Intelligent construction application resource integrated display and management system based on knowledge graph

Abstract

The invention discloses an intelligent construction application resource integrated display and management system based on a knowledge graph. The system comprises a data layer, a bottom knowledge graph construction layer and a top knowledge graph display layer, the data layer is used for storing data of each stage of the intelligent construction project, and the data comprises current data and historical data; the bottom-layer knowledge graph construction layer constructs and stores a bottom-layer knowledge graph in a graph structure form; the top knowledge graph display layer determines a to-be-displayed graph based on user input, the to-be-displayed graph is a sub-graph of the graph structure, the to-be-displayed graph is mapped into a top knowledge graph, the top knowledge graph is displayed to a user, and the top knowledge graph is a graphical graph. The method can flexibly express complex relations, adapts to rapid changes and supports multi-dimensional information integration and display.

Description

Technical Field

[0001] The present invention relates to the field of intelligent construction technology in the construction industry, and specifically to an intelligent construction application resource integrated display and management system based on a knowledge graph. Background Art

[0002] Knowledge management systems play a vital role in many fields, especially in the field of intelligent construction, which requires processing of large amounts of information and knowledge. In the field of intelligent construction, current knowledge management systems are usually constructed in a tree structure, relying on a tree structure to organize and present information. This approach simplifies the information classification and retrieval process to a certain extent, but it has limitations.

[0003] Tree-structured knowledge management systems, such as Confluence and Notion, provide a hierarchical way to organize pages, documents, and data. Users can quickly find the information they need through the defined directory structure. For example, a construction project may be classified into different stages in the system, such as the survey and planning stage, the design stage, and the construction stage. Each stage can be further divided into more specific tasks or documents. The intuitiveness and ease of use of this method make the tree structure the first choice for many knowledge management systems.

[0004] However, with the rapid development of intelligent construction, the life cycle of project construction has become more and more complex, involving more and more technologies, tasks and resources. In this context, the tree structure method of displaying and managing knowledge has begun to show its limitations:

[0005] Static: Tree structures are difficult to adapt to rapidly changing knowledge and information needs. Once established, it becomes cumbersome to modify and update the structure, especially when project requirements change frequently. In smart construction projects, new technologies and methods are constantly emerging, and project requirements and schedules are constantly changing. Static knowledge structures cannot flexibly adapt to these changes, causing the knowledge base to quickly become outdated and unable to effectively support the actual needs of project management.

[0006] Single dimension: The tree structure supports a single hierarchical relationship and is limited in expressing multi-dimensional associations and dependencies, which is a significant shortcoming in intelligent construction projects that integrate multiple technologies and manage multiple stages. In fact, there are complex multi-dimensional relationships between knowledge and resources in the field of intelligent construction. For example, the same technology may serve multiple project stages at the same time, and existing technologies find it difficult to effectively express and manage such cross-dimensional associations.

[0007] Information islands: In a tree structure, related information may be scattered in different branches, and users need to jump between multiple levels to get a complete view, which not only reduces efficiency but also increases the complexity of understanding.

[0008] Difficulty in knowledge sharing and collaboration: In a tree structure, knowledge sharing and collaboration are usually limited to information within the same branch or level. For cross-domain and cross-departmental smart construction projects, this structure obviously cannot meet the needs of efficient sharing and utilization of knowledge among cross-professional teams.

[0009] In summary, the tree structure mainly used in the prior art has limitations in many aspects. These limitations not only affect the efficiency of information retrieval, but also limit the ability of knowledge management systems to process complex and multi-dimensional information.

[0010] Therefore, in the field of intelligent construction, the complexity of the project is not only reflected in its multi-stage characteristics, but also in the diversity and interdependence of the technologies, tasks and resources involved in each stage. Therefore, a system that can flexibly express complex relationships, adapt to rapid changes and support multi-dimensional information integration is needed. Summary of the invention

[0011] In view of this, the present invention provides an intelligent construction application resource integrated display and management system based on knowledge graph, which can solve the technical problems of the static structure limitations of the prior art, insufficient expression ability of a single dimension, the existence of information islands, and the difficulty in knowledge sharing and collaboration.

[0012] In order to solve the above technical problems, the present invention is implemented as follows.

