method. An innovation method recommendation engine is integrated into the knowledge base system. When a user enters a question or searches for knowledge, the system analyzes the problem type and characteristics, selects applicable methods from the innovation method library, and recommends them to the user, providing application examples and guidance. A user-friendly innovation method practice platform is also provided, allowing users to conduct simulation analysis, design solutions, and other operations based on recommended methods. The platform records the discussion process and results and provides analytical tools to assist users in developing innovative solutions.

[0063] Figure 1 This is a flow chart of an intelligent solution to problems in the engineering construction industry according to an embodiment of the present invention. Figure 1 As shown, in one embodiment of the present invention, the intelligent solution method for engineering construction industry problems includes step S101 and step S102.

[0064] Step S101: construct an engineering construction industry knowledge base based on engineering construction industry knowledge, extract knowledge and association relationships between knowledge from the engineering construction industry knowledge base, and construct an engineering construction industry knowledge association map.

[0065] In one embodiment of the present invention, the present invention classifies and organizes the engineering construction industry knowledge according to engineering project stages and professional fields, and establishes the engineering construction industry knowledge base.

[0066] In one embodiment of the present invention, the engineering construction industry knowledge may include: industry standards and specifications information, construction technology and process information, design and planning information, quality management and inspection information, safety management information, construction cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

[0067] like Figure 3As shown, the present invention collects and organizes various knowledge in the engineering construction industry, uses a mature or open source knowledge base framework for storage, and classifies and organizes it according to dimensions such as engineering project stages and professional fields. The knowledge base covers industry standards, construction technology, design planning, quality management, safety management, cost control, project management, etc. At the same time, it contains information such as internal corporate task books, calculation books, and modification notices. After constructing the knowledge base, the present invention also uses data mining and machine learning technology to extract knowledge points and their associations from it, and establish a knowledge association map. The present invention analyzes the connections between knowledge points, such as the correspondence between a certain construction process and quality inspection standards, the impact of different management measures on cost control, etc. In this way, scattered knowledge is structured to form a clear knowledge association map.

[0068] In one embodiment of the present invention, in the construction of the knowledge graph, the present invention also explores other knowledge representation and association construction methods, such as semantic networks, to optimize the structure and retrieval performance of the knowledge graph.

[0069] Step S102: convert the engineering construction problems retrieved by the user into corresponding semantic representations through natural language processing, match the semantic representations with the knowledge nodes in the engineering construction industry knowledge association graph, determine the matching knowledge nodes, sort the matching knowledge nodes according to the matching degree and / or importance, and query the corresponding knowledge data from the engineering construction industry knowledge base according to the sorted knowledge nodes to generate search results.

[0070] like Figure 4 As shown, in the present invention, when a user searches for engineering construction related issues in the system, the system first performs an analysis, using natural language processing technology to perform lexical analysis, syntactic analysis, and semantic understanding to understand the true meaning of the problem, convert the problem into a semantic representation that the computer can understand, and match the knowledge nodes in the knowledge graph. During the matching process, the system will comprehensively consider the semantic matching degree and the importance of the knowledge points, screen out the most relevant knowledge nodes, and sort the matching results to ensure that users obtain the most valuable information first. Finally, the system extracts the corresponding knowledge data from the knowledge base and generates search results. Users can directly obtain relevant knowledge to solve the problem, thereby improving the efficiency of processing engineering construction problems.

[0071] In one embodiment of the present invention, in terms of natural language processing technology, the present invention adopts different natural language processing frameworks, such as other models based on the Transformer architecture, and may also adopt NLP technology components to achieve understanding and processing of natural language input by users.

[0072] For example: suppose a certain engineering construction company is carrying out a large-scale bridge construction project. During the project, the newly hired engineer A encountered the problem of cracks appearing during the concrete pouring process. According to the solution of the present invention, Engineer A can enter "Causes and solutions for cracks appearing during concrete pouring in large-scale bridge construction" in the search box of the intelligent enterprise knowledge base software system. The NLP technology of the intelligent retrieval module analyzes the input content, extracts key information, and then searches the knowledge base based on the engineering construction industry knowledge association map constructed by the present invention. The system quickly matches to relevant knowledge nodes, not only provides theoretical knowledge related to cracks in concrete pouring, but also associates the handling experience of previous similar projects, and displays them to Engineer A in order of matching degree and importance, so that he can quickly understand the relevant knowledge and handling experience required to solve the problem of cracks in the concrete pouring process.

