Task processing method and device of intelligent workbench, equipment and medium

Abstract

The embodiment of the invention provides a task processing method and device for an intelligent workbench, equipment and a medium, and the task processing method comprises the steps: classifying all tasks in a task list, setting task parameters of each task in the classified tasks, enabling each classified task to be directly issued to a target user according to the task parameters, and improving the user experience. The target user performs processing according to the sorted tasks in the task list, and the target user does not need to search and screen the tasks for a long time, so that the working efficiency is improved, and in addition, the task at the emergency level can be reminded, and the user can conveniently process the emergency task preferentially.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular, to a task processing method, device, equipment and medium for an intelligent workbench. Background Art

[0002] In the daily operations of modern enterprises and various organizations, especially financial enterprises or medical institutions, it is necessary to use work management tools to manage and allocate work tasks, so that employees can process various work tasks more efficiently and improve the overall work efficiency. Work tasks are usually published on the enterprise's exclusive platform or system, such as insurance systems, medical platforms, etc.

[0003] However, most traditional work management tools rely on manual entry of some to-do items and regular checking. This method is difficult to effectively help users manage work flexibly in multiple scenarios, and the degree of intelligence of such tools is not high enough. After entering the to-do items, a relatively simple classification method is usually adopted, such as classification according to the department to which the task belongs, task type (such as administrative tasks, business tasks), entry time, etc. According to this classification method, each to-do item will be simply assigned to a single department, making it difficult for relevant personnel to quickly find the specific tasks related to their work. Moreover, if some tasks need to be processed urgently, it is also impossible to quickly find the urgent tasks, increasing the time cost of searching and screening tasks and reducing work efficiency. Summary of the Invention

[0004] Embodiments of the present invention provide a task processing method, device, equipment and medium for an intelligent workbench, aiming to solve the problem that the classification method of existing work management tools increases the time cost of searching and screening tasks and reduces work efficiency.

[0005] In a first aspect, embodiments of the present invention provide a task processing method for an intelligent workbench, including:

[0006] Obtain the task list of the intelligent workbench, and classify all tasks in the task list according to task content to obtain classified tasks;

[0007] Pre-set task parameters for each task in the classified tasks, and send the corresponding tasks to the target user according to the task parameters;

[0008] Obtain the task list of the target user, sort the to-do tasks in the task list according to the deadline, and mark each sorted to-do task to confirm whether it is urgent;

[0009] When the to-do task is marked as the urgent level, remind the target user and update the task progress of the to-do task.

[0010] In a second aspect, an embodiment of the present invention provides a task processing device for an intelligent workbench, including:

[0011] A classification unit, configured to obtain a task list of the intelligent workbench, classify all tasks in the task list according to task content, and obtain classified tasks;

[0012] A distribution unit, configured to preset task parameters of each task in the classified tasks, and distribute the corresponding tasks to target users according to the task parameters;

[0013] A marking unit, configured to obtain a task list of the target user, sort the to-do tasks in the task list according to the order of the deadline, and mark each sorted to-do task to confirm whether it is urgent;

[0014] A reminder unit, configured to remind the target user when the to-do task is marked as urgent, and update the task progress of the to-do task.

[0015] In a third aspect, an embodiment of the present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the task processing method described above is implemented.

[0016] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the task processing method described above is implemented.

[0017] An embodiment of the present invention provides a task processing method, device, equipment, and medium for an intelligent workbench. The task processing method classifies all tasks in the task list and sets task parameters for each task in the classified tasks, so that each classified task can be directly distributed to target users according to the task parameters. The target user processes according to the sorted tasks in the task list. The target user does not need to spend a long time searching and filtering tasks, which improves work efficiency. Moreover, it can remind tasks at the urgent level, facilitating users to give priority to processing urgent tasks. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0019] Figure 1Schematic diagram of an application environment of a task processing method for an intelligent workbench in an embodiment of the present invention;

