A work task management system

Abstract

The present invention provides a work task management system, which belongs to the technical field of task management, and comprises: a priority determination module: determining the initial priority of a task based on task information input by a user; a sequence adjustment module: determining the dependency relationship of subtasks under each task based on the task information input by the user, and then determining the execution order of subtasks under each task; a list construction module: determining the execution related information of each task based on the execution order of subtasks and the execution related information of each subtask, and then constructing a task list in combination with the initial priority of each task; a list update module: monitoring and analyzing the progress of tasks, and updating the task list based on the analysis results; a strategy construction module: constructing a work task management strategy based on the task list and user permissions, thereby overcoming the defects of manually adjusting task priorities and inflexible dependency processing in the prior art, and greatly improving the automation and efficiency of task management.

Description

Technical Field

[0001] The present invention relates to the technical field of task management, and in particular to a work task management system. Background Art

[0002] With the development of information technology and the increase in enterprise management needs, work task management systems have been widely used in project management, task scheduling, and other aspects.

[0003] Existing work task management systems usually help users manage tasks through simple task lists and progress tracking, but they still have certain limitations in terms of automatic determination of task priorities, processing of subtask dependencies, and real-time updating of task lists. At present, the closest existing technical solutions are mostly based on task priorities manually input by users to sort and schedule tasks. This method is difficult to effectively optimize the order of task execution when the task volume is large or the dependencies are complex, thus affecting the overall work efficiency. For example, in some existing technical solutions, the determination of task priorities lacks intelligence, and the processing of subtask dependencies is relatively simple, which cannot meet the needs of complex task management.

[0004] Therefore, the present invention provides a work task management system. Summary of the invention

[0005] The present invention provides a work task management system, which is used to intelligently optimize the task execution order, dynamically update the task list, and formulate management strategies based on user permissions by combining task priorities, subtask dependencies and real-time progress analysis. It overcomes the defects of manual adjustment of task priorities and inflexible dependency processing in the prior art, and greatly improves the automation and efficiency of task management.

[0006] The present invention provides a work task management system, comprising:

[0007] Priority determination module: determines the initial priority of the task based on the task information input by the user;

[0008] Sequence adjustment module: Determines the dependency of subtasks under each task based on the task information input by the user, and then determines the execution order of subtasks under each task;

[0009] List building module: determines the execution-related information of each task based on the execution order of subtasks and the execution-related information of each subtask, and then builds a task list based on the initial priority of each task;

[0010] List update module: monitors and analyzes the progress of tasks, and updates the task list based on the analysis results;

[0011] Strategy building module: Build work task management strategies based on task lists and user permissions.

[0012] The present invention provides a work task management system, a priority determination module, comprising:

[0013] Information analysis unit: analyzes the task information input by the user to obtain relevant data of the task;

[0014] Prioritization unit: Determines the initial priority of a task based on its associated data:

[0015] ;in, is the initial priority of the ith task, is the kth attribute value of the ith task, is the preset weight corresponding to the kth attribute of the ith task, is the resource consumption of the kth attribute of the ith task, is the preset time urgency factor of the i-th task, is the preset strategy relevance factor of the i-th task, is the preset complexity factor of the i-th task, Adjust parameters for the preset.

[0016] The present invention provides a work task management system, a priority determination module, and further includes:

[0017] Dependency building unit: Analyzes the task information input by the user and builds the initial subtask dependency graph of each task;

[0018] Feature acquisition unit: Analyze the initial subtask dependency graph of each task to obtain the task features of the subtasks under each task;

[0019] Weight determination unit: trains the dependency prediction model based on historical task data, inputs the task features of the subtasks into the dependency prediction model, outputs the probability of the subtask dependency, and then determines the weight of the dependency between each subtask;

[0020] Graph adjustment unit: adjusts the initial subtask dependency graph based on the weight of the dependency relationship between each subtask to obtain the adjusted subtask dependency graph;

[0021] Sequence determination unit: performs topological sorting on the adjusted subtask dependency graph of each task to determine the execution order of the subtasks under each task.

