Project management method, system, equipment and medium

Abstract

The invention provides a project management method, system and device and a medium, and belongs to the field of project management. The method comprises the following steps: collecting project related data, and sorting and cleaning the project related data to obtain a structured data set; adopting an entity identification and relation extraction algorithm to carry out entity labeling and relation extraction processing on the structured data set so as to construct a knowledge graph related to the project; the method comprises the following steps: performing task decomposition by adopting a graph traversal algorithm on the basis of a knowledge graph, generating a task list and a priority sequence thereof, and monitoring task progress and resource utilization rate in real time on the basis of a dynamic optimization algorithm so as to dynamically adjust task priority and a resource configuration strategy. The task module is automatically decomposed based on the knowledge graph, the task decomposition efficiency and accuracy are improved, intelligent resource allocation and task priority adjustment are achieved in combination with dynamic planning and an optimization algorithm, the team cooperation efficiency is improved, and the flexibility and adaptability of a project are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of project management, and specifically relates to a project management method, system, equipment and medium. Background Art

[0002] With the rapid development of AI technology, the complexity and uncertainty of projects have increased significantly. Modern project management needs to meet the following requirements: Efficient task decomposition: able to quickly identify task modules and their dependencies, reducing manual intervention. Dynamic collaborative optimization: adjust team resource allocation and task priorities based on real-time data. Intelligent risk management: able to predict potential risks in advance and provide response strategies. Cross-domain knowledge integration: able to process knowledge and information from different fields and build a complete project knowledge system.

[0003] Traditional project management methods (such as waterfall model, agile development, etc.) are unable to cope with complex and large-scale AI projects. Specifically, Task decomposition is not intelligent enough: Traditional methods rely on manual decomposition of tasks, which takes a long time and is prone to missing key nodes. Inefficient collaboration: Collaboration between team members depends on frequent communication and coordination, and problems such as uneven resource allocation and information islands are common. Limited risk management capabilities: Traditional methods lack the ability to predict potential risks and can only respond passively after problems arise. Lack of dynamic optimization capabilities: During the project execution process, once the environment or requirements change, traditional methods are difficult to quickly adjust task arrangements and resource allocation. Manual adjustments are required when requirements change, which increases time by 50%. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a project management method, system, device and medium, which are used to completely or at least partially solve the technical problems existing in the above-mentioned prior art.

[0005] In a first aspect, an embodiment of the present application provides a project management method, including: Collect project-related data, organize and clean the project-related data, and obtain a structured data set; Using entity recognition and relationship extraction algorithms, the structured data set is subjected to entity labeling and relationship extraction processing to construct a knowledge graph related to the project; Based on the knowledge graph, a graph traversal algorithm is used to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priority and resource allocation strategies.

[0006] Optionally, project-related data is collected, and the project-related data is sorted and cleaned to obtain a structured data set, including: Collecting project-related data from multiple sources, wherein the project-related data includes but is not limited to project goals, task descriptions, resource requirements, and team member skills; Use NLP natural language processing technology to extract key information from project-related data, perform data cleaning, and convert unstructured data into structured data to ensure the consistency and integrity of the data format.

[0007] Optionally, entity recognition and relationship extraction algorithms are used to perform entity labeling and relationship extraction processing on the structured data set to construct a project-related knowledge graph, including: Based on predetermined project entities, domain terms in the structured data set are screened out and a domain term list is generated; Define an entity label set, a relationship label set, and labeling constraint rules, label the structured data set, and obtain labeled data; Perform entity mask enhancement on structured datasets, extract entity, attribute, and relation triplets from labeled data, and construct relation pre-training corpus; A dual-branch encoder is constructed based on the relational pre-training corpus and the BERT-base model, wherein the dual-branch encoder includes an entity branch encoder and a relation branch encoder, wherein the entity branch encoder is used to access the Token-level input and output the entity label distribution, and the relation branch encoder is used to receive the entity pair plus context input and output the relation classification probability; Input the labeled data into a dual-branch encoder, perform character-level alignment, and generate a Token label mapping table; Based on the Token tag mapping table, string matching and synonym merging are performed, and attribute value verification is used to build a project-related knowledge graph.