[0020] Figure 2 Schematic diagram of a process of a task processing method for an intelligent workbench in an embodiment;

[0021] Figure 3 For Figure 2 Schematic diagram of a specific implementation process before step S10 in

[0022] Figure 4 For Figure 2 Schematic diagram of a specific implementation process of step S10 in

[0023] Figure 5 For Figure 2 Schematic diagram of a specific implementation process of step S20 in

[0024] Figure 6 For Figure 2 Another schematic diagram of a specific implementation process of step S20 in

[0025] Figure 7 For Figure 2 Schematic diagram of a specific implementation process of step S30 in

[0026] Figure 8 For Figure 2 Another schematic diagram of a specific implementation process of step S30 in

[0027] Figure 9 Schematic diagram of a process of a task processing method for an intelligent workbench in another embodiment;

[0028] Figure 10 Schematic diagram of a structure of a task processing device for an intelligent workbench in an embodiment of the present invention;

[0029] Figure 11 Schematic diagram of a structure of a computer device in an embodiment of the present invention;

[0030] Figure 12 Another schematic diagram of a structure of a computer device in an embodiment of the present invention. Specific implementation manners

[0031] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0032] It should be understood that when used in this specification and the appended claims, the terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0033] It should also be understood that the terms used in this specification of the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly dictates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0034] It should be further understood that the term "and / or" used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0035] A task processing method for an intelligent workbench provided by an embodiment of the present invention can be applied in an application environment such as Figure 1 wherein the client communicates with the server through a network. The server can obtain a task list of the intelligent workbench, classify all tasks in the task list according to task content to obtain classified tasks; preset task parameters for each task in the classified tasks, and send the corresponding tasks to the target user according to the task parameters; obtain the task list of the target user, sort the to-do tasks in the task list according to the deadline from early to late, and mark each sorted to-do task to confirm whether it is urgent; when the to-do task is marked as the urgent level, remind the target user and update the task progress of the to-do task.

[0036] In the present invention, for complex insurance entities in the insurance business, there are some business tasks to be processed. The business tasks to be processed generate a task list. By classifying all the tasks in the task list, the classified tasks include customer expansion tasks, policy processing tasks, and claims settlement service tasks. Among them, customer expansion tasks are responsible for developing new customers and increasing the company's business volume; policy processing tasks are responsible for tasks such as inputting and reviewing new policies; claims settlement service tasks are responsible for processing customers' claims settlement applications and providing claims settlement services. Then, task parameters for each task in the classified tasks are set. The task parameters include: task name, target user, task description, priority, and time requirement. For customer expansion tasks, the task name is: Phone call to potential customers; the target user is: Sales representative; the task description is: Make 50 phone calls to potential customers every day to introduce the company's insurance products; the priority is: High; the time requirement is: 9:00 - 17:00 on weekdays. For policy processing tasks, the task name is: Input of new policies; the target user is: Policy input operator; the task description is: Input the information of new policies received on the same day into the system to ensure the accuracy of the information; the priority is: Medium; the time requirement is: Complete within 2 working days after receiving the policy. For claims settlement service tasks, the task name is: Review of claims settlement applications; the target user is: Claims settlement reviewer; the task description is: Review the claims settlement applications submitted by customers and verify the authenticity and integrity of the claims settlement materials; the priority is: High; the time requirement is: Complete within 3 working days after receiving the application. According to the set task parameters, the system directly distributes each classified task to the corresponding target user. After receiving the task list, the target user sorts the tasks according to the task priority and time requirement and processes each task in turn. For example, the sales representative gives priority to processing the task of phone call to potential customers and completes the call quantity within the specified time; the policy input operator completes the input within 2 working days as required after receiving the new policy; the claims settlement reviewer reviews the claims settlement application as soon as possible to ensure the review result is given within 3 working days.