[0073] It can be seen that the present invention combines natural language processing technology with knowledge graphs to achieve intelligent retrieval of knowledge bases, which can break through the limitations of traditional structured retrieval and accurately match user needs.

[0074] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0075] Based on the user's historical search record information, department information and project participation information, the preset demand prediction model is used to predict the user's engineering construction knowledge needs, and then the corresponding knowledge data is queried from the engineering construction industry knowledge base based on the engineering construction knowledge needs and knowledge intelligent recommendation information is generated.

[0076] This invention improves the efficiency of knowledge acquisition for personnel in the engineering and construction industry through intelligent recommendation capabilities. The system not only responds to direct user queries but also anticipates users' knowledge needs and proactively provides valuable information. Using machine learning models, the system combines information such as the user's historical search history, department affiliation, and project participation to predict the engineering and construction knowledge a user may need.

[0077] Training data comes from actual operational records of personnel in the engineering and construction industry, including their search keywords, knowledge points visited, project background, and job responsibilities. The model can be trained using supervised learning methods. First, a large amount of user behavior data is collected and the categories of knowledge actually acquired by users are annotated. Then, features such as query frequency, time interval, and common departmental issues are extracted to form training samples. An appropriate machine learning model, such as random forest, XGBoost, or neural network, is selected for training. The model continuously optimizes parameters to improve prediction accuracy. After training, the results are verified on a test dataset to ensure the accuracy of the recommendation results.

[0078] Based on a trained model, the system predicts in real time the knowledge points users may be interested in. It then queries the knowledge base for relevant information and generates intelligent recommendations. Recommendations include standards, construction examples, and industry experience, ensuring users can quickly access the knowledge they need and improve work efficiency.

[0079] For example: Based on Engineer A's historical search records, department, and project participation, the system intelligently recommends some of the latest research results and technical information related to bridge construction through a demand forecasting model, allowing Engineer A to quickly understand them.

[0080] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0081] Generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes;

[0082] The step S102 of matching the semantic representation with the knowledge nodes in the engineering construction industry knowledge association graph to determine the matching knowledge nodes includes:

[0083] The semantic representation is matched with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

[0084] In one embodiment of the present invention, the system calculates a vector representation for each knowledge node based on the knowledge association graph of the engineering construction industry. This vector representation is determined by both the knowledge node's own information and its associations with other knowledge nodes. First, the system extracts information such as the text description, category label, and related attributes of each knowledge node. Then, it analyzes the relationships between knowledge nodes, including references and causal relationships. This information is then subjected to feature extraction and fed into a vectorized model to generate a vector representation for each node.

[0085] In step S102, the present invention can calculate the similarity between the semantic representation and each knowledge node vector in the knowledge graph. The similarity can be calculated using cosine similarity, Euclidean distance, or dot product calculation.

[0086] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0087] Before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results, and the user's corresponding knowledge intelligent recommendation information to the user, an encryption key is generated based on the user's identity information, the data is encrypted based on the encryption key, and then the encrypted data is sent to the user's local terminal, so that the user obtains the encryption key through a decryption authorization process at the local terminal, and then decrypts the encrypted data.

[0088] like Figure 5 As shown, in one embodiment of the present invention, during the local document storage phase, the system uses the AES encryption algorithm to encrypt documents. The encryption key for each document is bound to the user's identity information. To enhance security, in addition to AES, the national encryption algorithm SM4 can also be used. This can meet different security level requirements and enhance document protection capabilities.

[0089] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0090] Before the user accesses the cloud analysis model, it is verified whether the user is in the preset whitelist. If so, the user's access request is approved; if not, the user's access request is rejected.

[0091] In one embodiment of the present invention, when users interact with a large cloud-based model, a strict whitelist mechanism is established. Only specific requests that have passed enterprise security authentication are whitelisted and allowed to interact with the large model. The large model then controls access to decrypted documents based on user permissions. For permissions management, a combination of role-based access control (RBAC) and attribute-based access control (ABAC) can be used to replace traditional permission control strategies, achieving more flexible and precise permission allocation.