[0008] Optionally, based on the knowledge graph, a graph traversal algorithm is used to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priorities and resource allocation strategies, including: A directed acyclic graph is generated based on the resource dependency attributes and execution time weights of the task nodes, and a task dependency matrix is ​​established during the task list generation process. Conflict detection is performed on task nodes with resource competition, and mutually exclusive access to shared resources is ensured by inserting virtual synchronization nodes. Task priorities are sorted based on the product of the node out-degree value and the weighted path duration. Construct a multi-dimensional monitoring vector of task progress deviation, resource utilization entropy value and node load balancing factor, and trigger priority re-evaluation when the task progress deviation, resource utilization entropy value and node load balancing factor all exceed the preset threshold; The dynamic adjustment strategy includes resource preemptive reallocation, which preempts the reserved resources of low-priority tasks according to the urgency index of lagging tasks, and records the resource borrowing and lending relationship for subsequent compensation scheduling, wherein the urgency index is determined by the ratio of the square of the remaining workload to the elasticity of the remaining resources.

[0009] Optionally, the project management method further includes: Assign optimized tasks to the appropriate team members and use collaborative tools to track task progress; Use real-time communication technology to ensure instant information transmission between team members; Design collaborative interfaces to display task assignments, progress updates, and communication records.

[0010] Optionally, the project management method further includes: Use front-end frameworks to build user interfaces and set different access permissions based on user roles; Supports users to adjust task priorities or reallocate resources through release operations.

[0011] In a second aspect, an embodiment of the present application further provides a project management system, including: The data collection and preprocessing module is used to collect project-related data, and to preliminarily organize and clean the project-related data to obtain a structured data set; A knowledge graph construction module, which is used to use entity recognition and relationship extraction algorithms to perform entity labeling and relationship extraction processing on the structured data set to construct a knowledge graph related to the project; The task decomposition and optimization module is used to perform task decomposition based on the knowledge graph using a graph traversal algorithm, generate a task list and its priority order, and monitor task progress and resource utilization in real time based on a dynamic optimization algorithm to dynamically adjust task priority and resource allocation strategies.

[0012] Optionally, the project management system further includes: The system integration and extension module is used to divide the system into multiple independent services, ensure modular design, and use the API gateway to manage communication and service discovery between modules.

[0013] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned project management method when executing the program.

[0014] In a fourth aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the project management method described above are implemented.

[0015] It can be seen from the above technical solutions that the present invention has the following advantages: In the project management method, system, equipment and medium provided in this application, the task modules are automatically decomposed based on the knowledge graph to improve the efficiency and accuracy of task decomposition, and dynamic planning and optimization algorithms are combined to realize intelligent allocation of resources and adjustment of task priorities, thereby improving team collaboration efficiency and improving the flexibility and adaptability of the project. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solution of the present invention, the accompanying drawings required for use in the description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only 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 creative work.

[0017] Figure 1 A flowchart of an implementation of a project management method provided by an embodiment of the present invention; Figure 2 A schematic diagram of a knowledge graph construction process provided by an embodiment of the present invention; Figure 3 A flowchart of project management based on knowledge graph provided in an embodiment of the present invention; Figure 4 A schematic diagram of the structure of a project management system provided by an embodiment of the present invention; Figure 5 A schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0018] In the detailed description below, various embodiments of the present disclosure will be described more fully. The present disclosure may have various embodiments, and adjustments and changes may be made therein. However, it should be understood that there is no intention to limit the various embodiments of the present disclosure to the specific embodiments disclosed herein, but rather the present disclosure should be understood to cover all adjustments, equivalents and / or alternatives that fall within the spirit and scope of the various embodiments of the present disclosure.

[0019] Hereinafter, the terms "include" or "may include" that may be used in various embodiments of the present disclosure indicate the presence of the disclosed functions or operations, and do not limit the addition of one or more functions or operations. In addition, as used in various embodiments of the present disclosure, the terms "include", "have" and their cognates are intended only to indicate specific features, numbers, steps, operations, or combinations of the foregoing items, and should not be understood as first excluding the presence of one or more other features, numbers, steps, operations, or combinations of the foregoing items or the possibility of adding one or more features, numbers, steps, operations, or combinations of the foregoing items.