[0013] An intelligent construction application resource integrated display and management system based on knowledge graph, the system comprising:

[0014] Data layer, bottom knowledge graph construction layer, top knowledge graph display layer;

[0015] The data layer is used to store data of each stage of the intelligent construction project, including current data and historical data;

[0016] The underlying knowledge graph construction layer constructs and stores the underlying knowledge graph in the form of a graph structure; the underlying knowledge graph is constructed in the following manner: entities are extracted from the data layer, and project phases, technical requirements, and project-specified work processes are used as first-type entities of the underlying knowledge graph; construction processes, management specifications, and quality standards are used as second-type entities of the underlying knowledge graph; historical data or user-input technical parameters, work implementation processes, and management plans are used as third-type entities; there is a multi-dimensional association relationship between the first-type entity and the second-type entity; the relationship between the entities is obtained from the data layer; and the technical points, preconditions, and outputs related to the entity are used as attributes of the entity;

[0017] The top-level knowledge graph display layer determines the graph to be displayed based on user input, the graph to be displayed is a subgraph of the graph structure, maps the graph to be displayed to the top-level knowledge graph, and displays the top-level knowledge graph to the user, the top-level knowledge graph is a graphical graph.

[0018] Preferably, the underlying knowledge graph construction layer obtains various documents, specifications, standards and actual operation data related to historical intelligent construction projects, classifies the various documents, specifications, standards and actual operation data obtained according to the various stages of the intelligent construction projects, and then extracts technical parameters, operation implementation processes, and management plans from the classification results as third-type entities; the underlying knowledge graph construction layer obtains the technical parameters, operation implementation processes, and management plans input by the user through an extended interface, and regards the technical parameters, operation implementation processes, and management plans input by the user as third-type entities; in the graph structure, the third-type entities are identified as knowledge nodes for storage.

[0019] Preferably, the underlying knowledge graph includes a fourth type of entity, which is an entity of other types other than the first type of entity, the second type of entity, and the third type of entity, including user evaluations, labels, case resources, training resources, and manufacturer information of products; in the underlying knowledge graph, a relationship between the fourth type of entity and other types of entities is established.

[0020] Preferably, in the underlying knowledge graph, each project stage, technical requirement, project-specified work process, construction technology, management specifications, quality standards, technical parameters, work implementation process, and management plan are defined as nodes. When there are multiple nodes with exactly the same content, the nodes with exactly the same content in different positions in the project are distinguished by associating other nodes. By establishing an inheritance relationship or a reuse relationship, and then performing mapping and normalization processing, the consistency of the nodes with exactly the same content is ensured.

[0021] Preferably, the relationship is divided into two categories: static relationship and dynamic relationship, wherein the static relationship is used to characterize the association relationship between entities, and the dynamic relationship is used to characterize the dynamic updated relationship between entities; the first type entity has a static relationship with the second type entity, and the third type entity, as a knowledge node, has a static relationship and / or a dynamic relationship with the first type entity and the second type entity; multiple entities of the same type have dynamic or static relationships; the static relationship includes dependency relationship, attribution relationship, and compatibility relationship; the dynamic relationship is used to represent the dynamically updated relationship between entities, and the dynamic relationship includes change relationship, priority adjustment relationship, reuse relationship, and inheritance relationship.

[0022] Preferably, the top-level knowledge graph display layer determines the graph to be displayed based on user input, and the graph to be displayed is a subgraph of the graph structure, including:

[0023] According to the user input, the term or concept of the user query is determined, and in the underlying knowledge graph, the graph of the user's needs is determined; wherein all entity nodes and their attributes related to the term or concept, as well as the direct and indirect relationships between all entity nodes related to the term or concept, are obtained as the graph of the user's needs;

[0024] Determine all first entities that have a direct relationship with entities included in the graph of user needs, and then determine all second entities that have a direct relationship with each of the first entities;

[0025] The entities included in the graph of user needs, the first total entities, and the second total entities constitute an entity set, and the graph to be displayed is composed of each entity in the entity set and the attributes of each entity, and the relationship between each entity in the entity set.

[0026] Preferably, the user provides new information through the extension interface provided by the top-level knowledge graph, where the new information is new knowledge or resource information, and stores the new information in the data layer, which is then updated by the underlying knowledge graph construction layer.

[0027] Through the knowledge graph technology, the present invention overcomes the many challenges faced by existing tree-structured knowledge management systems in the field of intelligent construction, such as static structure, insufficient expression ability of a single dimension, information island problems, and difficulty in knowledge sharing and collaboration. The intelligent construction application resource integrated display and management system based on the knowledge graph provides users with a dynamic, multi-dimensional, highly visual and highly interactive platform, which greatly improves the efficiency, accuracy and ease of use of knowledge management in the field of intelligent construction, thereby supporting more efficient and accurate project decision-making and management.