[0022] The present invention provides a work task management system, which relies on a building unit and includes:

[0023] Element extraction subunit: performs a first analysis on the task information input by the user and extracts the key elements of each task;

[0024] Structural determination subunit: Based on the results of the first analysis and the preset algorithm, each task is divided into several subtasks, and each subtask is further divided into more fine-grained task steps, thereby forming a hierarchical structure tree for each task;

[0025] Second analysis subunit: performs a second analysis on each subtask, and determines the task type of each subtask in combination with a pre-trained task classification model;

[0026] Dependency determination subunit: performs dependency analysis on all task types and determines the dependency relationships between task types;

[0027] Graph construction subunit: constructs the first subtask dependency graph of each task based on the hierarchical structure tree of each task and the dependency relationship of the task types of the subtasks under each task;

[0028] Graph optimization subunit: performing a first optimization on the first subtask dependency graph based on a preset optimization algorithm, and at the same time, performing a second optimization on the first subtask dependency graph based on a preset detection algorithm;

[0029] A graph determining subunit is configured to determine an initial subtask dependency graph for each task based on the first subtask dependency graph that has undergone the first optimization and the second optimization.

[0030] The present invention provides a work task management system, wherein the preset algorithms include: a hierarchical clustering algorithm and a nested tree structure algorithm.

[0031] The present invention provides a work task management system, a list construction module, comprising:

[0032] Information determination unit: determining the execution related information of each task based on the execution order of the subtasks and the execution related information of each subtask;

[0033] Overview determination unit: creates an execution overview for each task based on the execution related information of each task;

[0034] List filling unit: obtains a preset task list framework and fills the task list based on the initial priority and execution overview of each task.

[0035] The present invention provides a work task management system, including: overall start and end time of tasks, total resource requirements and priorities.

[0036] The present invention provides a work task management system, a list update module, comprising:

[0037] First priority acquisition unit: monitors the progress of tasks, obtains relevant data on the progress of each task, and then adjusts the initial priority to obtain the first priority:

[0038] ;in, is the first priority of the i-th task, is the initial priority of the ith task, is the scheduled completion time of the ith task, is the current time, is the completion rate of the i-th task, and , is the preset importance weight of the i-th task, is the preset resource requirement coefficient of the i-th task;

[0039] Second priority acquisition unit: adjusts the first priority based on the relevant data of the progress of each task and the impact between tasks to determine the second priority:

[0040] ;in, is the second priority of the i-th task, is the set of other tasks that affect the i-th task, is the number of other tasks that affect the i-th task, is the preset basic influence coefficient of the jth task on the ith task, is the first priority of the jth task, is the initial priority of the jth task, is the dependency strength between the jth task and the ith task, is the completion rate of the jth task, is the time from the jth task to the deadline, is the preset time sensitivity adjustment factor, is the preset resource requirement coefficient of the jth task;

[0041] List updating unit: updates the task list based on the second priority of each task.

[0042] A work task management system provided by the present invention intelligently optimizes the task execution order, dynamically updates the task list, and formulates management strategies based on user permissions by combining task priorities, subtask dependencies and real-time progress analysis. It overcomes the defects of manual adjustment of task priorities and inflexible dependency processing in the prior art, and greatly improves the automation and efficiency of task management. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a structural diagram of a work task management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] Example 1

[0047] like Figure 1 As shown, an embodiment of the present invention provides a work task management system, including:

[0048] Priority determination module: determines the initial priority of the task based on the task information input by the user;

[0049] Sequence adjustment module: Determines the dependency of subtasks under each task based on the task information input by the user, and then determines the execution order of subtasks under each task;

[0050] List building module: determines the execution-related information of each task based on the execution order of subtasks and the execution-related information of each subtask, and then builds a task list based on the initial priority of each task;

[0051] List update module: monitors and analyzes the progress of tasks, and updates the task list based on the analysis results;

[0052] Strategy building module: Build work task management strategies based on task lists and user permissions.

[0053] In this embodiment, the task information input by the user refers to various detailed information about the task input by the user in the system, including the name, description, deadline, participants, priority preference, expected completion time, etc. of the task. For example, the user enters a task "prepare quarterly report" and attaches the deadline of the task (such as September 30, 2024), participants (such as Zhang San and Li Si), priority preference (high priority), etc.;

[0054] In this embodiment, the initial priority of a task is the priority automatically assigned to each task by the system based on the task information (such as urgency, deadline, importance, etc.) input by the user. The initial priority is used to determine the order and scheduling of tasks in the task list. For example, the task "prepare quarterly report" is assigned a "high" priority because it is an urgent task and its deadline is approaching;

[0055] In this embodiment, the dependency relationship of subtasks refers to the mutual dependency between multiple subtasks in a task. Some subtasks may need to be started after other subtasks are completed. For example, in the task of "prepare quarterly report", the subtask "collect data" must be completed before "complete data analysis", so "collect data" is the predecessor task of "complete data analysis";

[0056] In this embodiment, the execution order of the subtasks is determined based on the dependencies between the subtasks, and the order of the subtasks is automatically adjusted according to these dependencies. For example: In the above example, the execution order may be: first "collect data", then "complete data analysis", and finally "write report".