[0037] For the application scenarios in the medical field, by classifying all the tasks in the task list, the classified tasks include diagnosis, treatment, and nursing. Among them, the diagnosis category is responsible for focusing on the detection and judgment of diseases; the treatment category is responsible for implementing various treatment means to help patients recover; the nursing category is responsible for paying attention to the daily care of patients and promoting the rehabilitation process. Then, set the task parameters for each task in the classified tasks. The task parameters include: task name, target user, task description, priority, and time requirement. For the diagnosis category, task name: Patient X-ray examination; target user: Radiologist; task description: Take an X-ray of the scheduled patient and preliminarily analyze the imaging results; priority: high; time requirement: Complete the examination and preliminary report within 30 minutes of the patient's scheduled time. For the treatment category, task name: Surgical operation; target user: Surgeon and surgical team; task description: Perform the specified surgical operation on the patient according to the surgical plan; priority: high; time requirement: Start the operation on time according to the scheduled operation time, and the operation duration depends on the complexity of the operation, but it needs to be estimated in advance and informed the patient's family. For the nursing category, task name: Patient daily care; target user: Responsible nurse; task description: Monitor the patient's vital signs, perform wound care, assist the patient in rehabilitation activities, etc. on time; priority: medium; time requirement: Monitor the vital signs every 2 hours, and perform wound care according to the doctor's advice at regular intervals. The hospital's task management system accurately pushes different types of tasks to the corresponding target users according to the set task parameters. After receiving the task list, the target user sorts the tasks according to the task priority and time requirement. For example, the radiologist completes the X-ray examination and preliminary report within 30 minutes of the patient's scheduled time; the surgeon and surgical team make preparations in advance and start the operation on time; the responsible nurse completes each nursing task in an orderly manner at the specified time intervals.

[0038] In the present invention, by directly distributing each classified task to the target user according to the task parameters, and the target user processes the tasks according to the sorted tasks in the task list, the work efficiency is improved. Moreover, it can remind the tasks at the emergency level to facilitate the user to give priority to handling the emergency tasks. Among them, the client can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of multiple servers. The present invention will be described in detail below through specific embodiments.

[0039] Please refer to Figure 2 , the embodiment of the present invention provides a task processing method for an intelligent workbench, including S10 - S40:

[0040] S10. Obtain the task list of the intelligent workbench, and classify all the tasks in the task list according to the task content to obtain classified tasks;

[0041] In this step, the tasks in the task list of the intelligent workbench can be obtained from external sources or internal sources. When obtaining from internal sources, the intelligent workbench can directly obtain the task list. When obtaining from external sources, the intelligent workbench needs to be connected to an external system. After successful connection, the intelligent workbench can obtain tasks from the external system. When the tasks are successfully obtained and the task list is generated, the tasks in the task list are classified according to the task content, enabling users to quickly find the tasks they need to process and reducing the time cost of searching for specific tasks among a large number of tasks. For example, when a user needs to process tasks related to project management, they can directly search in the "Project Management" category without having to filter through the entire task list one by one. Moreover, different categories of tasks require different processing procedures and methods. Through classification, users can formulate corresponding processing strategies based on the task categories, improving the efficiency and quality of task processing. For example, for customer service tasks, a unified template for replying to customer inquiries and a complaint handling process can be formulated.

[0042] In specific implementation, after classifying the tasks, the tasks under each category can be statistically analyzed to confirm the number of tasks and completion time under that category, thereby evaluating the progress of the project and the work efficiency of the team.

[0043] In one embodiment, before S10, as Figure 3 shown, it includes S1 - S2:

[0044] S1. Pre - construct request parameters and call the interface of the intelligent workbench to connect to the target system;

[0045] S2. Import the tasks generated by the target system into the intelligent workbench and generate a task list.