[0092] In one embodiment of the present invention, during the document download process, whether downloaded from a local device or the cloud, the document always remains encrypted, and the decryption authorization process needs to be repeated when accessed by other devices.

[0093] For example, while reviewing documents, Engineer A discovered that some documents related to core technologies were encrypted. Because Engineer A has the appropriate permissions, he can access these documents normally using local decryption software and keys. If this document requires interaction with a cloud-based large model for further analysis, the system first checks whether Engineer A's request is on a whitelist. Upon confirmation, the large model provides limited analysis services based on Engineer A's permissions.

[0094] It can be seen that the present invention adopts a combination of local encryption, cloud whitelist and fine permission control to ensure the confidentiality of documents during local storage, cloud interaction and downloading.

[0095] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0096] Establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the method's application examples and guidance to the user.

[0097] In one embodiment of the present invention, the present invention digitally models innovative methods such as the first principles, brainstorming, 40 inventive principles in TRIZ theory, 76 standard solutions to physical contradictions, and fishbone diagrams, the little man method, cause-and-effect analysis, and the 5W method to establish an innovative method library.

[0098] In one embodiment, the present invention establishes standardized mathematical models and knowledge graphs for each innovative method, and combines natural language processing and machine learning technologies to achieve intelligent matching and recommendation for user-input questions. Users can simulate and apply these methods through interactive tools on the practice platform, conduct solution design and optimization analysis, and ultimately develop feasible innovative solutions.

[0099] like Figure 6 As shown, the present invention sets up an innovative method recommendation engine in the knowledge base system. When a user inputs a question or queries knowledge, the system analyzes the question type and characteristics, selects applicable methods from the innovative method library and recommends them to the user, while providing application examples and guidance.

[0100] In one embodiment of the present invention, during the digital modeling process of the innovative method, the present invention uses knowledge graph technology to perform deeper semantic modeling of the innovative method to replace the traditional encoding method, making the recommendation of the innovative method more intelligent and accurate.

[0101] In one embodiment of the present invention, the intelligent solution to the problems in the engineering construction industry of the present invention further includes:

[0102] An innovative method practice platform is built to enable the users to perform method simulation, solution design and optimization analysis based on the recommended innovative method on the innovative method practice platform to form innovative solutions.

[0103] In one embodiment of the present invention, the present invention also builds an innovative method practice platform for users, on which users can perform simulation analysis, solution design and other operations based on recommended methods. The platform records the discussion process and results, and provides analysis tools to assist users in forming innovative solutions.

[0104] In one embodiment of the present invention, for the innovative method practice platform, the present invention can adopt an open source online collaboration platform architecture to develop a practice platform with similar functions but different interaction methods to meet the usage habits of different users.

[0105] For example, for a concrete cracking problem, the Innovation Method Integration Module analyzed the problem type and recommended the "Segmentation Principle" and "Pre-operation Principle" from TRIZ theory, providing examples of their application to similar engineering problems. Engineer A initiated a discussion on the Innovation Method Practice Platform, inviting team members to participate and brainstorm ideas. The system recorded the discussion and provided analysis tools to help Engineer A organize his thoughts, ultimately leading to an innovative solution.

[0106] It can be seen that the present invention digitally models a variety of innovative methodologies and deeply integrates them with the knowledge base, providing innovative support for technical personnel through recommendation engines and practice platforms.

[0107] It can be seen from the above embodiments that the solution of the present invention achieves at least the following beneficial effects:

[0108] 1. Improved Knowledge Transfer and Retrieval Efficiency: This invention's AI-based intelligent retrieval system enables employees to quickly access knowledge using natural language, eliminating the need to learn complex search rules. This significantly improves knowledge acquisition efficiency. Compared to traditional retrieval methods, the time required to find relevant content for a specific project brief is reduced from more than ten minutes or even longer to just seconds, ensuring that new employees can quickly inherit corporate knowledge and preventing knowledge transfer gaps.

[0109] 2. Enhanced Document Confidentiality: This system utilizes advanced document encryption and strict permissions management to comprehensively safeguard enterprise document security. Local encryption prevents unauthorized access from local devices, while cloud-based whitelisting and refined permission control mitigate the risk of data breaches. Even in the event of a cyberattack, malicious requests not on the whitelist cannot decrypt documents in the cloud. Downloaded documents are always encrypted, ensuring document confidentiality during transmission and external storage.

