Project management system and method

Abstract

The invention relates to the technical field of computers, and relates to a project management system and method. Wherein the declaration module is configured to respond to a template selection operation, load a form and fill in guide information, verify the writing content of the form, and generate a project declaration according to the filled content passing the verification; the collaborative approval module is configured to determine a target approval mode, send the project declaration to an approval role according to the target approval mode, record approval operation information and timestamp information of the approval role, and obtain an approval result and approval chain information; the contract generation module is configured to extract approval key information to determine a target term and fill a contract template, and output a finalized contract; the task disassembling module is configured to determine tasks, a dependency relationship and performance nodes according to a finalization contract, generate a project Gantt chart, and allocate the tasks in response to a confirmation operation on the project Gantt chart; the risk assessment module is configured to perform risk assessment; and the acceptance management module is configured to perform project acceptance.

Description

Technical Field

[0001] This disclosure relates to the field of computer technology, and more specifically, to a project management system and a project management method. Background Technology

[0002] In current project management practices, especially in fields such as scientific research, engineering construction, and complex product development, projects typically involve multiple stages. Traditional management methods heavily rely on manual operations, such as information transmission and approval via paper documents or basic office software, resulting in low efficiency throughout the process and the potential for information silos between different stages. Therefore, there is an urgent need for an integrated and automated management approach that enables the entire project lifecycle.

[0003] It should be noted that the information in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this disclosure is to provide a project management system, project management method, computer program product, and electronic device, thereby achieving integrated, automated, and intelligent management of the entire project lifecycle and improving the efficiency and accuracy of project management.

[0005] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part by practice of this disclosure.

[0006] According to one aspect of this disclosure, a project management system is provided, comprising an application module, a collaborative approval module, a contract generation module, a task breakdown module, a risk assessment module, and an acceptance management module. The application module is configured to, in response to a selection operation for a target project template, load a structured electronic form and filling guidance information, and perform compliance verification on the content entered into the structured electronic form to generate a project application form based on the verified content. The collaborative approval module is configured to, in response to a selection operation for an approval method of the project application form, determine the target approval method, send the project application form to the corresponding approval role according to the target approval method, and record the approval operation information and timestamp information of each approval role for the project application form to obtain the approval result and approval chain information. The contract generation module is configured to extract key approval information based on the project category and approval result of the project application form. The system is divided into three modules: 1) **Contract Template Management:** Based on key approval information, the module determines target clauses from the contract clause library and populates the contract template according to the project application, target clauses, and approval results, outputting the final contract. 2) **Task Decomposition:** Based on the final contract, the module identifies multiple tasks, their dependencies, and performance milestones. It generates and displays a project Gantt chart based on these tasks, and in response to confirmation of the Gantt chart, assigns multiple tasks to corresponding execution objects. 3) **Risk Assessment:** The module collects execution data characteristics of multiple tasks, performs risk assessments based on these characteristics, determines risk assessment results across multiple dimensions, and monitors the execution of multiple tasks based on the risk assessment results, obtaining monitoring results. 4) **Acceptance Management:** Based on the final contract, monitoring results, and task execution information, the module performs project acceptance to generate an acceptance report.

[0007] In one exemplary embodiment of this disclosure, the application module includes: a template library unit, configured to predefine multiple project templates based on project type and user role, and to retrieve template metadata from a cloud template database in real time using an asynchronous loading method, in response to a selection operation for a target project template, loading a structured electronic form and its filling guidance information by parsing the template metadata of the target project template; and a verification unit, configured to perform multi-level compliance verification on the content filled in the structured electronic form, and to generate a project application form based on the content filled in after all verification levels have passed.

[0008] In one exemplary embodiment of this disclosure, the multi-level compliance verification includes primary verification, intermediate verification, and advanced verification. The verification unit is configured to: perform language checks and data type verification on the filled content to achieve primary verification; perform business logic consistency verification on the filled content by calling the rule engine to achieve intermediate verification; and analyze the semantic compliance of the filled content using a natural language processing model and compare it with historical project data to perform anomaly detection to achieve advanced verification. If any verification level among primary, intermediate, and advanced verification fails, the verification unit is also configured to highlight the verification error and correction suggestions through a real-time feedback interface.

[0009] In one exemplary embodiment of this disclosure, the verification unit is further configured to: generate filling guidance information for the structured electronic form using a pre-trained information generation model based on the project type and the structured electronic form; wherein the pre-trained information generation model is obtained by training based on sample data of historical projects, forms and filling information.

[0010] In one exemplary embodiment of this disclosure, the collaborative approval module includes: an approval strategy parsing unit configured to provide a graphical interface to present multiple predefined approval methods, and in response to the user's approval method selection operation, determine the target approval method, the predefined approval methods including serial approval, parallel approval, hybrid approval, and custom approval; a dynamic routing unit configured to parse the target approval method, obtain an approval role sequence, and send the project application to the corresponding approval role according to the approval role sequence; and an operation recording unit configured to monitor and obtain the approval operation information of each approval role, and establish an association between each approval operation information and timestamp information to obtain the approval result and approval chain information.

[0011] In one exemplary embodiment of this disclosure, the contract generation module includes: an information extraction unit configured to extract first key information from structured fields in a project application form using predefined mapping rules, and to perform intent recognition on unstructured data in the approval results based on a pre-trained intent recognition model, generating second key information from the intent recognition results, so as to generate a contract data package from the first and second key information; a clause recommendation unit configured to determine target clauses from a contract clause library based on the project category and contract data package in the project application form; a contract synthesis unit configured to fill in a contract template based on the project application form, target clauses, and approval results, output a finalized contract, and add a version number to each version of the finalized contract; and a contract review unit configured to perform completeness and standardization checks on the finalized contract.

[0012] In one exemplary embodiment of this disclosure, the clause recommendation unit is configured to: determine candidate clauses in the corresponding preset business rules in the contract clause library based on the project category and contract data package; obtain reference clauses adopted by historical contract data corresponding to the project category, verify the candidate clauses based on the reference clauses, and determine the candidate clauses that pass the verification as target clauses.

[0013] In one exemplary embodiment of this disclosure, the task decomposition module includes: a contract parsing unit configured to decompose the finalized contract into tasks based on a predefined task knowledge base, identify multiple tasks, and extract performance nodes from the finalized contract; a dependency modeling unit configured to perform logical association analysis on multiple tasks to establish dependencies between multiple tasks based on the analysis results; a graph generation unit configured to generate a task mesh graph based on the dependencies, and determine the start time of each task based on the task information and performance nodes of each task, so as to integrate and render multiple tasks, dependencies between tasks, and start times in the task mesh graph to obtain a project Gantt chart; and a task allocation unit configured to present the project Gantt chart and, in response to a confirmation operation on the project Gantt chart, allocate multiple tasks to corresponding execution objects for task execution.

[0014] In one exemplary embodiment of this disclosure, the risk assessment module includes: a data processing unit configured to collect execution data features and clean the execution data features to obtain a standard feature set; and a risk assessment unit configured to use a risk assessment model corresponding to different risk dimensions to assess the standard feature set from different dimensions to obtain risk indicators corresponding to different risk dimensions, and monitor the execution status of multiple tasks based on the risk indicators of each risk dimension to obtain monitoring results.