[0046] This embodiment mainly focuses on the situation when the intelligent workbench obtains tasks from external sources. In S1, the constructed request parameters include authentication parameters, request type parameters, and data range parameters. Among them, the authentication parameters are used to confirm the identity of the requester. API keys or OAuth tokens can be used for identity confirmation. For example, when using an API key, the request parameters will include a field named api_key, and its value is the unique API key assigned to the connecting party. The request type parameters are used to indicate the type of operation to be performed, such as obtaining a task list, importing tasks, etc. The data range parameters are used to specify the data range to be obtained or operated on. For example, if the tasks in the target system have time attributes, the time range of the tasks to be imported is limited by the start_date and end_date fields.

[0047] The interface of the intelligent workbench is based on the HTTP protocol. The HTTP request library can be used to call the interface of the intelligent workbench. When the intelligent workbench is connected to the target system, the task data returned by the target system exists in multiple data formats, such as JSON format and XML format. At this time, it is necessary to parse the task data to extract the key information of the task, so as to confirm whether the returned task data is the task data requested by the intelligent workbench, import the correct parsed task data into the database of the intelligent workbench, and generate a task list.

[0048] In this embodiment, by importing the tasks generated by the target system into the intelligent workbench, data integration between different systems is achieved. This enables users to manage tasks from multiple systems on a unified platform, avoiding frequent switching between different systems and improving work efficiency. Moreover, the intelligent workbench can uniformly classify, sort, and filter the imported tasks, facilitating users to quickly search for and process tasks, and enhancing the convenience of task management.

[0049] In one embodiment, as Figure 4 shown, S10 includes S11 - S15:

[0050] S11. Pre - define different task categories and the corresponding keyword list for each task category;

[0051] S12. Traverse each task in the task list and extract the keywords in the task content;

[0052] S13. Use a pre - trained word vector model to convert the keywords into text vectors and calculate the TF - IDF values of each word in the text vector;

[0053] S14. Match the TF - IDF values with the keyword list;

[0054] S15. If the match is successful, classify the corresponding task into the corresponding category to obtain a classified task.

[0055] In S11, before starting to classify tasks, it is necessary to determine different task categories according to business requirements, work processes, and task natures, and for each determined task category, further determine its keywords. For example, for the "random work item" category, the corresponding keyword can be "issued task"; for the "fixed work item" category, the corresponding keyword can be "operation and maintenance assessment"; for the "team work item" category, the corresponding keyword can be "team task"; for the "special management project" category, the corresponding keywords can be "leave", "going out", etc.; for the "common function module" category, the corresponding keyword can be "frequently used". Organize these task categories and the corresponding keywords into a keyword list to provide a clear reference basis for subsequent task classification.

[0056] In specific implementation, in the "random work item" category, superiors can assign special tasks to employees, horizontal management can assign horizontal tasks to interface persons, and users can assign personal tasks to themselves; in the "fixed work item" category, operation and maintenance assessment is carried out on each module according to the ITIL process. For example, there are 16 modules such as disaster recovery management, emergency management, alarm management, risk management, and security management. For this module, the background connects to the business systems of each module to obtain data, aggregates and displays the data according to the assessment requirements to display the key data that users care about, and jumps to the corresponding detailed data for processing through the displayed data. For specific work, such as vulnerability repair, atomic capabilities such as one-click vulnerability repair can be associated to achieve automatic vulnerability processing and reduce the operation and maintenance workload; in the "team work item" category, each employee in the team has his own tasks to be responsible for; in the "special management project" category, when an employee takes leave or goes out, the tasks are handed over; in the "common function module" category, according to the user's usage habits, the user's commonly used functions are displayed to enable the user to get started quickly, and according to the commonly used work URLs for operation and maintenance work, custom quick access entries are defined.

[0057] In S12, after obtaining the task list of the intelligent workbench, analyze the task content in the task list, remove some meaningless words in the task content, such as modal particles and auxiliary words, and perform preliminary purification processing on the task content. Use the word segmentation method in natural language processing technology to split the task content into multiple independent words. For Chinese task content, Chinese word segmentation tools such as Jieba can be used; for English task content, the NLTK tool can be used for word segmentation. From the segmented results, select the words that can reflect the core content and key information of the task as keywords. For example, if the task content is "superiors assign special tasks to employees", the keywords extracted after processing may be "superiors", "employees", and "assign special tasks".