[0028] Beneficial technical effects brought by the present invention:

[0029] (1) The purpose of the knowledge graph-based intelligent construction application resource integrated display and management system proposed in this invention is to flexibly express complex relationships, adapt to rapid changes, and support multi-dimensional information integration and display. By adopting the knowledge graph as the core data structure, this system aims to provide a new method to organize, manage and display complex information and knowledge in the field of intelligent construction, overcome the limitations of existing tree-structured knowledge management systems, and achieve more efficient and flexible knowledge management and information retrieval.

[0030] (2) The system of the present invention is dynamic and flexible. By using the knowledge graph as the core data structure, the system can flexibly adapt to the rapid changes in the field of intelligent construction. The knowledge graph allows the dynamic addition and modification of nodes and relationships, so that the latest technologies, methods and requirements in intelligent construction projects can be reflected in a timely manner.

[0031] (3) The system of the present invention can integrate and express multi-dimensional information. The knowledge graph supports the expression of multi-dimensional relationships and can effectively capture and manage the complex relationships between technologies, tasks and resources in the field of intelligent construction. This not only improves the accuracy and efficiency of information retrieval, but also provides more comprehensive and in-depth knowledge support for project management and decision-making.

[0032] (4) The system of the present invention can improve the efficiency of information retrieval and utilization. Query and analysis based on the knowledge graph can quickly locate relevant information, reduce the need for users to jump between different information, and significantly improve the efficiency of knowledge retrieval and utilization. In addition, through the graph view, users can intuitively see the connection between different knowledge points and more easily understand the contextual relationship of complex information.

[0033] (5) The system of the present invention can promote knowledge sharing and collaboration. The system architecture design based on the knowledge graph supports more efficient cross-domain and cross-departmental knowledge sharing and collaboration. Knowledge points and resources are no longer limited to a single level or branch, but are integrated and connected through multi-dimensional relationships, making it easier for cross-professional teams to access and utilize the required knowledge and information, thereby promoting communication and collaboration efficiency between project teams.

[0034] (6) The system of the present invention can support highly customized knowledge management. The structure based on the knowledge graph enables the system to provide highly customized knowledge management services. Project managers can customize the structure and content of the knowledge graph according to the specific needs and characteristics of the project, including defining specific node types, relationship types, and attributes, thereby ensuring that the knowledge management system can accurately serve the actual needs of the project.

[0035] (7) The system of the present invention can improve the visualization and interactivity of knowledge. The knowledge graph can not only effectively store and manage knowledge, but also provide a more intuitive and dynamic knowledge interaction method through the visualization of the graph. This visual representation makes the complex knowledge structure and relationship clear at a glance. Users can easily explore and discover the deep connections between knowledge through intuitive interface operations, such as clicking and dragging nodes.

[0036] (8) The system of the present invention can enhance the timeliness and accuracy of knowledge. By updating the information in the knowledge graph in real time, the present invention ensures that the knowledge stored in the system is always the latest and most accurate. This is particularly important in the field of intelligent construction, because the knowledge and technology in this field are updated rapidly, and project managers need to rely on the latest information to make correct decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 A schematic diagram of the structure of the intelligent construction application resource integrated display and management system based on the knowledge graph provided by the present invention;

[0038] Figure 2 Schematic diagram of the effect of the intelligent construction application resource integrated display and management system based on the knowledge graph provided by the present invention. DETAILED DESCRIPTION

[0039] The present invention is described in detail below in conjunction with the accompanying drawings and embodiments.

[0040] like Figure 1 As shown, the present invention proposes an intelligent construction application resource integrated display and management system based on knowledge graph, and the system includes the following from bottom to top:

[0041] Data layer, bottom knowledge graph construction layer, top knowledge graph display layer;

[0042] The data layer is used to store data of each stage of the intelligent construction project, including current data and historical data;

[0043] The underlying knowledge graph construction layer constructs and stores the underlying knowledge graph in the form of a graph structure; the underlying knowledge graph is constructed in the following manner: entities are extracted from the data layer, and project phases, technical requirements, and project-specified work processes are used as first-type entities of the underlying knowledge graph; construction processes, management specifications, and quality standards are used as second-type entities of the underlying knowledge graph; historical data or user-input technical parameters, work implementation processes, and management plans are used as third-type entities; there is a multi-dimensional association relationship between the first-type entity and the second-type entity; the relationship between the entities is obtained from the data layer; and the technical points, preconditions, and outputs related to the entity are used as attributes of the entity;

[0044] The top-level knowledge graph display layer determines the graph to be displayed based on user input, the graph to be displayed is a subgraph of the graph structure, maps the graph to be displayed to the top-level knowledge graph, and displays the top-level knowledge graph to the user, the top-level knowledge graph is a graphical graph.