[0015] According to one aspect of this disclosure, a project management method is provided, applied to a project management system. The system includes a declaration module, a collaborative approval module, a contract generation module, a task breakdown module, a risk assessment module, and an acceptance management module. The method includes: In response to a selection operation for a target project template via the declaration module, loading a structured electronic form and filling guidance information, and performing compliance verification on the content entered into the structured electronic form to generate a project declaration form based on the verified content; In response to a selection operation for an approval method for the project declaration form via the collaborative approval module, determining the target approval method, sending the project declaration form to the corresponding approval role according to the target approval method, and recording the approval operation information and timestamp information of each approval role for the project declaration form to obtain the approval result and approval chain information; The contract generation module, based on the project category and approval result of the project declaration form, loads a structured electronic form and fills in the target project template selection operation, and performs compliance verification on the content entered into the structured electronic form, and generates a project declaration form based on the approved content; In response to a selection operation for an approval method for the project declaration form via the collaborative approval module, determining the target approval method, and sending the project declaration form to the corresponding approval role, and recording the approval operation information and timestamp information of each approval role for the project declaration form to obtain the approval result and approval chain information; In response to a selection operation for an approval method for the project declaration form via the collaborative approval module, determining the target approval method, and sending the project declaration form to the corresponding approval role according to the target approval method, and performing compliance verification on the target project template selection operation, and generating a project declaration form based on the target project template selection operation, and performing a project declaration operation ... The process involves: extracting key approval information; determining target clauses from the contract clause library based on this information; filling the contract template with the project application, target clauses, and approval results; outputting the finalized contract; using the task decomposition module to identify multiple tasks, their dependencies, and performance milestones based on the finalized contract; generating and displaying a project Gantt chart based on these tasks, dependencies, and performance milestones; and assigning tasks to corresponding execution objects in response to confirmation of the Gantt chart; collecting execution data characteristics of multiple tasks through the risk assessment module; conducting risk assessments based on these characteristics; determining risk assessment results across multiple dimensions; and monitoring the execution of multiple tasks based on these results; and finally, using the acceptance management module to conduct project acceptance based on the finalized contract and monitoring results, generating an acceptance report.

[0016] According to one aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements any of the above methods.

[0017] According to one aspect of this disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to perform any of the above methods by executing the executable instructions.

[0018] The project management system and method in the exemplary embodiments of this disclosure, on the one hand, ensure the standardization and completeness of the application information through the structured electronic forms and compliance verification of the application module, reducing errors and rework from the source. The collaborative approval module, through the selection of approval methods and automatic distribution, can adapt to the approval processes of different projects, avoiding delays caused by offline transmission and improving approval efficiency. The contract generation module, by automatically extracting key approval information and matching it with the contract clause library, can achieve rapid and accurate contract generation, significantly shortening contract preparation time. The task decomposition module not only generates a task list but also clarifies the dependencies and performance nodes of the tasks and generates a project Gantt chart, facilitating the overall planning of resources and schedules. The risk assessment module performs dynamic risk assessment based on real-time execution data characteristics, enabling managers to gain insights into project health from multiple dimensions and shift from post-event remediation to pre-event warning and in-event intervention. On the other hand, the approval operation information and timestamp information recorded by the collaborative approval module form a complete approval chain information, providing a reliable data foundation for auditing and accountability. The task decomposition module assigns tasks to corresponding execution objects, clarifying the responsible parties. The continuous monitoring function of the risk assessment module enables managers to promptly identify deviations and potential problems, thereby quickly adjusting resources or strategies and reducing the risk of project failure. Therefore, this disclosed embodiment, through the organic synergy and data linkage of various functional modules, constructs an efficient, transparent, controllable, and intelligent project management ecosystem. This significantly reduces manual intervention and repetitive work, improves the scientific nature of decision-making, and ultimately ensures the quality and efficiency of the entire project process from initiation to completion.

[0019] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0020] The above and other objects, features, and advantages of this disclosure will become readily apparent from the following detailed description of exemplary embodiments, taken in conjunction with the accompanying drawings. Several embodiments of this disclosure are illustrated in the drawings by way of example and not limitation.

[0021] Figure 1 A schematic diagram of a project management system according to an exemplary embodiment of the present disclosure is shown.

[0022] Figure 2 A schematic diagram of a filing module according to an exemplary embodiment of the present disclosure is shown.

[0023] Figure 3 A flowchart of the execution steps of a verification unit according to an exemplary embodiment of the present disclosure is shown.

[0024] Figure 4 A schematic diagram of a collaborative approval module according to an exemplary embodiment of the present disclosure is shown.

[0025] Figure 5 A schematic diagram of a contract generation module according to an exemplary embodiment of the present disclosure is shown.

[0026] Figure 6 A schematic diagram of a task breakdown module according to an exemplary embodiment of the present disclosure is shown.

[0027] Figure 7 A flowchart of a project management method according to an exemplary embodiment of the present disclosure is shown.

[0028] Figure 8 A block diagram of an electronic device according to an exemplary embodiment of the present disclosure is shown.

[0029] In the accompanying drawings, the same or corresponding reference numerals indicate the same or corresponding parts. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be more comprehensive and complete, and will fully convey the concept of exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and therefore their detailed description will be omitted.

[0031] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced without one or more of the specific details described, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known structures, methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this disclosure.

[0032] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, or in one or more software-hardened modules, or in different network and / or processor devices and / or microcontroller devices.

[0033] Traditional management methods heavily rely on manual operations, such as information transmission and approval via paper documents or basic office software, resulting in low efficiency throughout the process and the potential for information silos between different stages. Specifically, firstly, the application and approval processes are cumbersome and lack standardization, easily leading to rework due to non-standard forms or missing information; secondly, the various stages are often disconnected, relying on the manual experience and judgment of managers, which not only results in a large workload but also makes it difficult to ensure consistency and accuracy; finally, due to the lack of end-to-end data integration and linkage, managers cannot grasp the project status in real time and comprehensively, making it difficult to conduct effective risk warnings and accurate decision-making, thus affecting the overall execution efficiency and success rate of the project.

[0034] Based on this, the exemplary embodiments of this disclosure provide a project management system that, through the organic collaboration and data linkage of various functional modules, constructs an efficient, transparent, controllable and intelligent project management ecosystem. This system can significantly reduce manual intervention and repetitive work, improve the scientific nature of decision-making, and ultimately ensure the quality and efficiency of the entire project process from initiation to completion.

[0035] It should be noted that the project management system provided by the exemplary embodiments of this disclosure can be applied to the management of science and technology projects in large enterprise groups or R&D centers, as well as to the management of scientific research projects in universities and research institutes, and can also be applied to scenarios such as the management of science and technology projects by government science and technology management departments and innovation platforms. It can achieve integrated, automated, and intelligent management of the entire project lifecycle, improving the efficiency and accuracy of project management. The exemplary embodiments of this disclosure can be applied to application scenarios including but not limited to those described above.