[0110] 3. Enhanced Employee Innovation: This system deeply integrates innovation methods with a knowledge base, providing employees with innovative tools. When faced with complex engineering problems, the system recommends innovative methods that encourage employees to think outside the box and approach them from fresh perspectives. For example, during the engineering design phase, incorporating the 40 inventive principles of TRIZ theory can optimize designs, reduce costs, and improve project quality and performance. This innovative method practice platform fosters collaborative innovation within teams, stimulating employee enthusiasm and creativity.

[0111] 4. Enterprise Knowledge Management and Innovation Ecosystem Optimization: This system optimizes enterprise knowledge management processes, integrating knowledge storage, retrieval, updating, and innovation. The construction of a knowledge graph clarifies knowledge connections, facilitating comprehensive management and deep mining of knowledge assets. The application of innovative methods encourages employees to generate new knowledge and experience, which is then fed back into the knowledge base, creating a virtuous cycle of innovation and helping enterprises adapt to industry developments and maintain their leading position.

[0112] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0113] Based on the same inventive concept, an embodiment of the present invention also provides an intelligent problem-solving system for the engineering construction industry, as described in the following embodiments. Since the principle of solving problems by the intelligent problem-solving system for the engineering construction industry is similar to the intelligent solution method for the engineering construction industry, the embodiments of the intelligent problem-solving system for the engineering construction industry can refer to the embodiments of the intelligent solution method for the engineering construction industry, and the repeated parts will not be repeated. As used below, the terms "unit" or "module" can be a combination of software and / or hardware that implements predetermined functions. Although the system described in the following embodiments is preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and conceivable.

[0114] Figure 7 This is a structural diagram of the intelligent problem-solving system for the engineering construction industry according to an embodiment of the present invention. Figure 7 As shown, in one embodiment of the present invention, the intelligent problem-solving system for the engineering construction industry of the present invention includes:

[0115] The knowledge base construction module 1 is used to construct an engineering construction industry knowledge base based on engineering construction industry knowledge, and extract knowledge and the relationship between knowledge from the engineering construction industry knowledge base to construct an engineering construction industry knowledge relationship map;

[0116] The intelligent retrieval module 2 is used to convert the engineering construction problems retrieved by the user into corresponding semantic representations through natural language processing, match the semantic representations with the knowledge nodes in the engineering construction industry knowledge association map, determine the matching knowledge nodes, sort the matching knowledge nodes according to the matching degree and / or importance, and query the corresponding knowledge data from the engineering construction industry knowledge base according to the sorted knowledge nodes to generate retrieval results.

[0117] like Figure 7 As shown, in one embodiment of the present invention, the intelligent problem-solving system for the engineering construction industry of the present invention further includes:

[0118] The document encryption and authority management module 3 is used to generate an encryption key based on the user's identity information before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results and the user's corresponding knowledge intelligent recommendation information to the user, encrypt the data based on the encryption key, and then send the encrypted data to the user's local terminal, so that the user can obtain the encryption key through the decryption authorization process at the local terminal and then decrypt the encrypted data.

[0119] like Figure 7 As shown, in one embodiment of the present invention, the intelligent problem-solving system for the engineering construction industry of the present invention further includes:

[0120] The innovation method fusion module 4 is used to establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the application examples and guidance of the method to the user.

[0121] In one embodiment of the present invention, the intelligent retrieval module 2 includes:

[0122] A vector representation generating unit, configured to generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes;

[0123] The matching unit is used to match the semantic representation with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

[0124] In one embodiment of the present invention, the intelligent retrieval module 2 includes:

[0125] The knowledge intelligent knowledge recommendation unit is used to predict the user's engineering construction knowledge needs based on the user's historical search record information, department information and project participation information using a preset demand prediction model, and then query the corresponding knowledge data from the engineering construction industry knowledge base based on the engineering construction knowledge needs and generate knowledge intelligent recommendation information.

