Engineering project artificial intelligence interaction method, device, equipment and storage medium

Abstract

The present invention discloses an engineering project artificial intelligence interaction method, device, equipment and storage medium, the method includes: constructing a database based on entity relationship groups, the entity relationship groups are composed of question types and task chains based on question types, the task chains are composed of fixed sentences, engineering project knowledge, business data and related documents; receiving and identifying user questions to extract key information of the questions, the user's question form includes text input form and / or voice input form; obtaining the query authority of the user who asked the question to obtain the associated tasks related to the user's question; obtaining the query results based on the associated tasks; and displaying the query results according to the question information. The present invention can effectively integrate and utilize the professional knowledge and business data in the field of engineering projects in depth, thereby providing users with an accurate and efficient intelligent interaction experience.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and more specifically to an engineering project artificial intelligence interaction method, device, equipment and storage medium. Background Art

[0002] Existing AI interaction systems often lack a deep understanding and application of professional knowledge in the field of engineering projects. The field of engineering projects involves a large number of professional terms, technical details and business processes, all of which require the system to have rich industry knowledge and business understanding capabilities. However, existing systems can often only handle some general and superficial interaction problems, and often cannot give accurate answers to complex problems involving professional knowledge of engineering projects.

[0003] Moreover, the existing AI interactive systems are not capable of processing data in the field of engineering projects. Engineering project management involves a large amount of data, including information on project progress, cost, quality, etc. These data are important bases for the system to understand the project situation and provide effective suggestions. However, existing systems are often unable to effectively integrate and process these data, resulting in the inability to provide users with targeted interactive services.

[0004] In addition, existing AI interaction systems also have deficiencies in terms of user authority management and task association. Engineering project management often involves multiple roles and multiple tasks, and different roles and tasks have different information requirements and interaction permissions. However, existing systems often fail to effectively manage these permissions and associations, resulting in users being unable to obtain the information they need or being unable to effectively collaborate on tasks.

[0005] To sum up, existing technologies are unable to effectively integrate and utilize professional knowledge and business data in the field of engineering projects, and thus are unable to provide users with accurate and efficient intelligent interactive experience. Summary of the invention

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and provide an engineering project artificial intelligence interaction method, device, equipment and storage medium.

[0007] To achieve the above object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides an engineering project artificial intelligence interaction method, comprising:

[0009] Building a database based on entity relationship groups, wherein the entity relationship groups are composed of problem types and task chains based on the problem types, wherein the task chains are composed of fixed statements, engineering project knowledge, business data, and related documents;

[0010] Receiving and identifying a user's question to extract key information of the question, wherein the user's question form includes a text input form and / or a voice input form;

[0011] Obtain the query permissions of the user who asked the question to obtain the associated tasks related to the user's question;

[0012] Get query results based on associated tasks;

[0013] The query results are displayed based on the question information.

[0014] Furthermore, the constructing of a database based on entity relationship groups includes:

[0015] Acquire basic knowledge in engineering project management, including project planning, resource management, risk control and quality management;

[0016] Based on the basic knowledge, various core entities and their relationships are defined to form a first type of entity relationship group;

[0017] Identify key data sources in engineering project management, including schedule planning, resource allocation, task allocation, and risk assessment;

[0018] Extract relevant business data and documents from each key data source and convert them into standardized second-type entity relationship groups;

[0019] The first type of entity relationship group and the second type of entity relationship group are saved and indexed.

[0020] Furthermore, the constructing of the database based on the entity relationship group further includes:

[0021] Cross-hierarchically associating a first type of entity relationship group with a second type of entity relationship group;

[0022] The first type of entity relationship group and the second type of entity relationship group are updated in real time.

[0023] Furthermore, obtaining the query authority of the user who asked the question to obtain the associated tasks related to the user's question includes:

[0024] Determine the recent tasks and related projects of the user asking the question;

[0025] Based on the user role, determine the type of issues associated with the current task and the degree of association;

[0026] Tasks are graded according to their type and degree of relevance.