[0057] In this embodiment, the execution-related information of the subtask refers to the detailed information required to execute each subtask, including the estimated completion time, resource requirements, responsible persons, etc. For example, for the subtask of "collecting data", the execution-related information may include that the estimated completion time is 2 days;

[0058] In this embodiment, the execution-related information of the task is the result of integrating the execution-related information of all subtasks, including the overall estimated completion time of the task, required resources, participants, etc. For example, the execution-related information of the entire "prepare quarterly report" task may include a total estimated completion time of 10 days and required resources of 1 data analyst and 1 report writer.

[0059] In this embodiment, the task list is an ordered task list generated by the system based on the initial priorities of all tasks and the execution order of subtasks, and is used to guide users or teams to perform tasks in order. For example, the task list may include the following items: 1. Prepare quarterly report (high priority), 2. Update customer database (medium priority), 3. Prepare for team meeting (low priority);

[0060] In this embodiment, the task progress status refers to the status information reflected in real time during the execution of the task, such as the completion percentage of the task, the current stage, completed subtasks and remaining subtasks, etc. For example, the progress status of the "prepare quarterly report" task may be displayed as "50% completed: data collection completed, data analysis in progress".

[0061] In this embodiment, the analysis result is the conclusion or suggestion drawn by the system based on the monitored task progress, including whether the task is carried out as planned, whether resource allocation needs to be adjusted, whether there is a risk of delay, and the completion rate of the task. For example, the analysis result shows that "the data analysis phase takes 2 days longer than the expected time, there is a risk of delay, and the completion rate is 0.7";

[0062] In this embodiment, updating the task list refers to adjusting and optimizing the original task list based on the task progress and analysis results. The updated task list can better reflect the current work status and priority. If the "prepare quarterly report" task is re-evaluated as "urgent" due to the risk of delay, the system will re-order it in the task list as the highest priority.

[0063] In this embodiment, user authority refers to the level of operation authority granted to a user in the system. Users with different authority can view and operate task data of different scopes. For example, a project manager may have the authority to view and modify all tasks, while ordinary team members can only view and modify the tasks they are responsible for.

[0064] In this embodiment, building a work task management strategy refers to formulating a specific task execution strategy based on the task list and user permissions, including task allocation, time management, resource allocation, etc., defining permission levels: assigning different task access permissions such as viewing, editing, deleting, etc. according to the user's role and responsibilities, permission implementation: when a user tries to access a task, the system checks its permissions and allows or denies the corresponding operation based on the permission level, adjusting priorities based on progress: the task priority is dynamically adjusted based on the completion rate and remaining time of the task, overdue task detection: the system automatically identifies overdue tasks and notifies the relevant person in charge, hiding or readjusting tasks: based on the importance and impact of the task, decide whether to hide the task or readjust its priority and resource allocation. For example, strategies include "assigning high priority tasks to the most experienced team members and setting strict mid-term checkpoints to monitor progress."

[0065] The beneficial effects of the above technical solution are: by combining task priorities, subtask dependencies and real-time progress analysis, the task execution order is intelligently optimized, the task list is dynamically updated, and management strategies are formulated based on user permissions. This overcomes the defects of manual adjustment of task priorities and inflexible dependency processing in the existing technology, and greatly improves the automation and efficiency of task management.

[0066] Example 2

[0067] An embodiment of the present invention provides a work task management system, a priority determination module, including:

[0068] Information analysis unit: analyzes the task information input by the user to obtain relevant data of the task;

[0069] Prioritization unit: Determines the initial priority of a task based on its associated data:

[0070] ;in, is the initial priority of the ith task, is the kth attribute value of the ith task, is the preset weight corresponding to the kth attribute of the ith task, is the resource consumption of the kth attribute of the ith task, is the preset time urgency factor of the i-th task, is the preset strategy relevance factor of the i-th task, is the preset complexity factor of the i-th task, Adjust parameters for the preset.