[0036] like Figure 1 The diagram shown is a schematic representation of a project management system according to an exemplary embodiment of this disclosure. (Refer to...) Figure 1 As shown, the project management system 100 includes: Application module 110 is configured to load a structured electronic form and filling guidance information in response to the selection operation of the target project template, and to perform compliance verification on the content filled in the structured electronic form in order to generate a project application form based on the content that passes the verification. The collaborative approval module 120 is configured to respond to the selection of the approval method for the project application form, determine the target approval method, send the project application form to the corresponding approval role according to the target approval method, and record the approval operation information and timestamp information of each approval role for the project application form in order to obtain the approval result and approval chain information. The contract generation module 130 is configured to extract key approval information based on the project category and approval results of the project application, determine the target clauses from the contract clause library based on the key approval information, and fill in the contract template based on the project application, target clauses, and approval results to output the final contract. The task decomposition module 140 is configured to determine multiple tasks, their dependencies, and performance nodes based on the finalized contract, generate and display a project Gantt chart based on the multiple tasks, their dependencies, and performance nodes, and, in response to the confirmation operation of the project Gantt chart, assign multiple tasks to the corresponding execution objects to perform the tasks. The risk assessment module 150 is configured to collect the execution data characteristics of multiple tasks, perform risk assessment based on the execution data characteristics, determine the risk assessment results in multiple dimensions, and monitor the execution status of multiple tasks based on the risk assessment results to obtain the monitoring results. The Acceptance Management module 160 is configured to conduct project acceptance based on the finalized contract and monitoring results, in order to generate an acceptance report.

[0037] The project management system and method in the exemplary embodiments of this disclosure, on the one hand, ensure the standardization and completeness of the application information through the structured electronic forms and compliance verification of the application module, reducing errors and rework from the source. The collaborative approval module, through the selection of approval methods and automatic distribution, can adapt to the approval processes of different projects, avoiding delays caused by offline transmission and improving approval efficiency. The contract generation module, by automatically extracting key approval information and matching it with the contract clause library, can achieve rapid and accurate contract generation, significantly shortening contract preparation time. The task decomposition module not only generates a task list but also clarifies the dependencies and performance nodes of the tasks and generates a project Gantt chart, facilitating the overall planning of resources and schedules. The risk assessment module performs dynamic risk assessment based on real-time execution data characteristics, enabling managers to gain insights into project health from multiple dimensions and shift from post-event remediation to pre-event warning and in-event intervention. On the other hand, the approval operation information and timestamp information recorded by the collaborative approval module form a complete approval chain information, providing a reliable data foundation for auditing and accountability. The task decomposition module assigns tasks to corresponding execution objects, clarifying the responsible parties. The continuous monitoring function of the risk assessment module enables managers to promptly identify deviations and potential problems, thereby quickly adjusting resources or strategies and reducing the risk of project failure. Therefore, this disclosed embodiment, through the organic synergy and data linkage of various functional modules, constructs an efficient, transparent, controllable, and intelligent project management ecosystem. This significantly reduces manual intervention and repetitive work, improves the scientific nature of decision-making, and ultimately ensures the quality and efficiency of the entire project process from initiation to completion.

[0038] The following provides a more detailed explanation of each of the above modules.

[0039] Application module 110 is configured to load a structured electronic form and filling guidance information in response to the selection operation of the target project template, and to perform compliance verification on the content filled in the structured electronic form in order to generate a project application form based on the content that passes the verification.

[0040] The target project templates are standardized format frameworks pre-installed in the system, designed for different types or sources of projects. Each template is associated with specific application requirements, review criteria, and procedures. Examples include templates for the National Natural Science Foundation of China and templates for new product development by enterprises. The user's selection determines the form structure, guidance information, and validation rules that are subsequently loaded. Structured electronic forms are electronic forms that break down form content into multiple predefined, machine-recognizable and processable fields or data units. These may include, but are not limited to, structured fields such as project name, project type, start and end dates, project funding, and technical specifications, providing a foundation for subsequent automated processing (such as validation, information extraction, and contract generation). Filling guidance information is real-time, contextualized guidance provided to assist users in accurately filling out forms. This guidance can take the form of floating reminders, such as displaying instructions for filling out a field when the mouse hovers over it; sample text, such as displaying standard filling examples in or next to the input box; or format indicators, such as clearly indicating the format requirements for dates, amounts, etc., such as YYYY year-MM month-DD day, etc. Compliance verification refers to automatically checking the legality, completeness, and logical consistency of input data during the user's filling process or submission. The project application form is the final, officially generated application document that conforms to the required format.

[0041] In one exemplary embodiment, such as Figure 2 As shown, the application module 110 includes a template library unit 1101 and a verification unit 1102, wherein: Template library unit 1101 is configured to predefine multiple project templates based on project type and user role, and uses asynchronous loading to retrieve template metadata from the cloud template database in real time. In response to the selection operation of the target project template, it loads structured electronic forms and structured electronic form filling guidance information by parsing the template metadata of the target project template.

[0042] The template library unit 1101 is the core component of the application module responsible for project template management, retrieval, and loading. Project types and user roles define access and usage permissions for templates. By predefining templates for different project types and user roles, fine-grained management and access control of templates can be achieved. Asynchronous loading means that after sending a data request to the server, the user interface is not blocked while waiting for a response; instead, it can continue to respond to other user operations. When the data is returned, a callback function updates a specific part of the page. The cloud template library is a database stored on a cloud server (not a local server) that centrally manages all project templates and their information. Template metadata is used to represent structured information about the template's attributes, including but not limited to defining the fields, types, validation rules, template version number, and list of available user roles for structured electronic forms.

[0043] Specifically, when a user enters the system, the template library unit 1101 first filters and displays a list of available templates based on the user's role and project type. After the user selects an action, the system responds by asynchronously sending a request to the cloud-based template database to retrieve the template's metadata in real time. Upon receiving the template metadata, the system parses it and renders the various fields of the structured electronic form on the page based on the parsing results, injecting guidance information for filling it out. For example, the `formSchema` and `guideInfo` fields in the template metadata can be parsed.

[0044] The verification unit 1102 is configured to perform multi-level compliance verification on the content filled in the structured electronic form, and generate a project application form based on the content filled in after all verification levels have passed.

[0045] Verification unit 1102 is the core component in the declaration module responsible for ensuring data quality and compliance. Multi-level compliance verification refers to dividing the verification process into multiple levels that are performed sequentially or triggered by conditions, each level having different verification granularity and purpose. Only after all levels of verification have passed is the project proposal generated based on the verified information.

[0046] In one exemplary embodiment, the multi-level compliance verification includes primary verification, intermediate verification, and advanced verification. For example... Figure 3 As shown, the verification unit 1102 is configured to perform: Step S310: Perform language checks and data type validation on the entered content to achieve basic validation.

[0047] Basic validation is the most fundamental level of checking the format and standardization of the data itself. Language checks can be performed on text fields, such as checking for sensitive words, prohibited words, or whether they conform to basic language standards, such as not consisting entirely of meaningless gibberish. Data type validation ensures that the input data matches the preset field types. For example, an ID number field must be an 18- or 15-digit number plus specific letters; an email field must contain the "@" symbol; a budget field must be a positive number; and a date field must conform to the "YYYY-MM-DD" format.

[0048] Step S320: Perform business logic consistency verification on the filled content by calling the rule engine to achieve intermediate verification.