[0027] Furthermore, the grading of tasks according to task types and degrees of association includes:

[0028] Get the type information of each task from the database;

[0029] According to the task type, find the tasks associated with it;

[0030] Calculate the degree of correlation between tasks;

[0031] According to the closeness of association, tasks are divided into project level, business level and specific business data level, and the classification results are saved.

[0032] Further, obtaining the query result based on the associated task includes:

[0033] Trace the source of the problem through entity relationship groups;

[0034] Replace the parameters in the problem type and matching task chain with actual data, calculate, and output the results.

[0035] Furthermore, displaying query results according to the question information includes:

[0036] Parse the user's question request and detect whether it contains the keywords displayed in the link;

[0037] If a link keyword is identified, the corresponding business module address is determined based on the question type;

[0038] Fill the query results into the parameter table of the business module address;

[0039] Generate a link from the filled business module address and display it in the interactive dialog box;

[0040] If the link keyword is not recognized, the query result is displayed in the interactive dialog box in the form of natural language text.

[0041] In a second aspect, the present invention also provides an engineering project artificial intelligence interaction device, comprising:

[0042] A construction unit, used for constructing a database based on an entity relationship group, wherein the entity relationship group consists of a problem type and a task chain based on the problem type, wherein the task chain consists of fixed statements, engineering project knowledge, business data and related documents;

[0043] A question recognition unit, used to receive and recognize a user's question to extract key information of the question, wherein the user's question form includes a text input form and / or a voice input form;

[0044] The permission acquisition unit is used to acquire the query permission of the user who asked the question, so as to obtain the associated tasks related to the user's question;

[0045] A query result acquisition unit, used to acquire query results based on associated tasks;

[0046] The query result display unit is used to display the query result according to the question information.

[0047] In a third aspect, the present invention further provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the engineering project artificial intelligence interaction method as described above when executing the computer program.

[0048] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a processor, the processor executes the engineering project artificial intelligence interaction method as described above.

[0049] Compared with the prior art, the invention has the following beneficial effects: an artificial intelligence interaction method for engineering projects, comprising: constructing a database based on entity relationship groups, the entity relationship groups are composed of question types and task chains based on question types, the task chains are composed of fixed statements, engineering project knowledge, business data and related documents; receiving and identifying user questions to extract key information of the questions, the user's question form includes text input form and / or voice input form; obtaining the query authority of the questioning user to obtain associated tasks related to the user's question; obtaining query results based on the associated tasks; and displaying query results according to the question information. The invention can quickly identify user questions and extract relevant information from the entity relationship group database, provide instant responses, and improve the efficiency and satisfaction of user interaction. Through accurate key information extraction and task association, the query results provided are more targeted and practical, reducing the time and energy of users' secondary searches. In addition, since the query and display strategies can be adaptively adjusted according to the user's authority and historical behavior, personalized services and suggestions can be provided. Overall, it can effectively integrate and utilize professional knowledge and business data in the field of engineering projects, thereby providing users with accurate and efficient intelligent interaction experience.

[0050] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the following preferred embodiments are specifically cited and described in detail as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying any creative work.

[0052] Figure 1 A flowchart of an engineering project artificial intelligence interaction method provided by a specific embodiment of the present invention;

[0053] Figure 2 A schematic block diagram of an engineering project artificial intelligence interaction device provided by a specific embodiment of the present invention;

[0054] Figure 3 A schematic block diagram of a computer device provided for a specific embodiment of the present invention. DETAILED DESCRIPTION

[0055] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0056] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0057] It should also be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0058] It should be further understood that the term "and / or" used in the present description and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0059] like Figure 1 As shown, an embodiment of the present invention provides an engineering project artificial intelligence interaction method, which includes the following steps: S10-S50.

[0060] S10. Construct a database based on entity relationship groups. The entity relationship groups are composed of problem types and task chains based on the problem types. The task chains are composed of fixed statements, engineering project knowledge, business data and related documents.