[0045] The data of each stage include the construction technology, technical requirements, project-specified operating procedures, management specifications, quality standards, user evaluations, labels, case resources, training resources, and product manufacturer information involved in each stage; the labels are used to identify knowledge and / or products; the case resources are case resources related to knowledge and / or products.

[0046] In the present invention, the field of intelligent construction contains a rich business language, covering all stages of the entire life cycle from the initial planning and design of the project to construction, operation and maintenance. Each stage has its own unique technical requirements, work processes and management methods. Converting these business languages ​​into content in the knowledge graph is a key step in building an integrated display and management system for intelligent construction application resources. The present invention classifies data into different types of data, and then divides the data into different types of entities by type, which is convenient for simplifying the processing of massive data in the field of intelligent construction and can improve the processing speed. The present invention abstracts and classifies business languages: First, it is necessary to conduct in-depth analysis and abstraction of the business language in the field of intelligent construction, and classify it into different nodes and relationships. For example, the life cycle of a project construction can be divided into multiple stages such as survey planning, design, bidding and entry, deepening production, construction, completion delivery, full process management, operation and maintenance management, and special applications, and each stage is further subdivided into specific technology or task nodes.

[0047] Furthermore, the underlying knowledge graph construction layer obtains various documents, specifications, standards and actual operation data related to historical intelligent construction projects, classifies the obtained various documents, specifications, standards and actual operation data according to the various stages of the intelligent construction projects, and then extracts technical parameters, operation implementation processes, and management plans from the classification results as third-type entities; the underlying knowledge graph construction layer obtains the technical parameters, operation implementation processes, and management plans input by the user through the extended interface, and regards the technical parameters, operation implementation processes, and management plans input by the user as third-type entities; in the graph structure, the third-type entities are identified as knowledge nodes for storage.

[0048] In the underlying knowledge graph, each project phase, technical requirement, project-specified work process, construction technology, management specifications, quality standards, technical parameters, work implementation process, and management plan are defined as nodes. When there are multiple nodes with exactly the same content, the nodes with exactly the same content are distinguished in different positions in the project by associating other nodes. The consistency of nodes with exactly the same content is ensured by establishing inheritance or reuse relationships, and then performing mapping and normalization processing. For example, for nodes that are at different stages but have the same technical requirements or project-specified work processes, consistency and comparability are achieved by establishing mapping relationships and normalization processing.

[0049] Furthermore, the underlying knowledge graph includes a fourth type of entity, which is an entity other than the first type of entity, the second type of entity, and the third type of entity, including user evaluations, tags, case resources, training resources, and manufacturer information of products. In the underlying knowledge graph, a relationship between the fourth type of entity and other types of entities is established.

[0050] In the present invention, products, cases, training resources, supporting resources, manufacturers, service resources, and procurement resources exist as separate entities. They are combined with knowledge nodes in the knowledge graph in a many-to-many manner. A knowledge node can have multiple products, cases, training resources, etc. A product can be associated with multiple knowledge nodes, and a product can have multiple cases, training resources, etc. Cases, training resources, supporting resources, service resources, and procurement resources are combined with multiple other entity resources in the same way as products.

[0051] Furthermore, the relationship includes static relationship and dynamic relationship, wherein static relationship is used to characterize association relationship between entities, and dynamic relationship is used to characterize dynamic relationship between entities. The dynamic relationship is used to represent dynamically updated relationship between entities. The first type entity has a static relationship with the second type entity, and the third type entity, as a knowledge node, has a static relationship and / or a dynamic relationship with the first type entity and the second type entity; multiple entities of the same type have dynamic or static relationships; the static relationship includes dependency relationship, attribution relationship, and compatibility relationship; the dynamic relationship is used to represent dynamically updated relationship between entities, and the dynamic relationship includes change relationship, priority adjustment relationship, reuse relationship, and inheritance relationship.

[0052] In the graph structure, each project stage, key technical parameter, operation process, and management plan are defined as a node, and the logical relationship and dependency between nodes are represented by edges. For example, a specific construction task node may need to rely on certain design results nodes, and this dependency will be reflected in the graph through edges. Each node not only contains basic information about the business concept, but can also be associated with richer attributes and metadata, such as application profile, key points, preconditions, outputs, etc. These attributes provide detailed content richness for the knowledge graph, enabling the system to provide more accurate and comprehensive information services.