[0071] In this embodiment, the task-related data refers to specific information extracted from the task information input by the user and used to analyze and determine the task priority, including multiple attribute values, such as resource consumption, time urgency, policy relevance, task complexity, etc., as well as weights and adjustment parameters related to these attributes. The task-related data is an important basis for calculating the initial priority of the task. Assuming there is a task "develop new product functions", the task-related data may include the following: resource consumption: it is estimated that 5 developers and 2 months of time will be required, time urgency factor: the market demand is strong, and competitors are about to release similar functions, so the time urgency is high, policy relevance factor: this function is highly consistent with the company's future development strategy, and the policy relevance is high, complexity factor: it involves multiple technical difficulties and has a high complexity, attribute weight: the company may set the time urgency weight to 0.4, the policy relevance weight to 0.3, the complexity weight to 0.2, and the resource consumption weight to 0.1;

[0072] In this embodiment, the preset strategy relevance factor reflects the relevance of the task to the overall goal of the project;

[0073] In this embodiment, the preset complexity factor represents the difficulty of executing the task or the required skill level;

[0074] In this embodiment, the preset adjustment parameter is a very small constant used to avoid division by zero errors.

[0075] The beneficial effect of the above technical solution is that by analyzing the task information input by the user and determining the initial priority of the task, the task scheduling process is optimized and the efficiency of the overall workflow is improved.

[0076] Example 3

[0077] An embodiment of the present invention provides a work task management system, wherein the priority determination module further includes:

[0078] Dependency building unit: Analyzes the task information input by the user and builds the initial subtask dependency graph of each task;

[0079] Feature acquisition unit: Analyze the initial subtask dependency graph of each task to obtain the task features of the subtasks under each task;

[0080] Weight determination unit: trains the dependency prediction model based on historical task data, inputs the task features of the subtasks into the dependency prediction model, outputs the probability of the subtask dependency, and then determines the weight of the dependency between each subtask;

[0081] Graph adjustment unit: adjusts the initial subtask dependency graph based on the weight of the dependency relationship between each subtask to obtain the adjusted subtask dependency graph;

[0082] Sequence determination unit: performs topological sorting on the adjusted subtask dependency graph of each task to determine the execution order of the subtasks under each task.

[0083] In this embodiment, the task information input by the user refers to the detailed content related to the task provided by the user, such as the goal of the task, description of subtasks, expected results, resource requirements, priority, dependencies, etc. This information is the basis for the system to analyze and make decisions. When developing a software project, the task information that the user may input includes: "implementing a user login module", "developing a payment interface", "writing test cases", etc.;

[0084] In this embodiment, the task information input by the user is analyzed by word segmentation, part-of-speech tagging, entity recognition and other methods to extract the core verbs, nouns and related operation objects of the subtask. For example, first collect data, then clean the data, and finally generate a report. The extracted subtasks are: collect data, clean data, generate report, and the dependency relationship is: collect data->clean data->generate report.

[0085] In this embodiment, the initial subtask dependency graph is a graph structure used to represent the dependency relationship between each subtask in a task. The nodes in the graph represent subtasks, and the edges represent the dependency relationship between subtasks. For example, for a development project, the initial subtask dependency graph may show that "database design" needs to be completed first, and then "develop user login module" can be carried out.

[0086] In this embodiment, the task characteristics of a subtask refer to specific information or indicators extracted from the attributes of the subtask, which are used to describe the nature and dependencies of the subtask, including the complexity of the subtask, the required resources, the time urgency, etc. For example, for "developing a user login module", the task characteristics may include "medium complexity", "requires 1 developer", and "must be performed after the front-end development is completed".

[0087] In this embodiment, historical task data refers to the records of tasks and subtasks executed by the system or organization in the past, including the attributes, dependencies, execution results, etc. of these tasks. These data are used to train the dependency prediction model to improve the accuracy of the prediction. If in previous projects, the "test module" is always executed after the "development module", then this order will be reflected in the historical task data;

[0088] In this embodiment, the dependency prediction model is a model trained based on machine learning or other algorithms, and can predict the dependency relationships and weights between subtasks according to their task features. For example, by inputting the task features of "developing a payment interface" and "developing a front-end page", the model may predict that the payment interface can only be developed after the front-end page is developed, and give a high dependency weight;

[0089] In this embodiment, the subtask dependency graph is a graph structure that represents the dependency relationship between subtasks in a task. Different from the initial subtask dependency graph, the subtask dependency graph is weighted and optimized to reflect a more accurate dependency relationship. For example, the adjusted subtask dependency graph may show that "developing the payment interface" is performed after "developing the front-end page" is completed, and this relationship is represented as a weighted edge.