[0061] In one embodiment, step S10 specifically includes the following steps: S101 - S105 .

[0062] S101. Acquire basic knowledge in engineering project management, including project planning, resource management, risk control and quality management.

[0063] In this embodiment, a team of experienced project management experts is formed to organize the basic knowledge in engineering project management, including project planning, resource management, risk control, quality management and other aspects.

[0064] S102: Based on basic knowledge, define various core entities and their relationships to form a first type of entity relationship group.

[0065] In this embodiment, various core entities (such as projects, tasks, resources, risks) and their relationships (such as dependency relationships and inclusion relationships) are defined based on basic knowledge.

[0066] S103. Identify key data sources in engineering project management, including schedule planning, resource allocation, task allocation, and risk assessment.

[0067] By clarifying the source of business data, we can ensure the comprehensiveness and accuracy of data acquisition.

[0068] S104. Extract relevant business data and documents from each key data source and convert them into a standardized second type entity relationship group.

[0069] Convert business data into structured second-type entity relationship groups to ensure data standardization and consistency.

[0070] S105: Save the first type of entity relationship group and the second type of entity relationship group, and create an index.

[0071] The transformed entity relationship groups (referring to the first type of entity relationship groups and the second type of entity relationship groups) are stored in the database, and indexes are created to improve query efficiency.

[0072] The data storage and indexing mechanism (such as Lucene index) is used for storage and optimization, which enables efficient storage and fast retrieval of entity relationship groups and improves response speed.

[0073] It should be noted that the reason why the basic knowledge of engineering projects and business data and document acquisition are converted into entity relationship groups is to ensure that data from different sources can be processed and stored systematically and play their respective roles. These two parts of data have their own characteristics and uses, so they need to be processed and converted independently. The specific reasons are as follows:

[0074] Basic knowledge is common knowledge in engineering project management, which is systematic and widely applicable. This knowledge is usually relatively stable and does not change frequently. By converting basic knowledge into the first type of entity relationship group, this knowledge can be standardized to form a systematic knowledge base. Basic knowledge can be used as a shared resource for various engineering projects to improve the efficiency and consistency of project management.

[0075] Business data and documents are actual data in specific engineering projects, which are dynamic and project-specific. These data will be continuously updated as the project progresses, and need to reflect the latest status of the project in a timely manner. Converting business data and documents into the second type of entity relationship group can achieve structured storage, which is convenient for data management and query. Through the second type of entity relationship group, business data can be updated and analyzed in real time, supporting real-time monitoring and decision-making of the project.

[0076] Although basic knowledge and business data are converted into different types of entity relationship groups, the two are closely integrated and complement each other in the process of building a database.

[0077] In one embodiment, step S10 further specifically includes the following steps: S106 - S107 .

[0078] S106: Cross-level association between the first type of entity relationship group and the second type of entity relationship group.

[0079] By establishing cross-level associations, basic knowledge can be associated with specific business data. For example, the project management method in the basic knowledge can be associated with the task and risk management data in a specific project.

[0080] More specifically, the objects that can be associated are as follows:

[0081] Projects and tasks: Each project contains multiple tasks, and there may be dependencies between tasks;

[0082] Roles and tasks: In a project, specific roles (such as project managers and engineers) are responsible for specific tasks;

[0083] Resources and tasks: Each task requires specific resources (such as people, equipment, materials) to complete;

[0084] Risks and Projects / Tasks: Projects or tasks may face different risks, which have a likelihood and impact level;

[0085] Dependency: The dependency between tasks, such as the predecessor task must be completed before the next task can be carried out.

[0086] The association is as follows:

[0087] Project hierarchy association: defines the project entity and its associated task entities;

[0088] Task hierarchy association: defines task entities and their associated roles, resources, and risk entities;

[0089] Role hierarchy association: defines the role entity and its associated task entity;

[0090] Resource hierarchy association: defines resource entities and their associated task entities;

[0091] Risk Hierarchy Association: Defines risk entities and their associated project and task entities.