[0020] In various embodiments of the present disclosure, the expression "or" or "at least one of A or / and B" includes any combination or all combinations of the words listed at the same time. For example, the expression "A or B" or "at least one of A or / and B" may include A, may include B, or may include both A and B.

[0021] 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 only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0022] See also Figure 1 The flowchart of a project management method in a specific embodiment includes the following execution steps: Step 100: Collect project-related data, organize and clean the project-related data, and obtain a structured data set.

[0023] Specifically, when executing step 100, the following steps may be specifically performed: S1000: Collect project-related data from multiple source data, wherein the project-related data includes but is not limited to project goals, task descriptions, resource requirements, and team member skills.

[0024] Exemplarily, project-related data is collected from requirement documents, technical specifications, and team member information.

[0025] S1001: Use NLP natural language processing technology to extract key information from project-related data, perform data cleaning, convert unstructured data into structured data, and ensure the consistency and integrity of the data format.

[0026] Exemplarily, cleaning and standardizing data includes removing noise, and for text data, removing punctuation, converting to lowercase, removing stop words, etc. Use NLP natural language processing technology to extract task modules and dependencies from unstructured text data, and use machine learning to predict task completion time, resource requirements, and potential risks.

[0027] Step 101: Use entity recognition and relationship extraction algorithms to perform entity labeling and relationship extraction on the structured data set to construct a project-related knowledge graph.

[0028] For details, see Figure 2 As shown, when executing step 101, the following steps may be specifically performed: S1010: Based on predetermined project entities, domain terms in the structured data set are screened out and a domain term list is generated.

[0029] Exemplarily, the predetermined project entities include task modules, resources, and team members.

[0030] S1011: Define an entity tag set, a relationship tag set, and tagging constraint rules, and tag the structured data set to obtain tagged data.

[0031] For example, the task entity must contain an action word (such as "analyze"), the resource entity must carry quantitative attributes (quantity / type), and the skill entity must be associated with a member entity. Specifically, it can be represented as a task must be associated with ≥1 resource, a member skill must be associated with a specific member, and the number of resources must be ≥1.

[0032] S1012: Perform entity mask enhancement on the structured dataset, and extract entity, attribute, and relationship triplets from the labeled data to construct a relational pre-training corpus.

[0033] S1013: Construct a dual-branch encoder based on the relational pre-training corpus and the BERT-base model, wherein the dual-branch encoder includes an entity branch encoder and a relation branch encoder, the entity branch encoder is used to access the Token-level input and output the entity label distribution, and the relation branch encoder is used to receive the entity pair plus context input and output the relation classification probability.

[0034] S1014: Input the annotated data into a dual-branch encoder, perform character-level alignment, and generate a Token label mapping table.

[0035] S1015: Perform string matching and synonym merging based on the Token tag mapping table, and use attribute value verification to build a project-related knowledge graph.

[0036] For example, for resource entities, cross-validation is performed through quantity units (units / persons) and types (tools / manpower) to eliminate ambiguity (such as "3 days" is not a resource).

[0037] Exemplarily, graph conflict detection rules are constructed: task duration ≥ sum of subtask durations (±10% floating); total resource amount ≤ available amount (such as server × 2, inventory needs ≥ 2); member skill proficiency ≥ task requirements (mapped through skill ontology library); detected conflicts (confidence ≥ 0.8) are automatically marked as nodes for manual review.

[0038] Exemplarily, based on a visual knowledge graph, the relationships between task modules, resources, team members and machines are displayed, and a graph database (such as Neo4j) is used to store and manage the knowledge graph.

[0039] In a specific embodiment, a BERT model based on domain adaptation is used to optimize the construction of knowledge graphs through pre-training tasks (such as entity labeling and relationship extraction). Specifically, a labeled dataset containing 1,000 project management entities (task modules, resource requirements, team member skills) is used for fine-tuning, and the model accuracy reaches 92%. A graph database (such as Neo4j) is used to store entities and their relationships. A semantic network between task modules, resources, and team members is constructed. The knowledge graph is displayed through visualization tools (such as Gephi) to facilitate users to understand the relationship between task modules. Step 102: Based on the knowledge graph, a graph traversal algorithm is used to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priority and resource allocation strategies.