[0058] In S13, the pre-trained word vector model can adopt Word2Vec or GloVe. Both of these models are trained on a large-scale text data and can map words into a high-dimensional vector space, so that words with similar semantics are closer in the vector space. Input the extracted keywords into the pre-trained word vector model to obtain the text vectors corresponding to each keyword. At the same time, use the TF-IDF (term frequency-inverse document frequency) algorithm to calculate the importance of each keyword in the task content. The TF-IDF value takes into account the frequency of occurrence (TF) of the word in the current task content and its rarity (IDF) in the entire task list. The higher the frequency of a word in a certain task content and the lower its frequency in other task contents, the higher its TF-IDF value, indicating that the word is more representative of the task.

[0059] In S14, the TF-IDF values of each task keyword calculated are compared and matched with a pre-defined keyword list. To ensure the accuracy and flexibility of the matching, a matching threshold can be set. For the keywords of each task, when the TF-IDF value is greater than the set matching threshold and the keyword exists in the keyword list corresponding to a certain pre-defined task category, it is considered that the keyword matches successfully with that task category.

[0060] In S15, for the tasks with successful matches, they are classified into the corresponding task categories. If multiple keywords of a task match different task categories respectively, comprehensive judgment can also be made according to factors such as the number of matching keywords and the total sum of TF-IDF values, and the task is classified into the most matching category.

[0061] This embodiment can achieve the automation of task classification, reduce the workload and time cost of manual classification. When facing a large number of tasks, it can complete the classification work quickly and accurately, enabling the staff to invest more time and energy in the execution of specific tasks, thus improving the overall work efficiency. At the same time, it also avoids the subjective biases and inconsistencies that may occur in manual classification.

[0062] S20. Preset the task parameters of each task in the classification task, and send the corresponding tasks to the target users according to the task parameters;

[0063] In this step, by setting task parameters, tasks can be accurately assigned to target users. Information such as task objectives, quality standards, and deliverable requirements can be defined in detail in the task parameters. When receiving tasks, target users can clearly understand the specific requirements of the tasks and do not need to spend extra time communicating and confirming, so they can start executing tasks faster and shorten the task startup time.

[0064] In one embodiment, as Figure 5 shown, S20 includes S21 - S22:

[0065] S21. Preset the task content, task indicators, priority, and deadline of each task in the classification task;

[0066] S22. Designate the task handler as the target user according to the priority and send the corresponding tasks;

[0067] In S21, the task parameters include task content, task metrics, priority, and deadline. For the task content, it enables employees to accurately obtain the specific work content of the task; for the task metrics, they can be used to evaluate the quality of task completion. For example, when the task metric is task duration, the employee needs to complete the task within the specified task duration; for the priority, the importance of the task needs to be considered to divide the task priorities. For example, handling major customers should be set as high priority, while sorting out document materials should be assigned low priority. In actual operation, relevant personnel can be organized for discussion and evaluation to ensure that the priority division conforms to the actual business situation; for the deadline, a reasonable deadline can be determined for each task according to the task difficulty, workload, and business time requirements. When specifically implementing, the deadline can also be set flexibly, that is, in addition to setting a basic deadline, a certain buffer time is reserved. For example, for a document writing task, the basic deadline is set as [specific date 1], and the buffer time is [X] days, that is, the final deadline is [specific date 1 + X days].

[0068] In S22, specifying the task handler according to the priority can assign the task to the most suitable employee and give full play to the advantages and potential of the employee. That is, high-priority tasks are handled by capable employees, which can ensure that important tasks are completed in a timely and high-quality manner; low-priority tasks are assigned to suitable personnel, which can also ensure the orderly progress of all work and avoid resource waste.