[0092] For steps S106-S107, a structured and multi-dimensional database is formed through multi-level association. This structured database facilitates query and analysis of complex relationships and improves data utilization efficiency.

[0093] S107: Update the first type of entity relationship group and the second type of entity relationship group in real time.

[0094] By establishing a data synchronization mechanism, the latest data in engineering project management can be synchronized to the database in real time. Real-time data synchronization tools (such as Kafka and RabbitMQ) can be used to achieve data synchronization.

[0095] Real-time updates ensure that the data in the database is consistent with the actual project data, improving the real-time and accuracy of the data.

[0096] Of course, adaptive algorithms can be introduced to dynamically update and optimize the database, identify new entities and relationships, and use machine learning algorithms (such as K-means clustering and decision trees) for adaptive optimization. By introducing adaptive algorithms, the database can be self-learned and dynamically updated to keep the database up to date and adaptive.

[0097] S20, receiving and identifying a user's question to extract key information of the question, wherein the user's question may be in the form of text input and / or voice input.

[0098] Specifically, users can input through natural language text to facilitate the description and processing of problems. Users can also obtain question text through WeChat recording and audio-to-text interface to improve the convenience of interaction. Of course, the two methods can also be used in combination.

[0099] Once the question content is identified, the data can be automatically cleaned and standardized to ensure data consistency and quality.

[0100] After clarifying the content of the question, use NLP technology to identify key entities in the text (such as project name, date, etc.), extract the relationship information between entities, and form a structured search statement.

[0101] S30: Obtain the query authority of the user who asked the question to obtain the associated tasks related to the user's question.

[0102] In one embodiment, step S30 specifically includes the following steps: S301 - S303 .

[0103] S301, determining the recent tasks and related projects of the user asking the question.

[0104] In this embodiment, the user's identity is verified by username and password or other authentication methods, the user's recent tasks are queried from the database, and the projects associated with each task are queried based on the task ID, and a list of tasks and their associated projects that the user has permission to access is returned.

[0105] This design ensures that users can only access tasks and projects for which they have permissions, thus protecting data security.

[0106] S302: Determine the type of problem associated with the current task and the degree of association according to the user role.

[0107] In this embodiment, the role information of the user is obtained from the user database, and the scope of authority of the user role is determined according to the role mapping table. The type and closeness of the problem associated with the user role and the task are evaluated using a data closeness algorithm (e.g., a cosine similarity algorithm), and an authority information report is generated to indicate the type of problem that the user can access and the degree of its association.

[0108] Refine user permissions by dividing roles and improve the accuracy of task management.

[0109] S303: Classify the tasks according to the task types and the degree of correlation.

[0110] In one embodiment, step S303 specifically includes the following steps: S3031 - S3035 .

[0111] S3031. Classify tasks according to task type and degree of relevance, including:

[0112] S3032, obtaining type information of each task from the database;

[0113] S3033. Searching for tasks associated with the task type;

[0114] S3034, calculating the correlation between each task;

[0115] S3035. Classify the tasks into project level, business level and specific business data level according to the degree of association, and save the classification results.

[0116] For steps S3031-S3035, in this embodiment, the type information of each task is obtained from the task database, and the tasks related to the task type are found. The data analysis algorithm (for example, the cosine similarity algorithm) is used to calculate the correlation between the tasks. Based on the correlation, the tasks are divided into project level, business level, and specific business data level, and the classification results are stored in the task management system for subsequent use.

[0117] This design provides a clear task hierarchy structure, facilitating task priority management and resource allocation.

[0118] S40: Obtain query results based on the associated tasks.

[0119] In one embodiment, step S40 specifically includes the following steps: S401 - S402 .

[0120] S401. Trace the source of the problem through entity relationship groups.

[0121] In this embodiment, the type of question input by the user is determined, the relationship between the question type and its related entities is constructed based on the database, and the source and influencing factors of the question are traced using the entity relationship group.

[0122] This design helps users quickly locate the source of the problem and improve problem-solving efficiency.