[0049] Intermediate-level validation checks whether multiple data fields conform to preset business rules and logical relationships. The rule engine is an independent, configurable component that separates business rules from program code, allowing non-technical personnel to define, manage, and modify these rules through a graphical interface or scripting language. For example, labor cost percentage ≤ aa%. Users can adjust the rules in the rule engine through manual writing, function selection, etc., in the graphical interface, and can flexibly configure them according to actual scenario needs. This embodiment does not impose specific limitations on this.

[0050] Step S330: Use a natural language processing model to analyze the semantic compliance of the filled content and compare it with historical project data to perform anomaly detection in order to achieve advanced verification.

[0051] Advanced verification involves steps for semantic compliance and anomaly detection. The natural language processing (NLP) model is trained using sample data from the project application domain. This NLP model can be constructed using lightweight neural networks such as CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), and DNNs (Deep Neural Networks). Alternatively, more complex NLP models can be used, such as heavyweight neural networks like BERT (Bidirectional Encoder Representation from Transformers), Transformer (a language processing model), or any heavyweight neural network suitable for NLP. Furthermore, the NLP model can be a large-scale model with hundreds of millions of records. An LLM (Large Language Model) refers to a deep learning model trained on a large amount of data that can generate natural language text or understand the meaning of language text. This disclosure does not specifically limit the specific network structure of the NLP model.

[0052] Semantic compliance involves checking whether the text content aligns with the requirements of that type of project. For example, a project applying for "energy informatization" might describe core technologies that are entirely related to agricultural product synthesis processes, constituting a semantic non-compliance. Comparing the submitted content with historical project data involves multi-dimensionally comparing the current application with a vast amount of data from completed or rejected projects to detect anomalies. This can be achieved through big data analysis. Anomalies may include, but are not limited to, inflated budgets, overly advanced or outdated technical approaches, and inappropriate team member configurations. For instance, an application for standard laboratory equipment with a budget several times higher than the historical average for similar projects would be flagged as an anomaly.

[0053] Optionally, if any of the primary, intermediate, and advanced verification levels fails, the verification unit is also configured to highlight the verification error and correction suggestions through a real-time feedback interface.

[0054] The real-time feedback interface is an interactive user interface that instantly presents the verification results to the user. For example, on the form interface, by changing colors (such as red borders), adding icons, or pop-up prompts, the specific fields with problems can be clearly indicated. Corrective suggestions can be determined based on predefined prompts in the rule engine or the analysis results based on the natural language processing model. In other words, the prompts corresponding to anomalies can be predefined in the rule engine, or the natural language processing model can be trained to provide corrective suggestions simultaneously.

[0055] If any of the above verification levels fails, the process will be immediately interrupted, and the error information will be returned to the user through a real-time feedback interface, reducing the user's understanding cost and modification threshold, and guiding the user to generate a high-quality application.

[0056] The exemplary embodiments disclosed herein constitute a system from format to logic to semantics through three levels of verification: primary, intermediate and advanced. This system can not only intercept low-level input errors, but also discover deep-seated business contradictions, discrepancies between text and title, and abnormal risks that deviate from historical norms, thus ensuring the integrity, accuracy and rationality of project application data from the source.

[0057] In one exemplary embodiment, the verification unit 1102 is further configured to perform: Based on the project type and structured electronic form, a pre-trained information generation model is used to generate guidance information for filling out the structured electronic form; the pre-trained information generation model is trained based on sample data of historical projects, forms, and filled-in information.

[0058] The pre-trained information generation model is trained on a large amount of general text data, such as sample data of historical projects, forms, and filled-in information. It can be a CNN, RNN, or large language model, and its network structure is not specifically limited. Historical projects are the basic information of various completed projects; forms are the electronic form structures corresponding to those historical projects; and filled-in information is the content actually filled in by the user in the historical forms, especially the high-quality content that ultimately passed the review. Through training or fine-tuning, the information generation model can generate personalized guidance information based on the specific context of the real-world scenario.

[0059] Specifically, when a user selects a project type and the system loads the corresponding structured electronic form, the system takes the project type and the metadata of the structured electronic form as input and passes them to a pre-trained information generation model. Based on its knowledge learned from historical sample data, the model performs real-time inference to generate the most relevant guidance information for each specific field of the current form. Optionally, the generated intelligent guidance information is injected into the user interface in real time, appearing alongside the corresponding form fields to assist the user in filling out the form.

[0060] Based on this, the applicability of guidance information in different scenarios can be improved, thereby guiding users to fill out electronic forms and improving filling efficiency and accuracy.

[0061] The collaborative approval module 120 is configured to respond to the selection of approval method for the project application form, determine the target approval method, send the project application form to the corresponding approval role according to the target approval method, and record the approval operation information and timestamp information of each approval role for the project application form, so as to obtain the approval result and approval chain information.

[0062] The approval method selection is an interactive action where users choose the subsequent approval process mode on the system interface after submitting a project application. This can be implemented through drop-down menus, radio button groups, or flowchart clicks. The target approval method is the final approved method. An approval role is an abstract identity decoupled from a specific approver, representing a certain approval responsibility or position, such as project manager, department manager, financial auditor, or developer. The system sends approval tasks to roles, and then assigns the tasks to specific users holding those roles according to preset rules or organizational structure. Approval operation information includes the specific actions performed by the approver and their accompanying metadata, including approval, rejection, return for modification, transfer, and the approval comments and modification suggestions filled in. Timestamp information records the time of each of the above operations, accurate to the second. The approval result is the final conclusion of the entire approval process. The approval chain information is a complete and orderly record of the entire approval process, including all approval roles, their approval operation information, and corresponding timestamps.

[0063] In one exemplary embodiment, such as Figure 4 As shown, the collaborative approval module 120 includes an approval strategy parsing unit 1201, a dynamic routing unit 1202, and an operation recording unit 1203. Specifically: The approval strategy parsing unit 1201 is configured to provide a graphical interface to present a variety of predefined approval methods. In response to the user's approval method selection operation, it determines the target approval method. The predefined approval methods include serial approval, parallel approval, mixed approval, and custom approval.

[0064] As mentioned above, the graphical interface can present various predefined approval methods, allowing users to select the desired method. Sequential approval sends tasks to the next approval role in a preset order; the next approver receives the task only after the previous approver has approved it, suitable for hierarchical approval systems. Parallel approval sends tasks to multiple approval roles simultaneously, independently and without blocking each other, suitable for scenarios requiring multiple departments to sign off. Hybrid approval combines sequential and parallel approaches, such as parallel signing followed by sequential signing to the final decision-maker. Custom approval allows users to freely draw approval flowcharts using graphical tools, defining nodes, branch conditions, and routing rules.

[0065] The dynamic routing unit 1202 is configured to parse the target approval method, obtain the approval role sequence, and send the project application to the corresponding approval role according to the approval role sequence.

[0066] The dynamic routing unit 1202 can transform the abstract approval method selected by the user into a series of specific instructions and node lists that the system can understand, thereby obtaining an approval role sequence, i.e., a directed graph structure with logical relationships. This clarifies the order, parallel relationships, and jump conditions of the approval roles. For example, if the financial approval is rejected, the process ends directly; if it is rejected in the preliminary review stage, the project review process begins directly. In parallel nodes, multiple tasks can be initiated simultaneously; in sequential nodes, subsequent tasks can be automatically triggered after the predecessor node completes, thus sending the approval task to the corresponding approval role.