[0040] For details, see Figure 3 As shown, when executing step 102, the following steps may be specifically performed: S1020: Generate a directed acyclic graph based on the resource dependency attributes and execution time weights of the task nodes, and establish a task dependency matrix during the task list generation process, implement conflict detection for task nodes with resource competition, and ensure mutually exclusive access to shared resources by inserting virtual synchronization nodes.

[0041] Among them, the task priority is sorted based on the product of the node out-degree value and the weighted path duration.

[0042] It should be understood that the priority of the virtual node is dynamically adjusted according to the scarcity coefficient of the competing resources.

[0043] In some embodiments, the critical path analysis uses an improved PERT algorithm to set the optimistic time to, pessimistic time tp and probability weight w for the task node, and calculate the weighted expected time te=(w×to + tp) / (w+1), where the w value is dynamically adjusted according to the coefficient of variation of historical execution data.

[0044] S1021: Construct a multi-dimensional monitoring vector of task progress deviation, resource utilization entropy value and node load balancing factor, and trigger priority re-evaluation when the task progress deviation, resource utilization entropy value and node load balancing factor all exceed preset thresholds.

[0045] Specifically, the task progress deviation is calculated according to the following formula: ΔT = actual time consumption / estimated time consumption. The resource utilization entropy value is calculated according to the following formula:

[0046] The node load balancing factor is calculated according to the following formula: β = 1-σ (CPU utilization) / μ (CPU utilization).

[0047] It should be understood that the preset thresholds can be set according to specific application scenarios. For example, the task progress deviation threshold is set to 1.2, the resource utilization entropy threshold is set to 0.6, and the node load balancing factor is set to 0.3. When ΔT>1.2, H<0.6 and β>0.3, priority re-evaluation is triggered.

[0048] S1022: The dynamic adjustment resource configuration strategy includes resource preemptive reallocation, preempting the reserved resources of low-priority tasks according to the urgency index of the lagging tasks, and recording the resource lending relationship for subsequent compensation scheduling.

[0049] The urgency index is determined by the ratio of the square of the remaining workload to the elasticity of the remaining resources.

[0050] 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.

[0051] In a specific embodiment, the project management method execution process also includes assigning optimized tasks to corresponding team members and using collaboration tools to track task progress; using real-time communication technology to ensure instant information transmission between team members; and designing a collaboration interface to display task assignments, progress updates, and communication records.

[0052] For example, collaboration tools such as Jira and real-time communication technologies such as WebSocket ensure instant information transmission between team members, provide discussion or chat functions to facilitate team members to exchange problems and solutions, design intuitive collaboration interfaces, display task assignments, progress updates and communication records, and support team members to directly adjust tasks and submit feedback in the interface.

[0053] In a specific implementation, the project management method execution process also includes using a front-end framework to build a user interface and setting different access rights according to user roles; supporting users to adjust task priorities or reallocate resources through release operations.

[0054] For example, use front-end frameworks (such as React) to build intuitive user interfaces. Provide personalization settings to allow users to customize views according to their needs and set different access permissions based on user roles (project managers, team members, customers). Ensure the security and privacy of sensitive information. Support users to adjust task priorities or reallocate resources through drag-and-drop operations. Provide one-click report generation function to facilitate users to quickly obtain project status summaries.

[0055] In a specific embodiment, it also includes system integration and expansion: Microservice architecture design: divide the system into multiple independent services (such as data collection services, knowledge graph construction services, etc.) to ensure modular design. Each service runs independently, which is easy to expand and maintain. API gateway management: use API gateway to manage communication and service discovery between modules. Provide unified interface standards to simplify the integration process of third-party tools. Third-party tool integration: integrate commonly used project management tools (such as Jira, Trello) and data analysis tools (such as Tableau). Ensure that the system is seamlessly connected with other tools to improve overall work efficiency.