[0069] As Figure 6 shown, S20 also includes S23 - S24:

[0070] S23. Obtain the current number of tasks assigned to the specified task agent and the completion progress of each task;

[0071] S24. If the current number of tasks assigned is greater than the first predetermined number and the completion progress of each task is less than 50%, replace the task agent, or if the number of high-priority tasks among the specified task agents is greater than the second predetermined number, replace the task agent, where the first predetermined number is greater than the second predetermined number.

[0072] In S23, the database of the intelligent workbench records the detailed information of all tasks, including task agents, task status, completion progress, etc. Through database query statements (such as SQL), relevant task data of the specified task agent can be directly extracted from the database. At the same time, to ensure the accuracy and timeliness of data, data from different business systems, such as project management systems, office automation systems, etc., can also be integrated. From the obtained information, the tasks currently assigned to the specified task agent are filtered out. For each task, its completion progress information is extracted and stored in the database in the form of a percentage. The total number of currently assigned tasks of the specified task agent is counted, as well as the specific completion progress of each task.

[0073] In S24, it is necessary to determine whether to replace the task agent. First, according to business requirements and historical data, a first predetermined quantity and a second predetermined quantity are preset. The first predetermined quantity is greater than the second predetermined quantity. For example, the first predetermined quantity is set to 10 and the second predetermined quantity is set to 3. These two thresholds can be flexibly adjusted according to different positions and business scenarios. If the number of currently assigned tasks is greater than the first predetermined quantity (10), and the completion progress of each task is less than 50%, it is considered that the current workload of the task agent is too heavy and the task progress is slow, and the task agent needs to be replaced.

[0074] Alternatively, if the number of high-priority tasks among the task agents is greater than the second predetermined quantity (3), it means that the task agent is currently undertaking too many high-priority tasks and may not be able to ensure the timely completion of these tasks. At this time, the task agent also needs to be replaced.

[0075] Once it is necessary to replace the task agent, the intelligent workbench will trigger the task agent replacement process, screen out suitable replacement personnel from the available personnel pool, and the considerations include the skills, experience, current workload, etc. of the personnel. Then, the tasks of the original task agent are reassigned to the new task agent, and the relevant information in the task management database is updated.

[0076] S30. Obtain the task list of the target user, sort the to-do tasks in the task list according to the deadline from early to late, and mark each sorted to-do task to confirm whether it is urgent;

[0077] In this step, the task list of the target user may contain multiple to-do tasks. After sorting by the due time, the user can quickly find the tasks that are about to expire. This sorting method provides a clear task timeline for the user, avoiding blindly searching for important tasks among numerous tasks, and saving time and energy. Moreover, after marking the urgency of the tasks, the user can reasonably allocate their energy and resources according to the urgency. For urgent tasks, concentrate on dealing with them first; for non-urgent tasks, they can be arranged at an appropriate time. This helps the user to carry out work in an orderly manner and avoid delays in important tasks due to improper task arrangements.

[0078] In one embodiment, as Figure 7 shown, S30 includes S31 - S33:

[0079] S31. Obtain the task list by calling the task interface of the target user, and perform authentication based on the preset interface protocol;

[0080] S32. After successful authentication, obtain the due time of the to-do tasks in the task list, uniformly convert the due time into the timestamp format, and sort based on the order of the timestamps;

[0081] S33. During the sorting process, if there are multiple identical timestamps, perform a secondary sorting according to the priority levels of the to-do tasks.

[0082] In S31, the task interface address of the target user is provided by the intelligent workbench. Use a network request library to send a request to this interface according to the request method required by the interface (such as GET, POST). Carry necessary parameters in the request, such as the unique identifier of the target user, so that the interface can accurately identify the task list of the target user to be obtained. When performing authentication based on the preset interface protocol, the API key authentication or OAuth 2.0 authentication method can be used. If the API key authentication is adopted, add the API key pre-allocated to the user to the request parameters; if the OAuth 2.0 authentication is adopted, an access token needs to be obtained first, and then carry this token in the request. After receiving the request, the interface will verify the provided identity information, and only after successful verification can the task list of the target user be obtained.