[0053] In the mapping process of the knowledge graph to the graph structure, the key stages and important technical components in the project that can be further subdivided into key technical parameters, operating processes or key solution conditions are regarded as non-leaf nodes, and the key technical parameters, operating processes or key solutions that meet the specific operation points in the project implementation and no longer have subordinate subdivisions or whose subordinate subdivisions are not the key conditions that the project needs to pay attention to are regarded as leaf nodes; multiple nodes that meet the technical requirements, operating processes and key solution conditions that are common across multiple project stages or multiple technical components are regarded as nodes with inheritance relationships; multiple nodes that meet the standardized operations, general solutions or best practices that are repeatedly applied or referenced in different project stages or technical components are regarded as nodes with reuse relationships.

[0054] In the present invention, in the intelligent construction application resource integrated display and management system, technologies or tasks that can be further split are defined as non-leaf nodes, while specific technologies or tasks that cannot be further split are defined as leaf nodes. This division helps to clearly express the complex business structure and technical system in the field of intelligent construction. In actual intelligent construction projects, the same technology or resource is often reused in different stages or tasks. The knowledge graph effectively solves this problem by supporting multiple inheritance and reuse of nodes, while also avoiding information duplication and redundancy. The above-mentioned knowledge graph construction rules are essentially a hierarchical construction rule, which is the key to ensuring that the information structure is reasonable, easy to manage and retrieve.

[0055] The graph structure of the underlying knowledge graph is a framework for connecting and organizing knowledge in the field of intelligent construction, and its implementation method directly affects the performance of the system and user experience.

[0056] In the intelligent construction application resource integrated display and management system, nodes not only represent specific technologies, tasks or resources in the field of intelligent construction, but also include detailed information related to them, such as user evaluation, tags, case resources, training resources, manufacturer information, etc. This design makes each node an information aggregation point, providing a rich perspective from overview to details.

[0057] In the intelligent construction application resource integrated display and management system, edges not only represent static relationships between nodes, such as dependency and ownership, but also dynamic and conditional relationships, such as the sequence of processes, conditional triggering, etc. This design enables the knowledge graph to flexibly reflect the complex and ever-changing business logic and workflow in the field of intelligent construction.

[0058] In terms of graph storage and query, in order to support large-scale knowledge graphs, choosing the right graph database technology is the key. Graph databases can efficiently store and manage a large number of nodes and edges, while providing powerful graph query and analysis functions, supporting complex graph traversal, pattern matching and other operations, ensuring high system performance and good user experience.

[0059] The present invention deeply integrates various application resources and services (such as design tools, construction management software, training resources, etc.) into the system. Through the knowledge graph, these resources are associated with relevant knowledge points, project stages, etc.

[0060] Furthermore, the top-level knowledge graph display layer determines a graph to be displayed based on user input, and the graph to be displayed is a subgraph of the graph structure, including:

[0061] According to the user input, the term or concept of the user query is determined, and in the underlying knowledge graph, the graph of the user's needs is determined; wherein all entity nodes and their attributes related to the term or concept, as well as the direct and indirect relationships between all entity nodes related to the term or concept, are obtained as the graph of the user's needs;

[0062] Determine all first entities that have a direct relationship with entities included in the graph of user needs, and then determine all second entities that have a direct relationship with each of the first entities;

[0063] The entities included in the graph of user needs, the first total entities, and the second total entities constitute an entity set, and the graph to be displayed is composed of each entity in the entity set and the attributes of each entity, and the relationship between each entity in the entity set.

[0064] In the present invention, in order to cut out relevant subgraphs from the huge underlying knowledge graph, the system uses intelligent filtering and clustering algorithms to determine the boundaries. First, based on the user's input, the system searches and identifies entity nodes directly related to the query term in the underlying knowledge graph, which constitute the core part of the subgraph.

[0065] Next, the system analyzes the association rules and business logic between nodes to identify neighboring nodes that are directly related to the core node. These nodes and their relationships constitute the first-level boundary of the subgraph. Then, based on the set association depth and business needs, the system further expands the search scope to find other nodes that are indirectly related to the neighboring nodes, forming the second-level boundary of the subgraph.

[0066] In this way, it is possible to identify technologies and resources that are reused in different project phases or tasks, and ensure that these nodes are properly represented and linked in the subgraph through multiple inheritance and reuse mechanisms.

[0067] Finally, the system presents this knowledge subgraph with clear boundaries to the user in the form of a graphical network. The user can further explore the content of the subgraph through an interactive interface, such as zooming in to view detailed information of a specific node, or tracing to other related nodes along the path of the relationship. This intelligent subgraph cropping and display mechanism not only improves the efficiency of user knowledge retrieval, but also makes complex knowledge structures easier to understand and operate.