[0056] The technical effects achieved by this application are as follows: 1. Intelligent and efficient task decomposition: Automatically identify task modules and their dependencies through knowledge graph technology, significantly reduce manual intervention, and improve the efficiency and accuracy of task decomposition. Quickly extract key task modules from complex requirement documents and technical specifications. Automatically identify the logical relationship between tasks to avoid missing key nodes. Improve the traceability and explainability of task decomposition.

[0057] 2. Flexibility and real-time performance of dynamic collaboration optimization: Dynamically adjust task priorities and resource allocation based on real-time data to improve team collaboration efficiency. Intelligently assign tasks based on the workload and skill characteristics of team members. Quickly adjust task plans when project requirements or resource conditions change. Reduce resource waste and task delays, and improve project execution efficiency.

[0058] 3. Integration and utilization of cross-domain knowledge: Build a complete project knowledge system to promote cross-departmental and cross-domain knowledge sharing and collaboration. Integrate multi-source knowledge such as requirement documents, technical specifications, and team member experience. Through knowledge graphs, semantic understanding and association analysis of knowledge are achieved to improve the team's overall cognitive ability for complex projects.

[0059] 4. Maximize resource utilization: Rationally allocate resources through dynamic optimization algorithms to improve resource utilization. Dynamically adjust resource allocation according to task priorities and resource requirements. Avoid idle or overused resources. Improve the overall cost-effectiveness of the project.

[0060] 5. Improve user experience and usability: Improve user experience through friendly user interface and interactive design. Provide intuitive task view and real-time data visualization. Support personalized settings and multi-role permission management. Provide convenient task adjustment and feedback functions.

[0061] like Figure 4As shown, the following is an embodiment of the project management system provided by the embodiment of the present disclosure, which belongs to the same inventive concept as the project management method of the above-mentioned embodiments. For details not described in detail in the embodiment of the project management system, please refer to the embodiment of the above-mentioned project management method.

[0062] Project management system, including: The data collection and preprocessing module is used to collect project-related data, and to preliminarily organize and clean the project-related data to obtain a structured data set; A knowledge graph construction module, which is used to use entity recognition and relationship extraction algorithms to perform entity labeling and relationship extraction processing on the structured data set to construct a knowledge graph related to the project; The task decomposition and optimization module is used to perform task decomposition based on the knowledge graph using a graph traversal algorithm, generate a task list and its priority order, and monitor task progress and resource utilization in real time based on a dynamic optimization algorithm to dynamically adjust task priority and resource allocation strategies.

[0063] Preferably, the project management system also includes: a system integration and expansion module, which is used to divide the system into multiple independent services, ensure modular design, and use an API gateway to manage communication and service discovery between modules.

[0064] In some embodiments, the project management system further includes: a collaboration and communication module, which provides a collaboration platform between team members, supports task assignment, progress tracking and communication. Key technologies: Real-time communication technology (such as WebSocket) ensures instant information transmission. Collaboration tool integration (such as Jira, Trello, etc.) improves work efficiency. Input: task assignment information, team member feedback. Output: collaboration interface and communication records.

[0065] In some embodiments, the project management system further includes: a real-time monitoring and feedback module to track project progress in real time and provide data visualization and risk warning functions. Key technologies: Data visualization tools (such as Tableau, PowerBI) display project status. Predictive analysis algorithms (such as machine learning models) are used for risk identification. Input: real-time project data. Output: project progress report, risk warning information.

[0066] In some embodiments, the project management system further includes: a user interface and interaction module, which provides a user-friendly user interface to facilitate users to view project status, adjust task assignments, and obtain feedback. Key technologies: Front-end frameworks (such as React, Vue.js) build intuitive user interfaces. Back-end services (such as RESTful APIs) support data interaction. Input: user operation instructions. Output: dynamically updated project views and interactive feedback.

[0067] The system automatically identifies task modules and their dependencies through knowledge graph technology, significantly reduces manual intervention, improves the efficiency and accuracy of task decomposition, dynamically adjusts task priorities and resource allocation based on real-time data, improves team collaboration efficiency, and significantly improves team collaboration efficiency through intelligent collaboration platforms and real-time communication tools.