[0083] In S32, from the obtained task list, extract the due time of each task. The due time may be stored in different formats, such as "YYYY-MM-DD HH:MM:SS", "MM / DD / YYYY". Therefore, it is necessary to convert the time format of the due time for subsequent sorting. Specifically, convert various formats of the due time into the timestamp format. A timestamp is a number representing a specific point in time, usually the number of seconds elapsed from a fixed start time (such as 00:00:00 UTC on January 1, 2025) to the specified point in time. Among them, the date and time processing function can be used to convert the time format. After converting the due time of all to-do tasks into timestamps, sort them according to the size of the timestamps. The tasks with smaller timestamps are ranked in the front, that is, the tasks with earlier due times are ranked in the front. This can intuitively present the order of tasks and facilitate users to understand which tasks need to be processed first.

[0084] In S33, it is necessary to check for duplicate timestamps. After completing the sorting based on timestamps, check whether there are multiple to-do tasks with the same timestamp, which means the due times of the to-do tasks are the same. When finding to-do tasks with the same timestamp, further sort them according to the priorities of these to-do tasks to ensure that the tasks with higher priorities are ranked in the front.

[0085] In one embodiment, as Figure 8 shown, S30 further includes S34 - S37:

[0086] S34. If the due time of the to-do task is less than the first predetermined time from the current time, mark it as very urgent;

[0087] S35. If the due time of the to-do task is greater than or equal to the first predetermined time and less than the second predetermined time from the current time, mark it as urgent; where the first predetermined time is earlier than the second predetermined time;

[0088] S36. If the due time of the to-do task is greater than or equal to the second predetermined time from the current time, mark it as normal;

[0089] S37. If the set due time of the to-do task is empty, mark it as not urgent.

[0090] In S34, the specific duration of the first scheduled time can be determined in combination with business needs and actual conditions. For some business scenarios with extremely high timeliness requirements, the first scheduled time can be set to 24 hours. Get the deadline for each to-do task, compare it with the current time, calculate the time interval between the two, and when the calculated time interval is less than the first scheduled time (24 hours), mark the to-do task as "very urgent." The marking method can display the task name in a striking color (such as red) in the task list, or add a special icon (such as an exclamation mark) next to the task to highlight it.

[0091] In S35, the second scheduled time should be greater than the first scheduled time. If the first scheduled time is 24 hours, the second scheduled time can be set to 72 hours. For to-do tasks whose deadline and current time are greater than or equal to the first scheduled time and less than the second scheduled time, they are marked as "urgent". The marking can be different from "very urgent" but equally eye-catching, such as displaying the task name in orange or using icons of different styles.

[0092] In S36, for to-do tasks whose deadline and current time are greater than or equal to the second predetermined time, they are marked as “normal.” Such tasks have relatively ample time, and a more conventional display method can be used, such as displaying the task name in a normal color.

[0093] In S37, the task list is searched for to-do tasks with blank deadlines. These tasks have no clear time limits. Such tasks are marked as "not urgent". The task names may be displayed in a relatively light color or other less conspicuous marking methods may be used to distinguish them from tasks with clear time limits.

[0094] S40: When the to-do task is marked as an emergency level, the target user is reminded and the task progress of the to-do task is updated.

[0095] In this step, the urgency level includes urgent and very urgent. When a to-do task is marked as urgent, timely reminders can help users better manage their time to ensure that they can reserve enough time and energy for urgent tasks and avoid overdue tasks due to improper time management.

[0096] When reminding, you can use a combination of multiple reminder strategies, such as first reminding through a system pop-up window, and then sending a text message reminder if the user does not handle it, and then supplementing it with a phone reminder. The reminder frequency can be set to remind once every 30 minutes to 1 hour to ensure that users will not miss it.