[0068] Furthermore, mapping the graph to be displayed into a top-level knowledge graph includes:

[0069] According to the mapping rules, the graph to be displayed is mapped to the top-level knowledge graph, and the mapping rules are:

[0070] For each entity in the display diagram, perform the following actions according to the construction project stage it corresponds to:

[0071] For entities in the design stage, they are given a blue highlight to indicate conceptual and theoretical nature;

[0072] For entities in the construction phase, yellow markings are used to indicate actual operations and execution;

[0073] For entities in the operation phase, green is used to symbolize maintenance and ongoing performance.

[0074] For relationships between entities, depending on their type, do the following:

[0075] For dependency relationships, dashed arrows are added to indicate the direction and degree of dependency.

[0076] Furthermore, the static relationship also includes resource allocation relationship. For resource allocation relationship, a solid line with an icon (for example, a labor icon or a material icon) is used to clarify the resource type; for dependency relationship, the project progress is emphasized by marking a sequential number or a timestamp next to the edge.

[0077] The dynamic relationship also includes progress update relationship and condition trigger relationship. For progress update relationship, pulse effect or dynamic progress bar is used to reflect the state change in real time; for condition trigger relationship, condition icon (such as traffic light icon) is used to indicate whether the trigger condition is met.

[0078] In the present invention, the top-level knowledge graph is displayed to the user, that is, the entities, attributes and relationships corresponding to the graph to be displayed are displayed with visual elements, such as graphics, colors, lines, etc. In the present invention, for example, products, cases, training resources, supporting resources, manufacturers, service resources, and procurement resources that have relationships with entities in each stage are displayed, and the specific display view is divided into two parts. The first part displays a certain stage in the form of a mind map, and the second part, which is independent of the mind map, displays products, cases, training resources, supporting resources, manufacturers, service resources, and procurement resources that have relationships with the stage in visual forms such as pictures, links, texts, and videos. The user clicks on the node of the mind map in the first part as the user input to determine the term queried by the user. The first part displays the entity corresponding to the term, and the second part displays the products, cases, training resources, supporting resources, manufacturers, service resources, and procurement resources that have relationships with the entity corresponding to the term. When the user switches different nodes in one part, the second part is synchronously displayed in linkage.

[0079] In the present invention, the relationship between nodes and the attributes of nodes are effectively expressed through the following methods:

[0080] Labels and text: Display text labels next to nodes, providing the name or a brief description of the node. For relationships, you can add text labels next to the connecting line to describe the specific relationship between the two nodes, such as "supported by", "complying with standards", etc.

[0081] Interactive operation: Allow users to obtain more information through interactive operations. For example, users can click a node to pop up a window or panel to display detailed information about the node, such as a list of properties, associated documents, and history records.

[0082] Multi-level display: For complex relationships, you can design a multi-level display method. For example, the main relationship can be displayed directly in the map, while the secondary or complex relationship can be displayed through additional interfaces or views when the user requests it.

[0083] Filtering and Searching: Provides powerful filtering and searching capabilities, allowing users to find specific nodes and relationships based on keywords, attribute values, or other conditions, thereby quickly locating information of interest.

[0084] Context-sensitive tooltips: When the user hovers the mouse over a node or relationship, the system can provide context-sensitive tooltips, such as the definition of the node, its relationship with other nodes, etc.

[0085] Special mapping rules and processing methods: For the particularities of the intelligent construction field, such as multi-stage management, cross-disciplinary collaboration, etc., the system also needs to design special mapping rules and processing methods. For example, different colors or shapes can be used to distinguish technical nodes at different stages, or dynamic elements can be used to indicate project progress and status changes.

[0086] Furthermore, the user provides new information through the extension interface provided by the top-level knowledge graph, where the new information is new knowledge or resource information, and stores the new information in the data layer, which is then updated by the underlying knowledge graph construction layer.

[0087] With the advancement of intelligent construction projects and the application of new technologies, knowledge graphs need to be continuously updated and maintained. The intelligent construction application resource integration display and management system based on knowledge graphs provides convenient tools and interfaces to support knowledge managers to dynamically add, modify or delete nodes and relationships in the knowledge graph according to the actual situation of the project.

[0088] The present invention adopts knowledge graph to organize and manage knowledge and resources in the field of intelligent construction. Compared with traditional tree-like or tabular data structures, knowledge graph can more naturally and flexibly represent complex relationships between entities, such as multi-dimensional dependencies, associations and aggregation relationships. The effective management of such complex relationships is an important innovation of the present invention. The present invention not only focuses on the organization and management of knowledge, but also strives to deeply integrate various application resources and services (such as design tools, construction management software, training resources, etc.) into the system. Through the knowledge graph, these resources are associated with relevant knowledge points, project stages, etc. to achieve efficient utilization and sharing of resources. This deep integration strategy is another innovation of the present invention. The present invention provides users with an intuitive multi-dimensional view through the visual display of the knowledge graph, and supports users to interactively explore and analyze through a graphical interface. This visual interaction not only improves the user experience, but also makes complex information and relationships easier to understand and manage. The innovative application of visualization technology, especially in supporting complex data analysis and interactive design, is also an innovation of the present invention.