[0123] S402: Replace the problem type and the parameters in the matching task chain with actual data, calculate and output the result.

[0124] In this embodiment, the corresponding task chain is found according to the problem type, the parameters in the task chain are replaced with actual data, the calculation program is run, the logical operation result is obtained, and the calculation result is filled into the output parameter for subsequent use.

[0125] This design implements data-driven logical operations and ensures the accuracy of calculation results.

[0126] S50: Display query results according to the question information.

[0127] In the application scenario of engineering projects, result display and feedback mechanism are important links to ensure that users can effectively understand and use system output. Through natural language output and link display, result display can meet different needs.

[0128] In one embodiment, step S50 specifically includes the following steps: S501 - S505 .

[0129] S501, parsing the user's question request and detecting whether it contains the keywords displayed in the link;

[0130] S502: If a link keyword is identified, the corresponding business module address is determined according to the question type;

[0131] S503, filling the query result into the parameter table of the business module address;

[0132] S504, generating a link from the filled business module address and displaying it in an interactive dialog box;

[0133] S505: If the link keyword is not identified, the query result is displayed in the interactive dialog box in the form of natural language text.

[0134] For steps S501-S505, in this embodiment, the user's question request is parsed to check whether the question request contains keywords that need to be displayed by link. If the link keyword is not identified, the natural language output method is adopted, the query result is converted into a natural language description, and the natural language result is displayed in the interactive dialog box. If the link keyword is identified, the corresponding business module address is determined according to the question type, the calculation or query result is filled into the parameter table of the business module address, and the filled business module address is generated as a link, and the final result is displayed in the interactive dialog box in the form of a link.

[0135] It should be noted that in natural language output, link keywords can refer to specific words or phrases related to user requests. These link keywords are used to identify whether the user's intention requires linking to other information or functions. For example, link keywords can be "view details", "get more information", "user manual" and "installation problems".

[0136] By identifying these link keywords, the system can decide whether to provide hyperlinks or guide users to other related content, which not only improves the accessibility of information but also enhances the smoothness of the user experience.

[0137] The present invention can quickly identify user questions and extract relevant information from the entity relationship group database, provide instant responses, and improve the efficiency and satisfaction of user interaction. Through accurate key information extraction and task association, the query results provided are more targeted and practical, reducing the time and energy of users' secondary searches. In addition, since it can adaptively adjust the query and display strategies according to the user's authority and historical behavior, it can provide personalized services and suggestions. Overall, it can effectively integrate and utilize professional knowledge and business data in the field of engineering projects, thereby providing users with accurate and efficient intelligent interactive experience.

[0138] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0139] The embodiment of the present invention also provides an engineering project artificial intelligence interaction device, which is used to perform the steps in any embodiment of the aforementioned engineering project artificial intelligence interaction method. Figure 2 , Figure 2 A schematic block diagram of an engineering project artificial intelligence interaction device 100 provided in an embodiment of the present application is shown, and the engineering project artificial intelligence interaction device 100 specifically includes:

[0140] A construction unit 110 is used to construct a database based on an entity relationship group, wherein the entity relationship group consists of a question type and a task chain based on the question type, wherein the task chain consists of fixed statements, engineering project knowledge, business data, and related documents; a question recognition unit 120 is used to receive and recognize a user's question to extract key information of the question, wherein the user's question form includes a text input form and / or a voice input form; a permission acquisition unit 130 is used to obtain the query permission of the user who asked the question to obtain associated tasks related to the user's question; a query result acquisition unit 140 is used to obtain query results based on associated tasks; a query result display unit 150 is used to display query results according to the question information.

[0141] In one embodiment, the construction unit 110 is specifically configured to:

[0142] Acquire basic knowledge in engineering project management, which includes project planning, resource management, risk control and quality management; based on the basic knowledge, define various core entities and their relationships to form a first type of entity relationship group; identify key data sources in engineering project management, which include schedule planning, resource allocation, task allocation and risk assessment; extract relevant business data and documents from each key data source and convert them into a standardized second type of entity relationship group; save the first type of entity relationship group and the second type of entity relationship group, and establish an index.