[0067] The operation recording unit 1203 is configured to monitor and acquire the approval operation information of each approval role, and to establish a connection between each approval operation information and the timestamp information to obtain the approval result and approval chain information.

[0068] Monitoring and acquiring operations refers to the operation recording unit 1203 actively listening to all approval-related operation events in the system and capturing their detailed information. Furthermore, each approval operation information can be bound to timestamp information to form an indivisible and tamper-proof data unit, thus obtaining the atomic basis for the trusted approval chain information.

[0069] Specifically, throughout its entire lifecycle, the operation recording unit 1203 continuously monitors the system, acquiring approval operation information for each approval role. Simultaneously, it obtains precise timestamp information from the system server and establishes a correlation between the two. Based on all recorded operations, it automatically calculates the final approval result according to the rules of the approval strategy. Furthermore, it assembles all timestamped operation records into a complete and traceable approval chain information according to chronological order and logical relationships. The approval strategy rules, such as "approval by all" or "approval by one" respectively, can be flexibly set according to the actual approval method and role type in the scenario.

[0070] The exemplary embodiments disclosed herein transform complex approval process management into intuitive visual operations, enabling the system to quickly adapt to the approval needs of projects in different scenarios and at different levels. The system automatically sends tasks to the corresponding roles based on the approval role sequence, which helps improve approval efficiency, shorten project cycles, and avoids omissions and delays that may result from manual transmission.

[0071] The contract generation module 130 is configured to extract key approval information based on the project category and approval results of the project application, determine the target clauses from the contract clause library based on the key approval information, and fill in the contract template based on the project application, target clauses, and approval results to output the final contract.

[0072] The approval results include not only the final approval conclusion but also approval comments. These comments may contain key constraints of the finalized contract, such as a budget reduction of bb% or the need to add a CC clause. Key approval information refers to data automatically identified and extracted from the project application and approval chain that has a decisive impact on the contract content. This includes, but is not limited to, the project name, information about both parties, contract amount, project duration, deliverables list, and specific conditions imposed by the approver. The contract clause library is a structured, searchable database storing a large number of standardized, reusable contract clauses. Optionally, each clause includes metadata tags, such as clause type (e.g., payment method, confidentiality obligation, breach of contract liability), applicable project category, and effective conditions, to facilitate accurate matching. The contract template is a pre-defined document framework containing fixed text and variable placeholders, specifying the overall structure and format of the contract. The finalized contract is the final output, with all variables filled in, all clauses finalized, and ready for signing.

[0073] In one exemplary embodiment, such as Figure 5 As shown, the contract generation module 130 may include an information extraction unit 1301, a clause recommendation unit 1302, a contract synthesis unit 1303, and a contract review unit 1304, specifically: The information extraction unit 1301 is configured to extract first key information from the structured fields in the project application form through predefined mapping rules, and to perform intent recognition on the unstructured data in the approval result based on a pre-trained intent recognition model, and generate second key information from the intent recognition result, so as to generate a contract data package from the first key information and the second key information.

[0074] Structured fields refer to data units explicitly defined and directly readable in the project application, such as form fields like project amount, start date, and responsible person. Predefined mapping rules are predefined data extraction logic, such as mapping the value of the "total budget" field in the application to the "contract amount" in the contract data. Unstructured data refers to approval opinions in free text form in the approval results, such as budget reductions of dd%, or the need to add a confidentiality agreement, which have no fixed format. A pre-trained intent recognition model is used to understand the true intent or instructions behind the approval opinion text and transform it into structured key information. This model can be a CNN, RNN, or other network structure, which is not specifically limited in this embodiment. Specifically, the pre-trained intent recognition model can analyze unstructured data (such as approval opinions) to extract core instructions to generate second key information. Then, the first and second key information can be packaged to generate a contract data package containing all the key information required to generate the contract.

[0075] The clause recommendation unit 1320 is configured to determine target clauses from the contract clause library based on the project category and contract data package in the project application.

[0076] The contract terms library is a database that stores various standardized contract terms and their attributes, such as applicable scenarios and keyword tags for each contract term. Optionally, the terms recommendation unit 1302 can receive project categories and contract data packages, use project categories as the first-level filtering condition to initially select candidate terms from the contract terms library, and then use key information in the contract data package as the second-level filtering condition to determine the most applicable target terms through semantic matching or tag matching.

[0077] Optionally, the clause recommendation unit 1302 can be configured to perform: First, in the contract terms library, candidate terms in the corresponding pre-set business rules are determined based on the project category and contract data package; Then, the reference clauses used in the historical contract data corresponding to the project category are obtained, and the candidate clauses are verified based on the reference clauses. The candidate clauses that pass the verification are determined as the target clauses.

[0078] Pre-defined business rules are explicit, pre-defined logical judgment rules used to enforce or recommend the use of certain contract terms in specific business scenarios. These rules can be pre-set by legal or risk control experts, or compiled from relevant terms used in historical project proposals. Candidate terms are a set of terms initially selected from the contract term library by applying pre-defined business rules, applicable to the current contract at the rule level. Historical contract data is a database of successfully signed and executed past contracts accumulated by the system, including the contract text and the terms ultimately adopted. Reference terms are the most frequently used or most effective terms obtained from historical contract data through statistical analysis or machine learning models for the current project category. This allows for comparison and verification between rule-based candidate terms and data-based reference terms.

[0079] Specifically, the clause recommendation unit 1302 receives the project category and contract data package. Then, based on this input information, it executes the corresponding pre-set business rules in the contract clause library to quickly filter out candidate clauses that meet the hard requirements. Simultaneously, it acquires historical contract data of the same project category and extracts reference clauses through analysis. The candidate clauses are then compared with the reference clauses, such as through consistency checks and complementarity enhancement. Specifically, it checks whether the candidate clauses are consistent with the most commonly used clauses in historical practice (i.e., reference clauses), whether there are any excellent clauses in the reference clauses that are not covered by the rules but are widely used in practice, and whether they need to be added as candidate clauses. Finally, the candidate clauses that pass the verification are determined as the target clauses.

[0080] The exemplary embodiments of this disclosure, by combining pre-set business rules and historical contract data to determine target terms, can improve the accuracy and reliability of terms used in contracts.

[0081] Contract synthesis unit 1303 is configured to fill in the contract template based on the project application, target terms, and approval results, output the final contract, and add a version number to each version of the final contract.

[0082] The version number is an identifier used to uniquely identify and track each generation or modification record of a contract, and is used for contract version management. Specifically, the contract synthesis unit 1303 can automatically fill the basic information, target clauses, and approved data from the project application into the selected contract template, and automatically add a version number to the final contract while outputting the final contract.

[0083] Contract review unit 1304 is configured to perform integrity and standardization checks on the final draft of the contract.

[0084] Integrity verification checks whether all necessary variable placeholders in the finalized contract have been filled and whether there are blank chapters or missing attachments. Normative verification checks whether the contract format complies with the preset standards, whether the key contents are consistent, and whether the clause numbers are consecutive, etc. For example, whether the font, font size, header and footer comply with the preset standards.

[0085] Specifically, the contract review unit 1304 performs a final quality inspection on the generated finalized contract to ensure that there is no content missing and that the format is standardized and unified. Optionally, if the verification fails, it returns to the previous step and prompts an error; if successful, this version of the contract is determined to be the finalized contract that finally takes effect.