[0089] As a widely used knowledge management and collaboration tool, Confluence has won the favor of many enterprises and organizations with its powerful document editing and team collaboration functions. However, when faced with the specific needs of the intelligent construction field, Confluence's traditional document center and tree structure organization method show certain limitations. The knowledge graph-based intelligent construction application resource integrated display and management system of the present invention provides significant technical advantages in many key aspects. The following are its main advantages compared with Confluence:

[0090] Expression and management of multi-dimensional relationships: The knowledge and information involved in the field of intelligent construction are extremely complex, involving not only a large number of technologies, processes and resources, but also the intricate relationships between these elements. Confluence organizes information through a tree structure, which has limitations in expressing multi-dimensional and complex relationships. The knowledge graph technology used in this system can naturally and flexibly represent and manage these multi-dimensional relationships, providing users with a richer and more comprehensive information view.

[0091] Visualization and interaction of knowledge: Although Confluence provides a wealth of document typesetting and display functions, it is still limited in intuitively displaying complex information and knowledge systems. The knowledge graph visualization of this system not only makes complex knowledge structures and relationships clear at a glance, but also provides a wealth of interactive operations, such as graph navigation, node search, relationship exploration, etc., which greatly improves the user experience and operation efficiency.

[0092] Customized functions for smart construction: As a general knowledge management tool, Confluence has good flexibility and configurability, but it may not be sufficient to meet the unique needs of the smart construction field. Based on the actual situation of smart construction, this system provides targeted functions and tools, such as project progress monitoring, automatic classification and annotation of professional and technical knowledge, and integration with construction software, providing a more tailored solution for the specific needs of smart construction projects.

[0093] The technical solution of the present invention lies in its unique design concept and implementation method, which provides a brand-new solution for knowledge management and resource integration in the field of intelligent construction.

[0094] The present invention provides an information structure design based on a knowledge graph: compared with the traditional tree structure, the design based on the knowledge graph can more flexibly express and manage the multi-dimensional relationships between complex technologies, tasks and resources in the field of intelligent construction.

[0095] The present invention provides dynamic, multi-dimensional knowledge representation and management: through dynamic graph structure and rich node attributes, the system can effectively support the full life cycle management of intelligent construction projects, provide multi-angle, multi-dimensional knowledge representation and retrieval functions, and meet the needs of cross-professional team collaboration.

[0096] The present invention provides an efficient application of graph database technology: the selected graph database technology provides the system with powerful data storage, management and query capabilities, supports complex graph operations and real-time data updates, and ensures the high performance and scalability of the system.

[0097] The present invention provides intuitive knowledge graph visualization and interactive design: through the carefully designed knowledge graph visualization and interactive interface, the system greatly improves the user experience, enables users to intuitively understand and explore complex information structures, and facilitates the rapid acquisition of required knowledge.

[0098] The present invention provides a flexible knowledge graph update and maintenance mechanism: the system provides easy-to-operate tools and interfaces to support knowledge managers to flexibly update and maintain the knowledge graph according to the actual needs of the intelligent construction project, thereby ensuring the timeliness and accuracy of the knowledge.

[0099] The present invention not only solves the problems faced by traditional knowledge management systems when applied in the field of intelligent construction, such as information islands and static structures that are insufficient to cope with project changes, but also provides powerful technical support for project management, decision support and cross-professional team collaboration, significantly improving the efficiency and quality of intelligent construction projects.

[0100] The present invention provides a method for using a knowledge graph-based intelligent construction application resource integrated display and management system. Based on the display and management system described above, the method includes:

[0101] Step S1: obtaining user input, performing semantic analysis on the user input, and determining the term or concept corresponding to the user input;

[0102] Step S2: If there is a graph to be displayed corresponding to the term or concept in the underlying knowledge graph, the graph to be displayed is mapped to the top-level knowledge graph, and the top-level knowledge graph is displayed to the user; otherwise, the user is guided to input various types of entities corresponding to the term or concept through the extended interface, the underlying knowledge graph is updated, and then the graph to be displayed is determined, and the graph to be displayed is mapped to the top-level knowledge graph, and the top-level knowledge graph is displayed to the user.