[0090] In this embodiment, topological sorting is a graph algorithm used to sort the nodes in a directed acyclic graph (DAG) so that for each directed edge (u, v) in the graph, node u is ranked before node v. This sorting is used to determine the execution order of subtasks. If "database design" must be completed before "user login module", then topological sorting will ensure that "database design" is ranked before "user login module";

[0091] In this embodiment, the execution order refers to the order in which the subtasks in the task are executed in sequence according to the topological sorting after the dependencies between the subtasks in the task are determined, so as to ensure the reasonable completion of the task. For example, in a software development project, the execution order may be "database design" -> "develop user login module" -> "develop payment interface".

[0092] The beneficial effects of the above technical solution are: by introducing a dependency prediction model and a method for dynamically adjusting the subtask dependency graph, the intelligent optimization of the task management system is realized, the dependency between subtasks is identified and adjusted, the task execution order is optimized, and the task completion efficiency and resource utilization are improved. In multi-task scenarios, more flexible and accurate task scheduling capabilities are provided, which effectively reduces human intervention and errors and improves the efficiency of the overall workflow.

[0093] Example 4

[0094] A work task management system provided by an embodiment of the present invention relies on a building unit and includes:

[0095] Element extraction subunit: performs a first analysis on the task information input by the user and extracts the key elements of each task;

[0096] Structural determination subunit: Based on the results of the first analysis and the preset algorithm, each task is divided into several subtasks, and each subtask is further divided into more fine-grained task steps, thereby forming a hierarchical structure tree for each task;

[0097] Second analysis subunit: performs a second analysis on each subtask, and determines the task type of each subtask in combination with a pre-trained task classification model;

[0098] Dependency determination subunit: performs dependency analysis on all task types and determines the dependency relationships between task types;

[0099] Graph construction subunit: constructs the first subtask dependency graph of each task based on the hierarchical structure tree of each task and the dependency relationship of the task types of the subtasks under each task;

[0100] Graph optimization subunit: performing a first optimization on the first subtask dependency graph based on a preset optimization algorithm, and at the same time, performing a second optimization on the first subtask dependency graph based on a preset detection algorithm;

[0101] A graph determining subunit is configured to determine an initial subtask dependency graph for each task based on the first subtask dependency graph that has undergone the first optimization and the second optimization.

[0102] In this embodiment, the first analysis refers to dependency path parsing;

[0103] In this embodiment, the key elements of each task include: task, resource requirements, time limit, dependency, etc.

[0104] In this embodiment, each task node in the hierarchical structure tree represents a subtask, and each leaf node represents a specific task step.

[0105] In this embodiment, the second analysis is a semantic analysis.

[0106] In this embodiment, the preset optimization algorithms include: genetic algorithm, ant colony algorithm, particle swarm optimization algorithm, simulated annealing algorithm;

[0107] In this embodiment, the first optimization is to delete redundant edges and simplify the structure of the graph;

[0108] In this embodiment, the second optimization is to use the strongly connected component algorithm to detect the circular dependency problem in the graph and make appropriate adjustments to ensure that the dependency graph is a DAG (directed acyclic).

[0109] The beneficial effects of the above technical solution are: through the combination of the hierarchical structure tree and the task classification model, the task dependency graph is automatically constructed and optimized, thereby realizing the intelligence and efficiency of the task management system. Through multi-level task decomposition and two optimizations, the system can accurately identify and adjust the dependencies of subtasks to ensure smooth and efficient task execution, reduce human intervention, enhance the scheduling and management capabilities of complex tasks, and significantly improve the reliability of the system and the overall efficiency of task execution.

[0110] Example 5

[0111] An embodiment of the present invention provides a work task management system, wherein preset algorithms include: a hierarchical clustering algorithm and a nested tree structure algorithm.