[0086] The exemplary embodiments of the present disclosure can obtain all key contract information from heterogeneous data sources without omission and accurately, and generate a structured contract data packet, avoiding the problem that the contract content is inconsistent with the approval intention due to manual interpretation deviation or omission, and ensuring the accuracy of contract intention restoration. And the applicable terms are determined based on specific project characteristics and approval requirements, which can improve the personalization and professionalism of the contract and effectively reduce legal risks.

[0087] The task decomposition module 140 is configured to determine multiple tasks, the dependency relationships of the multiple tasks, and performance nodes according to the finalized contract, generate and display a project Gantt chart based on the multiple tasks, the dependency relationships of the multiple tasks, and the performance nodes, and in response to a confirmation operation on the project Gantt chart, allocate the multiple tasks to corresponding execution objects to execute the tasks.

[0088] The multiple tasks are specific and operable work units decomposed to achieve the contract goal. Each task should have a clear description, deliverables, and estimated working hours. For example, complete the platform construction, conduct the first-stage test, etc. The dependency relationship is the logical sequence constraint in time between tasks. For example, after the previous task must be completed, the next task can start; after the previous task starts, the next task can start, and so on. The performance node is a key time point or milestone event agreed in the contract, which can be linked to payment, delivery or acceptance, and is a constraint point for project progress control. For example, deliver the design plan within 30 days after the contract is signed, pay the remaining contract payment after the overall project acceptance is qualified, and so on.

[0089] Among them, the project Gantt chart is a chart used to visually display the project plan, which can show the list of tasks, the start and end dates of tasks, the duration of tasks, the dependency relationships between tasks, and key performance nodes. The confirmation operation refers to the interactive behavior in which project managers review the Gantt chart plan automatically generated by the system and may perform manual fine-tuning, and finally approve the plan. The execution object is an individual, team or department responsible for completing a certain task.

[0090] In one exemplary embodiment, such as Figure 6 The task decomposition module 140 includes a contract parsing unit 1401, a dependency modeling unit 1402, a graph generation unit 1403, and a task allocation unit 1404, specifically: Contract parsing unit 1401 is configured to decompose the finalized contract into tasks based on a predefined task knowledge base, identify multiple tasks, and extract performance nodes from the finalized contract.

[0091] The predefined task knowledge base is a structured database that stores common task lists, task templates, and their attributes for different project types. Using this knowledge base, the content of a contract can be broken down into specific, executable tasks, such as scope of work and deliverables, through natural language processing or rule matching. Performance nodes can then be extracted from the contract text.

[0092] Dependency modeling unit 1402 is configured to perform logical association analysis on multiple tasks in order to establish dependencies between the multiple tasks based on the analysis results.

[0093] Logical association analysis refers to analyzing the inherent relationships between tasks and determining their sequence. For example, it might determine that construction drawings must be completed before construction. Task relationship reasoning can be performed using a pre-defined logical analysis model to derive the inherent connections. The network structure of this model is not specifically limited, and it can also be an open-source large language model.

[0094] The graph generation unit 1403 is configured to generate a task mesh graph based on dependencies, and determine the start time of each task based on the task information and fulfillment nodes of each task, so as to integrate and render multiple tasks, the dependencies between tasks and the start time in the task mesh graph to obtain a project Gantt chart.

[0095] A task mesh diagram is a graph data structure used for internal calculations to represent tasks and dependencies, serving as the data foundation for generating Gantt charts. Task information includes the estimated duration, required resources, and detailed description for each task. The start and end dates for each task are calculated using methods such as the critical path method, based on the constraints of dependencies and fulfillment milestones. Furthermore, all elements, including tasks, dependencies (e.g., represented by arrows), timelines, and start dates, can be comprehensively drawn into an intuitive project Gantt chart on a graphical interface.

[0096] The task assignment unit 1404 is configured to present a project Gantt chart and, in response to a confirmation operation on the project Gantt chart, assign multiple tasks to corresponding execution objects for task execution.

[0097] The confirmation action for the project Gantt chart can be an interactive action by which the operator approves the plan. This action can be triggered by clicking a function item, and there are no special limitations on it. Specifically, the task allocation unit 1404 presents the project Gantt chart. After the user reviews it and confirms it, the task allocation unit 1404 responds to this action by automatically assigning multiple tasks to the corresponding execution objects, and the tasks enter the execution phase.

[0098] The exemplary embodiments disclosed herein improve the accuracy and efficiency of task allocation through an automated pipeline for contract parsing, dependency modeling, and graph generation.

[0099] The risk assessment module 150 is configured to collect execution data characteristics of multiple tasks, perform risk assessment based on the execution data characteristics, determine risk assessment results in multiple dimensions, and monitor the execution status of multiple tasks based on the risk assessment results to obtain monitoring results.

[0100] Execution data characteristics are multi-dimensional, real-time / near real-time data generated during task execution that reflect the health of the task. These include, but are not limited to, schedule data, cost data, resource data, quality data, and communication data. Examples include percentage of planned completion, deviations from planned start / end times, actual work hours consumed, and differences between actual expenses and the budget. Based on execution data characteristics, risk assessments are conducted to predict the likelihood and impact of future task problems, such as schedule risk, cost risk, and quality risk.

[0101] In one exemplary embodiment, the risk assessment module 150 includes: The data processing unit is configured to collect execution data features and clean the execution data features to obtain a standard feature set.

[0102] The risk assessment unit is configured to use risk assessment models corresponding to different risk dimensions to assess the standard feature set from different dimensions, so as to obtain risk indicators corresponding to different risk dimensions, and monitor the execution of multiple tasks based on the risk indicators of each risk dimension to obtain monitoring results.

[0103] The data processing unit performs data cleaning, including but not limited to deduplication, data filling, data removal, and normalization. For different risk dimensions, historical data samples corresponding to that dimension can be used for model training to obtain risk assessment models for each dimension. For example, regression analysis can be used to predict completion dates, Monte Carlo simulation can be used to analyze delay probabilities, or a classification model can be built based on historical defect data for quality risk assessment. Furthermore, risk indicators corresponding to each risk dimension can be obtained.

[0104] Specifically, the data processing unit collects raw, multi-source execution data features from the project execution environment, cleans this raw data to remove impurities, standardizes it, and ultimately generates a high-quality standard feature set. Then, the risk assessment unit uses risk assessment models corresponding to different risk dimensions to assess the standard feature set from different perspectives. Each model operates independently, outputting risk indicators for its specialized dimension. For example, the schedule risk model outputs a delay rate of AA% for task A, and the cost risk model outputs a value excess index of 1.cc for task B, and so on. Based on this, the risk assessment unit monitors the execution status of multiple tasks throughout the project using risk indicators for each risk dimension. Optionally, risk indicators exceeding a certain preset threshold can be highlighted and communicated to relevant users.

[0105] The exemplary embodiments of this disclosure ensure the quality of the input model through data cleaning by the data processing unit, fundamentally improving the accuracy of risk indicators and the comparability of risks between different tasks. By using risk assessment models corresponding to different risk dimensions for parallel analysis, it is possible to accurately determine specific risks of a project in different aspects, thereby improving the overall accuracy of risk assessment.