[0143] In one embodiment, the construction unit 110 is further specifically configured to:

[0144] The first type of entity relationship group and the second type of entity relationship group are cross-hierarchically associated; and the first type of entity relationship group and the second type of entity relationship group are updated in real time.

[0145] In one embodiment, the permission acquisition unit 130 is specifically used to:

[0146] Determine the recent tasks and related projects of the user asking the question; determine the type of questions associated with the current task and the degree of association based on the user role; and classify tasks based on task type and degree of association.

[0147] In one embodiment, the permission acquisition unit 130 is further specifically configured to:

[0148] Obtain the type information of each task from the database; find the tasks related to the task type according to the task type; calculate the degree of correlation between the tasks; classify the tasks into project level, business level and specific business data level according to the degree of correlation, and save the classification results.

[0149] In one embodiment, the query result acquisition unit 140 is specifically used to:

[0150] Trace the source of the problem through the entity relationship group; replace the problem type and the parameters in the matching task chain with actual data, calculate and output the results.

[0151] In one embodiment, the query result display unit 150 is specifically used to:

[0152] Parse the user's question request and detect whether it contains keywords for link display; if link keywords are recognized, determine the corresponding business module address according to the question type; fill the query results into the parameter table of the business module address; generate a link for the filled business module address and display it in the interactive dialog box; if link keywords are not recognized, display the query results in the interactive dialog box as natural language text.

[0153] It should be noted that technicians in the relevant field can clearly understand that the specific implementation process of the above-mentioned engineering project artificial intelligence interaction device 100 and each unit can refer to the corresponding description in the aforementioned method embodiment, and for the convenience and brevity of description, it will not be repeated here.

[0154] The above-mentioned engineering project artificial intelligence interaction device can be implemented in the form of a computer program, which can be used in Figure 3 Runs on the computer device shown.

[0155] See also Figure 3 , Figure 3 700 is a schematic block diagram of a computer device provided in an embodiment of the present application. The computer device 700 may be a server, wherein the server may be an independent server or a server cluster composed of multiple servers.

[0156] like Figure 3 As shown, the computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the engineering project artificial intelligence interaction method as described above are implemented.

[0157] The computer device 700 may be a terminal or a server. The computer device 700 includes a processor 720 , a memory, and a network interface 750 connected via a system bus 710 , wherein the memory may include a non-volatile storage medium 730 and an internal memory 740 .

[0158] The non-volatile storage medium 730 can store an operating system 731 and a computer program 732. When the computer program 732 is executed, the processor 720 can execute the engineering project artificial intelligence interaction method.

[0159] The processor 720 is used to provide computing and control capabilities and support the operation of the entire computer device 700.

[0160] The internal memory 740 provides an environment for the operation of the computer program 732 in the non-volatile storage medium 730. When the computer program 732 is executed by the processor 720, the processor 720 can execute the engineering project artificial intelligence interaction method.

[0161] The network interface 750 is used for network communication, such as sending assigned tasks, etc. Those skilled in the art will appreciate that Figure 3The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 700 to which the solution of the present application is applied. The specific computer device 700 may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components. The processor 720 is used to run the program code stored in the memory to implement the engineering project artificial intelligence interaction method.

[0162] Those skilled in the art will understand that Figure 3 The embodiments of the computer device shown in the figure do not constitute a limitation on the specific composition of the computer device. In other embodiments, the computer device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. For example, in some embodiments, the computer device may only include a memory and a processor. In such embodiments, the structure and function of the memory and the processor are the same as those of the embodiment of the present invention. Figure 3 The embodiments shown are consistent and will not be described again here.

[0163] It should be understood that in the embodiment of the present application, the processor 720 may be a central processing unit (CPU), and the processor 720 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, etc. Among them, the general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0164] In another embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium may be a non-volatile computer-readable storage medium. The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the engineering project artificial intelligence interaction method disclosed in the embodiment of the present invention is implemented.