[0112] In this embodiment, the hierarchical clustering algorithm is an algorithm for grouping tasks or data points by similarity. In the work task management system, the algorithm is used to divide a task into several subtasks. Specific steps: Initial stage: Each task is regarded as an independent group or node. Aggregation process: The system calculates the similarity between tasks based on task information (such as the goals, steps, resources, etc. of the task), and gradually aggregates the most similar tasks into larger subtask groups. Hierarchy formation: As the aggregation proceeds, a hierarchical structure composed of subtasks is formed. The top layer is the original task, and the bottom layer is the smallest task unit. Suppose there is a project management task, including four main tasks of "requirements analysis", "design", "development" and "testing". According to the similarity of these tasks, the "design" and "development" tasks are aggregated together to form a subtask group. This process can be further applied to the subdivided subtasks of each main task. For example, the "development" task can be further clustered into two subtasks of "front-end development" and "back-end development";

[0113] In this embodiment, the nested tree structure algorithm is an algorithm for building and managing a hierarchical structure. In a work task management system, the algorithm is used to create a hierarchical structure tree of tasks, and complex tasks are decomposed into nested subtasks and steps. It is characterized in that each task can be further subdivided and nested in a superior task to form a structured tree. For example, in a software development project, the top-level task may be "software development". This task can be divided into multiple subtasks, such as "demand analysis", "system design", "coding", and "testing". Each subtask can be further subdivided, such as "system design" can be divided into "architecture design" and "module design". The nested tree structure algorithm can ensure that each subtask clearly belongs to a superior task, thereby forming a clear task hierarchy, making task management more intuitive and efficient.

[0114] The beneficial effects of the above technical solution are: by combining the hierarchical clustering algorithm and the nested tree structure algorithm, the intelligent decomposition and organization of tasks are creatively realized, the task hierarchy can be dynamically adjusted, the flexibility and visualization of task management can be improved, and thus the management efficiency and execution effect of complex projects can be significantly improved. This combination breaks the single hierarchical structure limitation of traditional task management and provides a more efficient way of task allocation and progress tracking.

[0115] Example 6

[0116] An embodiment of the present invention provides a work task management system, a list construction module, including:

[0117] Information determination unit: determining the execution related information of each task based on the execution order of the subtasks and the execution related information of each subtask;

[0118] Overview determination unit: creates an execution overview for each task based on the execution related information of each task;

[0119] List filling unit: obtains a preset task list framework and fills the task list based on the initial priority and execution overview of each task.

[0120] In this embodiment, execution related information refers to various information closely related to the actual execution process of a task and its subtasks, including the execution time of the task, the required resources, the responsible personnel, the task status (such as not started, in progress, completed), the task dependencies, the task priority, etc. This information helps the system to better track and control the progress of tasks in task management. Assume that a software development project has a subtask of "writing the code for the user login module". The execution related information of this subtask may include: execution time: expected to be completed in 3 days, required resources: 1 back-end developer and 1 front-end developer, responsible personnel: Zhang San is responsible for the back-end, Li Si is responsible for the front-end, task status: in progress,

[0121] Priority: High, as this is a critical feature of the project, Dependencies: Needs to be completed before the "Database Design" task can begin.

[0122] In this embodiment, the preset task list framework is a predefined template or structure for organizing and displaying the information of all tasks. It is a standardized format that helps the task management system display the information of different tasks in a consistent manner. This framework may include multiple fields or columns, such as task name, priority, status, start and end date, responsible personnel, etc. In the same software development project, there is a preset task list framework, including: Task name: describes the task content, such as "Write user login module code", priority: high, medium, low, status: not started, in progress, completed, responsible personnel: Zhang San, Li Si, start date: August 23, 2024, end date: August 26, 2024, task dependency: dependent on the "database design" task.

[0123] The beneficial effects of the above technical solution are: by automatically building and filling the task list, combining the execution order of subtasks and the task overview, the systematization and efficiency of task management are achieved. Compared with traditional manual arrangement, it can generate an accurate task list to ensure the orderly advancement and reasonable allocation of tasks, significantly improve the efficiency and accuracy of task management, and has strong innovation and practicality. It realizes the intelligent sorting and efficient execution of task priorities, making task management more intuitive and easy to operate.

[0124] Example 7

[0125] An embodiment of the present invention provides a work task management system, which executes an overview, including: the overall start and end time of the task, the total resource requirements and the priority.