[0106] The Acceptance Management module 160 is configured to accept projects based on the finalized contract, monitoring results, and task execution information to generate an acceptance report.

[0107] The finalized contract is the fundamental basis for acceptance. Project acceptance involves systematically comparing the final state of the project with the standards stipulated in the finalized contract, based on the finalized contract, monitoring results, and task execution information, to generate a structured and standardized acceptance conclusion document.

[0108] Specifically, the acceptance management module 160 can automatically extract all the clauses in the final contract that require acceptance, and compare the final delivery results of the project with all the clauses that require acceptance to determine the verification results.

[0109] It should be noted that although several modules or units of the project management system have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0110] The project management system and method in the exemplary embodiments of this disclosure, on the one hand, ensure the standardization and completeness of the application information through the structured electronic forms and compliance verification of the application module, reducing errors and rework from the source. The collaborative approval module, through the selection of approval methods and automatic distribution, can adapt to the approval processes of different projects, avoiding delays caused by offline transmission and improving approval efficiency. The contract generation module, by automatically extracting key approval information and matching it with the contract clause library, can achieve rapid and accurate contract generation, significantly shortening contract preparation time. The task decomposition module not only generates a task list but also clarifies the dependencies and performance nodes of the tasks and generates a project Gantt chart, facilitating the overall planning of resources and schedules. The risk assessment module performs dynamic risk assessment based on real-time execution data characteristics, enabling managers to gain insights into project health from multiple dimensions and shift from post-event remediation to pre-event warning and in-event intervention. On the other hand, the approval operation information and timestamp information recorded by the collaborative approval module form a complete approval chain information, providing a reliable data foundation for auditing and accountability. The task decomposition module assigns tasks to corresponding execution objects, clarifying the responsible parties. The continuous monitoring function of the risk assessment module enables managers to promptly identify deviations and potential problems, thereby quickly adjusting resources or strategies and reducing the risk of project failure. Therefore, this disclosed embodiment, through the organic synergy and data linkage of various functional modules, constructs an efficient, transparent, controllable, and intelligent project management ecosystem. This significantly reduces manual intervention and repetitive work, improves the scientific nature of decision-making, and ultimately ensures the quality and efficiency of the entire project process from initiation to completion.

[0111] In an exemplary embodiment of this disclosure, a project management method is also provided, applied to a project management system, namely... Figure 1 The system shown. (As shown in the image) Figure 7 This indicates that the project management methods may include: Step S710: In response to the selection of the target project template through the application module, load the structured electronic form and filling guidance information, and perform compliance verification on the content filled in the structured electronic form, so as to generate the project application form based on the content that passes the verification.

[0112] Step S720: In response to the project application form approval method selection operation through the collaborative approval module, determine the target approval method, send the project application form to the corresponding approval role according to the target approval method, and record the approval operation information and timestamp information of each approval role for the project application form to obtain the approval result and approval chain information.

[0113] Step S730: Based on the project category and approval results in the project application form, the contract generation module extracts key approval information, determines the target clauses from the contract clause library based on the key approval information, and fills in the contract template according to the project application form, target clauses, and approval results to output the final contract.

[0114] Step S740: Based on the finalized contract, the task decomposition module determines multiple tasks, their dependencies, and performance nodes. It then generates and displays a project Gantt chart based on the tasks, their dependencies, and performance nodes. In response to the confirmation operation on the project Gantt chart, the module assigns multiple tasks to their corresponding execution objects for execution.

[0115] Step S750: Collect execution data characteristics of multiple tasks through the risk assessment module, conduct risk assessment based on the execution data characteristics, determine risk assessment results in multiple dimensions, and monitor the execution status of multiple tasks according to the risk assessment results to obtain monitoring results.

[0116] Step S760: Use the acceptance management module to accept the project based on the finalized contract and monitoring results, and generate an acceptance report.

[0117] Since the detailed content of the project management method of the exemplary embodiments of this disclosure has been described in the exemplary embodiments of the various functional modules of the project management system described above, it will not be repeated here.

[0118] Exemplary embodiments of this disclosure also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the project management method described above.

[0119] In one implementation, the computer program product can be a tangible product containing a computer program, such as a computer-readable storage medium storing the computer program. The readable storage medium can be a storage medium based on electrical, magnetic, optical, electromagnetic, infrared, or other signals, including but not limited to: random access memory (RAM), read-only memory (ROM), magnetic tape, floppy disk, flash memory, hard disk drive (HDD), solid-state drive (SSD), etc. For example, the computer program product can be implemented as a non-volatile storage medium storing a computer program, such as read-only memory, NAND flash memory, etc.

[0120] In one implementation, the computer program product can be an intangible product containing a computer program. For example, the computer program product can be implemented as a virtual digital product, such as an executable file, installation package, or other digital file storing the computer program.

[0121] Computer program code can be written in one or more programming languages. The program code can execute entirely on the user's computing device, or partially on the user's computing device, or as a standalone software package, or partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device through any type of network, such as a local area network (LAN), a wide area network (WAN), etc., or it can be connected to an external computing device (e.g., through an internet connection provided by a mobile network operator).

[0122] Computer programs can be carried or transmitted via signals such as electricity, magnetism, light, electromagnetic fields, and infrared radiation. Electronic devices can convert the signals carrying computer programs into digital signals, thereby running the computer programs. When a computer program runs on an electronic device, its code is used to cause the electronic device to execute (more specifically, to execute) the method steps of various exemplary embodiments of this disclosure, such as the steps of the project management method described above.

[0123] Furthermore, in exemplary embodiments of this disclosure, an electronic device capable of implementing the above-described methods is also provided. Those skilled in the art will understand that various aspects of this disclosure can be implemented as systems, methods, or program products. Therefore, various aspects of this disclosure can be specifically implemented as: entirely hardware embodiments, entirely software embodiments (including firmware, microcode, etc.), or embodiments combining hardware and software aspects, collectively referred to herein as "circuit," "module," or "system."

[0124] The following reference Figure 8 To describe an electronic device 800 according to such an embodiment of the present disclosure. Figure 8 The electronic device 800 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments disclosed herein.

[0125] like Figure 8 As shown, the electronic device 800 is presented in the form of a general-purpose computing device. The components of the electronic device 800 may include, but are not limited to: at least one processing unit 810, at least one storage unit 820, a bus 830 connecting different system components (including storage unit 820 and processing unit 810), and a display unit 840.

[0126] The storage unit stores program code that can be executed by the processing unit 810, causing the processing unit 810 to perform the steps described in the "Exemplary Methods" section above, according to various exemplary embodiments of this disclosure.

[0127] Storage unit 820 may include readable media in the form of volatile storage units, such as random access memory (RAM) 821 and / or cache memory 822, and may further include read-only memory (ROM) 823. Storage unit 820 may also include a program / utility 824 having a set (at least one) of program modules 825, such program modules 825 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of these examples may include an implementation of a network environment.