[0068] Figure 5 It is a schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0069] The project management method provided in the embodiment of the present application can be applied to electronic devices. It will be appreciated by those skilled in the art that the electronic device structure involved in the embodiment of the present invention does not constitute a limitation on the electronic device, and the electronic device may include more or less components than shown, or combine certain components, or different component arrangements. In an embodiment of the present invention, the electronic device includes but is not limited to a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples, and are not intended to limit the implementation of the embodiments of the present application described herein and / or required.

[0070] The electronic device may include a processor, an external memory interface, an internal memory, a universal serial bus (USB) interface, a charging management module, a power management module, a battery, a wireless communication module, an audio module, a speaker, a microphone, a sensor module, buttons, a camera, a display, and a SIM card interface, etc.

[0071] It is to be understood that the structure illustrated in the embodiments of the present application does not constitute a specific limitation on the electronic device. In other embodiments of the present application, the electronic device may include more or fewer components than shown in the figure, or combine certain components, or split certain components, or arrange the components differently. The components shown in the figure may be implemented in hardware, software, or a combination of software and hardware.

[0072] The processor may include one or more processing units, for example, the processor may include a central processing unit (CPU), an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units may be independent devices or integrated into one or more processors.

[0073] The processor can be the nerve center and command center of the electronic device. The controller can generate an operation control signal according to the instruction operation code and timing signal to complete the control of fetching and executing instructions.

[0074] A memory may also be provided in the processor for storing instructions and data. In some embodiments, the memory in the processor is a cache memory. The memory may store instructions or data that the processor has just used or is cyclically used. If the processor needs to use the instruction or data again, it may be directly called from the memory. This avoids repeated access, reduces the waiting time of the processor, and thus improves system efficiency.

[0075] The external memory interface can be used to connect an external memory card, such as a MicroSD card, to expand the storage capacity of the electronic device. The external memory card communicates with the processor through the external memory interface to implement data storage functions. For example, files such as music and videos can be saved in the external memory card.

[0076] The internal memory can be used to store computer executable program codes, which include instructions. The processor executes various functional applications and data processing of the electronic device by running the instructions stored in the internal memory. The internal memory may include a program storage area and a data storage area. The internal memory may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, a universal flash storage (UFS), etc.

[0077] The wireless communication function of an electronic device can be realized through an antenna, a wireless communication module, a modem processor, and a baseband processor.

[0078] The wireless communication module can provide wireless communication solutions for electronic devices, including wireless local area networks (WLAN) (such as wireless fidelity (Wi-Fi) networks), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared technology (IR), etc.

[0079] Electronic devices can implement audio functions, etc. through audio modules, speakers, receivers, microphones, headphone jacks, and application processors.

[0080] Electronic devices can achieve shooting functions through ISP, camera, video codec, GPU, display and application processor.

[0081] Electronic devices can achieve display functions through GPU, display screen and application processor.

[0082] The GPU is a microprocessor for image processing that connects the display screen and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. The processor may include one or more GPUs that execute program instructions to generate or change display information.

[0083] The display screen is used to display images, videos, etc. The display screen includes a display panel.

[0084] The storage medium provided in the present application stores a program product capable of implementing the project management method.

[0085] The project management method includes: collecting project-related data, organizing and cleaning the project-related data to obtain a structured data set; using entity recognition and relationship extraction algorithms to perform entity labeling and relationship extraction processing on the structured data set to construct a project-related knowledge graph; based on the knowledge graph, using a graph traversal algorithm to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priorities and resource allocation strategies.

[0086] In some possible implementations, the subject-name project management method and system of the present disclosure may be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary implementations of the present disclosure described in the above “Exemplary Method” section of this specification.

[0087] The storage medium of the present disclosure can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0088] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A project management method, characterized in that: include: Collect project-related data, organize and clean the project-related data, and obtain a structured data set; Using entity recognition and relationship extraction algorithms, the structured data set is subjected to entity labeling and relationship extraction processing to construct a knowledge graph related to the project; Based on the knowledge graph, a graph traversal algorithm is used to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priority and resource allocation strategies.