[0165] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the above-described equipment, devices and units can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. Those of ordinary skill in the art can appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented with electronic hardware, computer software or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to the function. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0166] In the several embodiments provided by the present invention, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. Units with the same function may also be combined into one unit. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interfaces, devices or units, or may be electrical, mechanical or other forms of connection.

[0167] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of the present invention.

[0168] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0169] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), disk or optical disk and other media that can store program codes.

[0170] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. An artificial intelligence interaction method for engineering projects, characterized in that: include: Building a database based on entity relationship groups, wherein the entity relationship groups are composed of problem types and task chains based on the problem types, wherein the task chains are composed of fixed statements, engineering project knowledge, business data, and related documents; Receiving and identifying a user's question to extract key information of the question, wherein the user's question form includes a text input form and / or a voice input form; Obtain the query permissions of the user who asked the question to obtain the associated tasks related to the user's question; Get query results based on associated tasks; Display query results based on question information; The step of constructing a database based on entity relationship groups includes: Acquire basic knowledge in engineering project management, including project planning, resource management, risk control and quality management; Based on the basic knowledge, various core entities and their relationships are defined to form a first type of entity relationship group; Identify key data sources in engineering project management, including schedule planning, resource allocation, task allocation, and risk assessment; Extract relevant business data and documents from each key data source and convert them into standardized second-type entity relationship groups; The first type of entity relationship group and the second type of entity relationship group are saved and indexed; The constructing of a database based on entity relationship groups further includes: Cross-hierarchically associating a first type of entity relationship group with a second type of entity relationship group; Performing real-time updates on the entity relationship group of the first type and the entity relationship group of the second type; The step of obtaining the query authority of the user who asked the question to obtain the associated tasks related to the user's question includes: Determine the recent tasks and related projects of the user asking the question; Based on the user role, determine the type of issues associated with the current task and the degree of association; Classify tasks according to their type and degree of relevance; The tasks are graded according to the task type and the degree of correlation, including: Get the type information of each task from the database; According to the task type, find the tasks associated with it; Calculate the degree of correlation between tasks; According to the closeness of association, tasks are divided into project level, business level and specific business data level, and the classification results are saved.

2. The engineering project artificial intelligence interaction method according to claim 1 is characterized in that: The obtaining of query results based on the associated tasks includes: Trace the source of the problem through entity relationship groups; Replace the parameters in the problem type and matching task chain with actual data, calculate, and output the results.

3. The engineering project artificial intelligence interaction method according to claim 1 is characterized in that: The query result display according to the question information includes: Parse the user's question request and detect whether it contains the keywords displayed in the link; If a link keyword is identified, the corresponding business module address is determined based on the question type; Fill the query results into the parameter table of the business module address; Generate a link from the filled business module address and display it in the interactive dialog box; If the link keyword is not recognized, the query result is displayed in the interactive dialog box in the form of natural language text.

4. An engineering project artificial intelligence interaction device, when in operation, executes the engineering project artificial intelligence interaction method according to any one of claims 1 to 3, characterized in that: include: A construction unit, used for constructing a database based on an entity relationship group, wherein the entity relationship group consists of a problem type and a task chain based on the problem type, wherein the task chain consists of fixed statements, engineering project knowledge, business data and related documents; A question recognition unit, used to receive and recognize a user's question to extract key information of the question, wherein the user's question form includes a text input form and / or a voice input form; The permission acquisition unit is used to acquire the query permission of the user who asked the question, so as to obtain the associated tasks related to the user's question; A query result acquisition unit, used to acquire query results based on associated tasks; The query result display unit is used to display the query result according to the question information.

5. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for artificial intelligence interaction of an engineering project as claimed in any one of claims 1 to 3 is implemented.

6. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which includes program instructions. When the program instructions are executed by a processor, the processor executes the engineering project artificial intelligence interaction method according to any one of claims 1 to 3.

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