[0126] In this embodiment, the overall start time and end time refer to the time range from the start to the completion of the task. For example, the "requirements analysis" task of a project may start on August 1 and is expected to end on August 10. This information helps project managers understand the time allocation of tasks;

[0127] In this embodiment, the total resource requirement refers to all resources required to complete the task, including human resources, material resources, funds, etc. For example, a "development phase" task may require three developers, one tester, and corresponding development tools and software licenses;

[0128] In this embodiment, the priority is the importance and urgency of the task. For example, the task of "customer feedback processing" may be set as a high priority and needs to be completed first, while the task of "document arrangement" may be a low priority and can be carried out after other tasks are completed.

[0129] The beneficial effects of the above technical solution are: it provides an innovative work task management system through the execution overview, enabling managers to fully grasp the time progress, resource allocation and priority of the task, combined with real-time data and dynamic adjustment, which not only improves the efficiency of task management, but also enhances the optimal allocation of resources and the priority processing of key tasks, thereby achieving more accurate project execution and higher overall work efficiency.

[0130] Example 8

[0131] An embodiment of the present invention provides a work task management system, a list update module, including:

[0132] First priority acquisition unit: monitors the progress of tasks, obtains relevant data on the progress of each task, and then adjusts the initial priority to obtain the first priority:

[0133] ;in, is the first priority of the i-th task, is the initial priority of the ith task, is the scheduled completion time of the ith task, is the current time, is the completion rate of the i-th task, and , is the preset importance weight of the i-th task, is the preset resource requirement coefficient of the i-th task;

[0134] Second priority acquisition unit: adjusts the first priority based on the relevant data of the progress of each task and the impact between tasks to determine the second priority:

[0135] ;in, is the second priority of the i-th task, is the set of other tasks that affect the i-th task, is the number of other tasks that affect the i-th task, is the preset basic influence coefficient of the jth task on the ith task, is the first priority of the jth task, is the initial priority of the jth task, is the dependency strength between the jth task and the ith task, is the completion rate of the jth task, is the time from the jth task to the deadline, is the preset time sensitivity adjustment factor, is the preset resource requirement coefficient of the jth task;

[0136] List updating unit: updates the task list based on the second priority of each task.

[0137] In this embodiment, the data related to the task progress refers to various data related to the current status, completion degree and execution status of the task, including: completion rate: the proportion of the completed part of the task to the total tasks. For example, if a task needs to process 100 projects and 80 have been processed, the completion rate is 80%. Task time data: including the scheduled completion time of the task, the current time, etc., used to determine whether the progress of the task is as planned. For example, if the task is scheduled to be completed on August 20, and the current date is August 18, and the completion rate is 50%, the task progress may be behind schedule. Resource consumption: whether the resources (such as manpower and material resources) used by the task are consistent with expectations. For example, the completion rate of a software development task is 60%, the current date is September 1, and the scheduled completion date is September 5. The data related to the task progress will contain this information for priority adjustment.

[0138] In this embodiment, the preset resource requirement coefficient is the relative weight of the resources required for a task during its execution, which measures the impact of the amount of resources required to complete the task on the task priority. If Task A and Task B have the same initial priority, but Task A requires a large amount of manpower, capital, and equipment resources (coefficient is 0.8), while Task B requires relatively fewer resources (coefficient is 0.3), then Task A has a higher resource requirement coefficient, which may result in its higher priority.

[0139] In this embodiment, the preset basic influence coefficient refers to the basic influence degree of other tasks on the target task, which represents the interdependence and influence between tasks. If the completion of task C is very important for the start of task D (such as the result of task C is the input of task D), then the preset basic influence coefficient of task C on task D may be 0.9, indicating that C has a strong influence on D, and the priority of C directly affects the priority of D.

[0140] In this embodiment, the preset time sensitivity adjustment coefficient refers to the degree of influence of time on the priority of a task when the task is close to the deadline. The closer the task is to the deadline, the higher the coefficient may be, thereby increasing the priority of the task. For example, if Task E is only two days away from the deadline and the completion rate is only 50%, the time sensitivity adjustment coefficient will be higher (such as 0.7), thereby increasing the priority of Task E and prompting the system to invest more resources in the task to ensure timely completion.