[0128] Bus 830 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0129] Electronic device 800 can also communicate with one or more external devices 900 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 800, and / or with any device that enables electronic device 800 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 850. Furthermore, electronic device 800 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 860. As shown, network adapter 860 communicates with other modules of electronic device 800 via bus 830. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 800, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0130] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0131] Furthermore, the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of this disclosure and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Additionally, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0132] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This disclosure is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

Claims

1. A project management system, characterized in that, The system includes an application module, a collaborative approval module, a contract generation module, a task breakdown module, a risk assessment module, and an acceptance management module, wherein: The application module is configured to load a structured electronic form and filling guidance information in response to the selection operation of the target project template, and to perform compliance verification on the content filled in the structured electronic form in order to generate a project application form based on the content that passes the verification. The collaborative approval module is configured to respond to the approval method selection operation for the project application form, determine the target approval method, send the project application form to the corresponding approval role according to the target approval method, and record the approval operation information and timestamp information of each approval role for the project application form, so as to obtain the approval result and approval chain information. The contract generation module is configured to extract key approval information based on the project category of the project application and the approval result, determine target clauses from the contract clause library based on the key approval information, and fill in the contract template based on the project application, the target clauses, and the approval result to output the final contract. The task decomposition module is configured to determine multiple tasks, the dependencies between the multiple tasks, and the performance nodes according to the finalized contract, generate and display a project Gantt chart based on the multiple tasks, the dependencies between the multiple tasks, and the performance nodes, and, in response to a confirmation operation on the project Gantt chart, assign the multiple tasks to corresponding execution objects to perform the tasks. The risk assessment module is configured to collect the execution data characteristics of the multiple tasks, perform risk assessment based on the execution data characteristics, determine risk assessment results in multiple dimensions, and monitor the execution status of the multiple tasks according to the risk assessment results to obtain monitoring results. The acceptance management module is configured to conduct acceptance testing on the project based on the finalized contract, the monitoring results, and the task execution information, in order to generate an acceptance report.

2. The system according to claim 1, characterized in that, The application module includes: The template library unit is configured to predefine multiple project templates based on project type and user role, and uses an asynchronous loading method to retrieve template metadata from the cloud template database in real time. In response to the selection operation of the target project template, it loads the structured electronic form and the filling guidance information of the structured electronic form by parsing the template metadata of the target project template. The verification unit is configured to perform multi-level compliance verification on the content filled in the structured electronic form, and generate a project application form based on the content filled in after all verification levels have passed.

3. The system according to claim 2, characterized in that, The multi-level compliance verification includes primary verification, intermediate verification, and advanced verification, and the verification unit is configured as follows: The entered content is checked for language and validated for data type to achieve basic verification; Intermediate-level validation is achieved by calling the rules engine to perform business logic consistency checks on the filled-in content; The semantic compliance of the filled content is analyzed using a natural language processing model, and anomaly detection is performed by comparing it with historical project data to achieve advanced verification. If any of the primary, intermediate, and advanced verification levels fails, the verification unit is also configured to highlight the verification error and correction suggestions through a real-time feedback interface.

4. The system according to claim 2, characterized in that, The verification unit is further configured to: Based on the project type and the structured electronic form, a pre-trained information generation model is used to generate filling guidance information for the structured electronic form; The pre-trained information generation model is trained based on sample data of historical projects, forms, and filled-in information.

5. The system according to claim 1, characterized in that, The collaborative approval module includes: The approval strategy parsing unit is configured to provide a graphical interface to present a variety of predefined approval methods. In response to the user's approval method selection operation, it determines the target approval method. The predefined approval methods include serial approval, parallel approval, hybrid approval, and custom approval. The dynamic routing unit is configured to parse the target approval method, obtain the approval role sequence, and send the project application to the corresponding approval role according to the approval role sequence. The operation recording unit is configured to monitor and acquire the approval operation information of each approval role, and to establish a correlation between each approval operation information and the timestamp information in order to obtain the approval result and approval chain information.

6. The system according to claim 1, characterized in that, The contract generation module includes: The information extraction unit is configured to extract first key information from the structured fields in the project application form through predefined mapping rules, and to perform intent recognition on the unstructured data in the approval result based on a pre-trained intent recognition model, and to generate second key information from the intent recognition result, so as to generate a contract data package by combining the first key information and the second key information. The clause recommendation unit is configured to determine the target clause from the contract clause library based on the project category of the project application and the contract data package; The contract synthesis unit is configured to fill in the contract template based on the project application, the target terms, and the approval results, output the final contract, and add a version number to each version of the final contract; The contract review unit is configured to perform integrity and standardization checks on the finalized contract.

7. The system according to claim 6, characterized in that, The term recommendation unit is configured as follows: Based on the project category and the contract data package, candidate clauses in the corresponding pre-set business rules are determined in the contract clause library. The reference clauses used in the historical contract data corresponding to the project category are obtained, and the candidate clauses are verified based on the reference clauses. The candidate clauses that pass the verification are determined as the target clauses.

8. The system according to claim 1, characterized in that, The task breakdown module includes: The contract parsing unit is configured to decompose the finalized contract into tasks based on a predefined task knowledge base, determine the multiple tasks, and extract the performance nodes from the finalized contract. The dependency modeling unit is configured to perform logical association analysis on the multiple tasks in order to establish the dependency relationships between the multiple tasks based on the analysis results. The graph generation unit is configured to generate a task mesh graph based on the dependencies, and determine the start time of each task based on the task information and fulfillment node of each task, so as to integrate and render the multiple tasks, the dependencies between tasks and the start time in the task mesh graph to obtain the project Gantt chart. The task allocation unit is configured to present the project Gantt chart and, in response to a confirmation operation on the project Gantt chart, allocate the plurality of tasks to corresponding execution objects for task execution.

9. The system according to claim 1, characterized in that, The risk assessment module includes: The data processing unit is configured to collect the execution data features and clean the execution data features to obtain a standard feature set; The risk assessment unit is configured to use risk assessment models corresponding to different risk dimensions to assess the standard feature set from different dimensions to obtain risk indicators corresponding to different risk dimensions, and to monitor the execution of the multiple tasks based on the risk indicators of each risk dimension to obtain monitoring results.

10. A project management method, characterized in that, Applied to a project management system, the system includes an application module, a collaborative approval module, a contract generation module, a task breakdown module, a risk assessment module, and an acceptance management module; the method includes: The application module responds to the selection of a template for the target project by loading a structured electronic form and filling guidance information, and performs compliance verification on the content filled in the structured electronic form, so as to generate a project application form based on the content that passes the verification. In response to the operation of selecting the approval method for the project application, the collaborative approval module determines the target approval method and sends the project application to the corresponding approval role according to the target approval method. It also records the approval operation information and timestamp information of each approval role for the project application to obtain the approval result and approval chain information. The contract generation module extracts key approval information based on the project category in the project application and the approval result, determines target clauses from the contract clause library based on the key approval information, and fills in the contract template based on the project application, the target clauses, and the approval result to output the final contract. The task decomposition module determines multiple tasks, their dependencies, and performance nodes based on the finalized contract. It then generates and displays a project Gantt chart based on the tasks, their dependencies, and performance nodes. In response to a confirmation operation on the project Gantt chart, the module assigns the multiple tasks to corresponding execution objects for task execution. The risk assessment module collects the execution data characteristics of the multiple tasks, performs risk assessment based on the execution data characteristics, determines risk assessment results in multiple dimensions, and monitors the execution status of the multiple tasks based on the risk assessment results to obtain monitoring results. The acceptance management module is used to conduct acceptance testing on the project based on the finalized contract and the monitoring results, in order to generate an acceptance report.

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