[0126] In one embodiment of the present invention, the knowledge base construction module is specifically used to classify and organize the engineering construction industry knowledge according to the engineering project stage and professional field, and establish the engineering construction industry knowledge base, wherein the engineering construction industry knowledge includes: industry standards and specifications information, construction technology and process information, design and planning information, quality management and inspection information, safety management information, cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

[0127] In one embodiment of the present invention, the document encryption and rights management module is also used to verify whether the user is in a preset whitelist before the user accesses the cloud-based analysis model. If so, the user's access request is approved; if not, the user's access request is rejected.

[0128] In one embodiment of the present invention, the innovation method fusion module is also used to build an innovation method practice platform, so that the user can perform method simulation, solution design and optimization analysis based on the recommended innovation method on the innovation method practice platform to form an innovative solution.

[0129] In order to achieve the above object, according to another aspect of the present application, a computer device is also provided. Figure 8 As shown, the computer device includes a memory, a processor, a communication interface and a communication bus. The memory stores a computer program that can be run on the processor. When the processor executes the computer program, the steps in the above embodiment method are implemented.

[0130] The processor may be a central processing unit (CPU). The processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or a combination of the above chips.

[0131] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and units, such as the corresponding program units in the above-described method embodiments of the present invention. The processor executes the non-transitory software programs, instructions, and modules stored in memory to perform various processor functions and work data processing, thereby implementing the methods in the above-described method embodiments.

[0132] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the processor, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0133] The one or more units are stored in the memory, and when executed by the processor, perform the method in the above embodiment.

[0134] The specific details of the above-mentioned computer device can be understood by referring to the corresponding descriptions and effects in the above-mentioned embodiments, and will not be repeated here.

[0135] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a computer-readable storage medium is further provided, wherein the computer-readable storage medium stores a computer program, and the computer program implements the steps in the intelligent solution to the above-mentioned engineering construction industry problems when executed in a computer processor. Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, which, when executed, may include the processes of the embodiments of the above-mentioned methods. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), a random access memory (RAM), a flash memory (Flash Memory), a hard disk (Hard Disk Drive, abbreviated as: HDD) or a solid-state drive (SSD), etc.; the storage medium can also include a combination of the above-mentioned types of memories.

[0136] In order to achieve the above-mentioned purpose, according to another aspect of the present application, a computer program product is also provided, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-mentioned intelligent solution to the problems in the engineering construction industry.

[0137] Obviously, those skilled in the art will appreciate that the modules or steps of the present invention described above can be implemented using a general-purpose computing device. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they can be implemented using program code executable by a computing device, which can then be stored in a storage device and executed by the computing device. Alternatively, they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.

[0138] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An intelligent solution to problems in the engineering construction industry, characterized by: include: Building an engineering construction industry knowledge base based on engineering construction industry knowledge, and extracting knowledge and the relationship between knowledge from the engineering construction industry knowledge base to build an engineering construction industry knowledge relationship map; Through natural language processing, the engineering construction problems retrieved by users are converted into corresponding semantic representations, and the semantic representations are matched with the knowledge nodes in the engineering construction industry knowledge association graph to determine the matching knowledge nodes. The matching knowledge nodes are sorted according to the matching degree and / or importance, and the corresponding knowledge data are queried from the engineering construction industry knowledge base based on the sorted knowledge nodes to generate search results.

2. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: Also includes: Before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results, and the user's corresponding knowledge intelligent recommendation information to the user, an encryption key is generated based on the user's identity information, the data is encrypted based on the encryption key, and then the encrypted data is sent to the user's local terminal, so that the user obtains the encryption key through a decryption authorization process at the local terminal, and then decrypts the encrypted data.

3. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: Also includes: Establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the method's application examples and guidance to the user.

4. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: Also includes: Generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes; The matching of the semantic representation with the knowledge nodes in the engineering construction industry knowledge association graph to determine the matching knowledge nodes includes: The semantic representation is matched with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

5. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: Also includes: Based on the user's historical search record information, department information and project participation information, the preset demand prediction model is used to predict the user's engineering construction knowledge needs, and then the corresponding knowledge data is queried from the engineering construction industry knowledge base based on the engineering construction knowledge needs and knowledge intelligent recommendation information is generated.

6. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: The construction industry knowledge base is constructed based on the construction industry knowledge, including: The engineering construction industry knowledge is classified and organized according to the engineering project stages and professional fields to establish the engineering construction industry knowledge base, wherein the engineering construction industry knowledge includes: industry standards and specifications information, construction technology and process information, design and planning information, quality management and testing information, safety management information, cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

7. The intelligent solution to engineering construction industry problems according to claim 1 is characterized in that: Also includes: Before the user accesses the cloud analysis model, it is verified whether the user is in the preset whitelist. If so, the user's access request is approved; if not, the user's access request is rejected.

8. The intelligent solution to engineering construction industry problems according to claim 3 is characterized by: Also includes: An innovative method practice platform is built to enable the users to perform method simulation, solution design and optimization analysis based on the recommended innovative method on the innovative method practice platform to form innovative solutions.

9. An intelligent problem-solving system for the engineering construction industry, characterized by: include: A knowledge base construction module is used to construct an engineering construction industry knowledge base based on engineering construction industry knowledge, and to extract knowledge and the relationship between knowledge from the engineering construction industry knowledge base to construct an engineering construction industry knowledge relationship map; The intelligent retrieval module is used to convert the engineering construction problems retrieved by users into corresponding semantic representations through natural language processing, match the semantic representations with the knowledge nodes in the engineering construction industry knowledge association graph, determine the matching knowledge nodes, sort the matching knowledge nodes according to the matching degree and / or importance, and query the corresponding knowledge data from the engineering construction industry knowledge base based on the sorted knowledge nodes to generate retrieval results.

10. The intelligent problem-solving system for the engineering construction industry according to claim 9 is characterized in that: Also includes: The document encryption and authority management module is used to generate an encryption key based on the user's identity information before sending the documents queried by the user from the engineering construction industry knowledge base, the user's search results, and the user's corresponding knowledge intelligent recommendation information to the user, encrypt the data based on the encryption key, and then send the encrypted data to the user's local terminal, so that the user can obtain the encryption key through the decryption authorization process at the local terminal and then decrypt the encrypted data.

11. The intelligent problem-solving system for the engineering construction industry according to claim 9 is characterized in that: Also includes: The innovation method fusion module is used to establish an innovation method library, analyze the user's input questions and queried knowledge according to a preset innovation method recommendation engine, screen out recommended innovation methods from the innovation method library, and send the recommended innovation method and the method's application examples and guidance to the user.

12. The intelligent problem-solving system for the engineering construction industry according to claim 9 is characterized in that: The intelligent retrieval module includes: A vector representation generating unit, configured to generate a vector representation corresponding to each knowledge node based on the node information of each knowledge node in the engineering construction industry knowledge association graph and the association information between the knowledge nodes; The matching unit is used to match the semantic representation with the vector representation corresponding to each of the knowledge nodes to determine the matching knowledge nodes.

13. The intelligent problem-solving system for the engineering construction industry according to claim 9 is characterized in that: The intelligent retrieval module includes: The knowledge intelligent knowledge recommendation unit is used to predict the user's engineering construction knowledge needs based on the user's historical search record information, department information and project participation information using a preset demand prediction model, and then query the corresponding knowledge data from the engineering construction industry knowledge base based on the engineering construction knowledge needs and generate knowledge intelligent recommendation information.

14. The intelligent problem-solving system for the engineering construction industry according to claim 9 is characterized in that: The knowledge base construction module is specifically used to classify and organize the engineering construction industry knowledge according to the engineering project stage and professional field, and establish the engineering construction industry knowledge base, wherein the engineering construction industry knowledge includes: industry standards and specifications information, construction technology and process information, design and planning information, quality management and testing information, safety management information, construction cost and cost management information, engineering progress and project management information, engineering cases and experience information, internal enterprise task books, calculation books and modification notices.

15. The intelligent problem-solving system for the engineering construction industry according to claim 10, characterized in that: The document encryption and rights management module is also used to verify whether the user is in a preset whitelist before the user accesses the cloud analysis model. If so, the user's access request is approved; if not, the user's access request is rejected.

16. The intelligent problem-solving system for the engineering construction industry according to claim 11, characterized in that: The innovation method fusion module is also used to build an innovation method practice platform, so that the user can perform method simulation, solution design and optimization analysis based on the recommended innovation method on the innovation method practice platform to form an innovative solution.

17. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

18. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

19. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

Images