[0141] The beneficial effects of the above technical solution are: by dynamically adjusting task priorities and combining task progress and mutual influencing factors, intelligent updating of the task list is achieved. Compared with traditional static management methods, this solution has significant advantages in real-time and flexibility, and can accurately allocate resources and optimize task scheduling, thereby improving the overall project execution efficiency and success rate, making complex task management more efficient and accurate.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A work task management system, characterized in that: include: Priority determination module: determines the initial priority of the task based on the task information input by the user; Sequence adjustment module: Determines the dependency of subtasks under each task based on the task information input by the user, and then determines the execution order of subtasks under each task; List building module: determines the execution-related information of each task based on the execution order of subtasks and the execution-related information of each subtask, and then builds a task list based on the initial priority of each task; List update module: monitors and analyzes the progress of tasks, and updates the task list based on the analysis results; Strategy building module: build work task management strategies based on task lists and user permissions; Among them, the priority modules include: Information analysis unit: analyzes the task information input by the user to obtain relevant data of the task; Prioritization unit: Determines the initial priority of a task based on its associated data: ;in, is the initial priority of the ith task, is the kth attribute value of the ith task, is the preset weight corresponding to the kth attribute of the ith task, is the resource consumption of the kth attribute of the ith task, is the preset time urgency factor of the i-th task, is the preset strategy relevance factor of the i-th task, is the preset complexity factor of the i-th task, Adjust parameters for presets; Prioritize modules, including: Dependency building unit: Analyzes the task information input by the user and builds the initial subtask dependency graph of each task; Feature acquisition unit: Analyze the initial subtask dependency graph of each task to obtain the task features of the subtasks under each task; Weight determination unit: trains the dependency prediction model based on historical task data, inputs the task features of the subtasks into the dependency prediction model, outputs the probability of the subtask dependency, and then determines the weight of the dependency between each subtask; Graph adjustment unit: adjusts the initial subtask dependency graph based on the weight of the dependency relationship between each subtask to obtain the adjusted subtask dependency graph; Sequence determination unit: performs topological sorting on the adjusted subtask dependency graph of each task to determine the execution order of the subtasks under each task; Among them, the dependent building units include: Element extraction subunit: performs a first analysis on the task information input by the user and extracts the key elements of each task; Structural determination subunit: Based on the results of the first analysis and the preset algorithm, each task is divided into several subtasks, and each subtask is further divided into more fine-grained task steps, thereby forming a hierarchical structure tree for each task; Second analysis subunit: performs a second analysis on each subtask, and determines the task type of each subtask in combination with a pre-trained task classification model; Dependency determination subunit: performs dependency analysis on all task types and determines the dependency relationships between task types; Graph construction subunit: constructs the first subtask dependency graph of each task based on the hierarchical structure tree of each task and the dependency relationship of the task types of the subtasks under each task; Graph optimization subunit: performing a first optimization on the first subtask dependency graph based on a preset optimization algorithm, and at the same time, performing a second optimization on the first subtask dependency graph based on a preset detection algorithm; A graph determining subunit: determining an initial subtask dependency graph of each task based on the first subtask dependency graph that has undergone the first optimization and the second optimization; Among them, the list update module includes: First priority acquisition unit: monitors the progress of tasks, obtains relevant data on the progress of each task, and then adjusts the initial priority to obtain the first priority: ;in, is the first priority of the i-th task, is the initial priority of the ith task, is the scheduled completion time of the ith task, is the current time, is the completion rate of the i-th task, and , is the preset importance weight of the i-th task, is the preset resource requirement coefficient of the i-th task; Second priority acquisition unit: adjusts the first priority based on the relevant data of the progress of each task and the impact between tasks to determine the second priority: ;in, is the second priority of the i-th task, is the set of other tasks that affect the i-th task, is the number of other tasks that affect the i-th task, is the preset basic influence coefficient of the jth task on the ith task, is the first priority of the jth task, is the initial priority of the jth task, is the dependency strength between the jth task and the ith task, is the completion rate of the jth task, is the time from the jth task to the deadline, is the preset time sensitivity adjustment factor, is the preset resource requirement coefficient of the jth task; List updating unit: updates the task list based on the second priority of each task.

2. A work task management system according to claim 1, characterized in that: The preset algorithms include: hierarchical clustering algorithm and nested tree structure algorithm.

3. A work task management system according to claim 1, characterized in that: List building blocks, including: Information determination unit: determining the execution related information of each task based on the execution order of the subtasks and the execution related information of each subtask; Overview determination unit: creates an execution overview for each task based on the execution related information of each task; List filling unit: obtains a preset task list framework and fills the task list based on the initial priority and execution overview of each task.

4. A work task management system according to claim 3, characterized in that: Execution overview, including: overall start and end time of tasks, total resource requirements, and priority.

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