[0103] The above specific embodiments only describe the design principle of the present invention. The shapes and names of the components in the description may be different and are not limited. Therefore, those skilled in the art in the field of the present invention may modify or replace the technical solutions recorded in the above embodiments; and these modifications and replacements do not deviate from the creative purpose and technical solutions of the present invention and should all fall within the protection scope of the present invention.

Claims

1. A knowledge graph-based intelligent construction application resource integrated display and management system, characterized in that: include: Data layer, bottom knowledge graph construction layer, top knowledge graph display layer; The data layer is used to store data of each stage of the intelligent construction project, including current data and historical data; The underlying knowledge graph construction layer constructs and stores the underlying knowledge graph in the form of a graph structure; the underlying knowledge graph is constructed in the following manner: entities are extracted from the data layer, and project phases, technical requirements, and project-specified work processes are used as first-type entities of the underlying knowledge graph; construction processes, management specifications, and quality standards are used as second-type entities of the underlying knowledge graph; and historical data or technical parameters input by users, work implementation processes, and management plans are used as third-type entities; there is a multi-dimensional association relationship between the first-type entity and the second-type entity; Obtaining the relationship between entities from the data layer; Take the technical points, preconditions, and outputs related to the entity as the attributes of the entity; The top-level knowledge graph display layer determines the graph to be displayed based on user input, the graph to be displayed is a subgraph of the graph structure, maps the graph to be displayed to the top-level knowledge graph, and displays the top-level knowledge graph to the user, the top-level knowledge graph is a graphical graph.

2. The system according to claim 1, characterized in that The underlying knowledge graph construction layer obtains various documents, specifications, standards and actual operation data related to historical intelligent construction projects, classifies the various documents, specifications, standards and actual operation data obtained according to the various stages of the intelligent construction projects, and then extracts technical parameters, operation implementation processes, and management plans from the classification results as third-type entities; the underlying knowledge graph construction layer obtains the technical parameters, operation implementation processes, and management plans input by the user through an extended interface, and regards the technical parameters, operation implementation processes, and management plans input by the user as third-type entities; in the graph structure, the third-type entities are identified as knowledge nodes for storage.

3. The system according to claim 2, characterized in that The underlying knowledge graph includes fourth-type entities, which are entities of other types except first-type entities, second-type entities and third-type entities, including user evaluations, labels, case resources, training resources and manufacturer information of products. In the underlying knowledge graph, relationships between the fourth-type entities and other types of entities are established.

4. The system according to claim 1, characterized in that In the underlying knowledge graph, each project phase, technical requirement, project-specified work process, construction technology, management specifications, quality standards, technical parameters, work implementation process, and management plan are defined as nodes. When there are multiple nodes with exactly the same content, the nodes with exactly the same content in different positions in the project are distinguished by associating other nodes. The consistency of nodes with exactly the same content is ensured by establishing inheritance or reuse relationships, and then performing mapping and normalization processing.

5. The system according to claim 1, wherein: The relationships are divided into two categories: static relationships and dynamic relationships, among which static relationships are used to characterize the association relationships between entities, and dynamic relationships are used to characterize the dynamic relationships between entities. The dynamic relationships are used to represent the dynamically updated relationships between entities. The first type of entity has a static relationship with the second type of entity, and the third type of entity, as a knowledge node, has a static relationship and / or a dynamic relationship with the first type of entity and the second type of entity. Multiple entities of the same type have dynamic or static relationships. The static relationships include dependency relationships, attribution relationships, and compatibility relationships. The dynamic relationships are used to represent the dynamically updated relationships between entities, and the dynamic relationships include change relationships, priority adjustment relationships, reuse relationships, and inheritance relationships.

6. The system according to claim 1, wherein: The top-level knowledge graph display layer determines the graph to be displayed based on user input, and the graph to be displayed is a subgraph of the graph structure, including: According to the user input, the term or concept of the user query is determined, and in the underlying knowledge graph, the graph of the user's needs is determined; wherein all entity nodes and their attributes related to the term or concept, as well as the direct and indirect relationships between all entity nodes related to the term or concept, are obtained as the graph of the user's needs; Determine all first entities that have a direct relationship with entities included in the graph of user needs, and then determine all second entities that have a direct relationship with each of the first entities; The entities included in the graph of user needs, the first total entities, and the second total entities constitute an entity set, and the graph to be displayed is composed of each entity in the entity set and the attributes of each entity, and the relationship between each entity in the entity set.

7. The system according to any one of claims 1 to 6, characterized in that: The user provides new information through the extension interface provided by the top-level knowledge graph, and the new information is new knowledge or resource information. The new information is stored in the data layer, and the underlying knowledge graph is updated by the underlying knowledge graph construction layer.

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