2. The project management method according to claim 1, characterized in that: Collect project-related data, organize and clean the project-related data, and obtain a structured data set, including: Collecting project-related data from multiple sources, wherein the project-related data includes but is not limited to project goals, task descriptions, resource requirements, and team member skills; Use NLP natural language processing technology to extract key information from project-related data, perform data cleaning, and convert unstructured data into structured data to ensure the consistency and integrity of the data format.

3. The project management method according to claim 1, characterized in that: Entity recognition and relationship extraction algorithms are used to perform entity labeling and relationship extraction on the structured data set to construct a project-related knowledge graph, including: Based on predetermined project entities, domain terms in the structured data set are screened out and a domain term list is generated; Define an entity label set, a relationship label set, and labeling constraint rules, label the structured data set, and obtain labeled data; Perform entity mask enhancement on structured datasets, extract entity, attribute, and relation triplets from labeled data, and construct relation pre-training corpus; A dual-branch encoder is constructed based on the relational pre-training corpus and the BERT-base model, wherein the dual-branch encoder includes an entity branch encoder and a relation branch encoder, wherein the entity branch encoder is used to access the Token-level input and output the entity label distribution, and the relation branch encoder is used to receive the entity pair plus context input and output the relation classification probability; Input the labeled data into a dual-branch encoder, perform character-level alignment, and generate a Token label mapping table; Based on the Token tag mapping table, string matching and synonym merging are performed, and attribute value verification is used to build a project-related knowledge graph.

4. The project management method according to claim 1, characterized in that: Based on the knowledge graph, a graph traversal algorithm is used to decompose tasks, generate a task list and its priority order, and based on a dynamic optimization algorithm, monitor task progress and resource utilization in real time to dynamically adjust task priorities and resource allocation strategies, including: A directed acyclic graph is generated based on the resource dependency attributes and execution time weights of the task nodes, and a task dependency matrix is ​​established during the task list generation process. Conflict detection is performed on task nodes with resource competition, and mutually exclusive access to shared resources is ensured by inserting virtual synchronization nodes. Task priorities are sorted based on the product of the node out-degree value and the weighted path duration. Construct a multi-dimensional monitoring vector of task progress deviation, resource utilization entropy value and node load balancing factor, and trigger priority re-evaluation when the task progress deviation, resource utilization entropy value and node load balancing factor all exceed the preset threshold; The dynamic adjustment of resource configuration strategy includes resource preemptive reallocation, which preempts the reserved resources of low-priority tasks according to the urgency index of lagging tasks, and records the resource borrowing and lending relationship for subsequent compensation scheduling, wherein the urgency index is determined by the ratio of the square of the remaining workload to the elasticity of the remaining resources.

5. The project management method according to claim 1, characterized in that: The project management method also includes: Assign optimized tasks to the appropriate team members and use collaborative tools to track task progress; Use real-time communication technology to ensure instant information transmission between team members; Design collaborative interfaces to display task assignments, progress updates, and communication records.

6. The project management method according to claim 1, characterized in that: The project management method also includes: Use front-end frameworks to build user interfaces and set different access permissions based on user roles; Supports users to adjust task priorities or reallocate resources through release operations.

7. A project management system, characterized in that: include: The data collection and preprocessing module is used to collect project-related data, and to preliminarily organize and clean the project-related data to obtain a structured data set; A knowledge graph construction module, which is used to use entity recognition and relationship extraction algorithms to perform entity labeling and relationship extraction processing on the structured data set to construct a knowledge graph related to the project; The task decomposition and optimization module is used to perform task decomposition based on the knowledge graph using a graph traversal algorithm, generate a task list and its priority order, and monitor task progress and resource utilization in real time based on a dynamic optimization algorithm to dynamically adjust task priority and resource allocation strategies.

8. The project management system according to claim 7, characterized in that: The project management system also includes: The system integration and extension module is used to divide the system into multiple independent services, ensure modular design, and use the API gateway to manage communication and service discovery between modules.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the project management method according to any one of claims 1 to 6 are implemented.

10. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the project management method according to any one of claims 1 to 6 are implemented.

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