[0097] In one embodiment, if Figure 9 As shown, the task processing method further includes S50-S80:

[0098] S50. When the task progress of the to-do task is in the completed state, record the total completion duration of the corresponding to-do task.

[0099] S60. When the intelligent workbench issues a new task, compare the deadline with the total completion duration.

[0100] S70. If the deadline is greater than or equal to the total completion duration, assign the corresponding task to the current task agent.

[0101] S80. If the deadline is less than the total completion duration, replace the task agent and assign the corresponding task to the replaced task agent.

[0102] In S50, when the task is assigned to a designated task agent, the system automatically records the start time of the task. By setting a field in the intelligent workbench, when the task status changes from "to be assigned" to "in progress", the current time is automatically written into this field. When the task agent marks the task progress as "completed", the time at this moment is also automatically recorded as the end time of the task. The intelligent workbench calculates the total completion duration of the to-do task based on the recorded start time and end time.

[0103] In S60, when the intelligent workbench has a new task to issue, first obtain the task parameters of the new task, including the deadline of the task, and query the total completion duration of the historical tasks similar to the new task from the stored task records. Here, "similar" can be judged according to factors such as the type of task, difficulty, and business area involved. Compare the deadline of the new task with the total completion duration of the queried historical tasks to provide a basis for subsequent task assignment decisions.

[0104] In S70, when it is judged that the deadline of the new task is greater than or equal to the total completion duration of the historical task, it is considered that the current task agent has enough time to complete the task. The new task can be assigned to the current task agent, and the assignment information of the task is updated. At the same time, notify the task agent that a new task has been issued. The notification can be carried out through system messages, emails, instant messaging tools, etc. to ensure that the task agent understands the task situation in a timely manner.

[0105] In S80, if the deadline of the new task is less than the total completion duration of the historical task, it means that the current task agent may not be able to complete the task on time within the given time. At this time, the intelligent workbench will re-evaluate the assignable task agents, transfer the new task from the current task agent to the newly selected task agent, and update the assignment information. At the same time, send corresponding notifications to the original task agent and the new task agent to inform them of the change in task assignment so that the new task agent can start working in a timely manner.

[0106] In specific implementation, according to the work content processed by an individual, a work report is automatically generated through data aggregation.

[0107] Through this task processing method, users can automatically analyze and carry out work anytime and anywhere. Users no longer need to work overtime until midnight to complete tasks that can be automated, and can better manage their time. Moreover, tasks can be assigned to users according to the attributes of the users (task agents), such as completion duration, ability, etc., which can improve the work efficiency of users, reduce some unnecessary time waste and learning costs. And when users process tasks according to the sorted tasks, they can avoid missing tasks and handle urgent tasks in a timely manner. Moreover, users no longer need to write work reports separately, and the system will automatically generate reports according to the work content.

[0108] The embodiment of the present invention further provides a task processing device for an intelligent workbench, and this device is used to execute any embodiment of the aforementioned task processing method of the intelligent workbench. Specifically, please refer to Figure 10 , Figure 10 FIG. is a schematic block diagram of a task processing device for an intelligent workbench provided by an embodiment of the present invention. The task processing device 900 of the intelligent workbench includes:

[0109] A classification unit 910, configured to obtain a task list of the intelligent workbench, and classify all tasks in the task list according to task content to obtain classified tasks;

[0110] A distribution unit 920, configured to preset task parameters of each task in the classified tasks, and distribute the corresponding tasks to target users according to the task parameters;

[0111] A marking unit 930, configured to obtain the task list of the target user, sort the to-do tasks in the task list according to the deadline from early to late, and mark each sorted to-do task to confirm whether it is urgent;

[0112] A reminder unit 940, configured to remind the target user when the to-do task is marked as urgent, and update the task progress of the to-do task.

[0113] In one embodiment, before the classification unit 910, it includes:

[0114] A construction unit, configured to pre-construct request parameters and call an interface of the intelligent workbench to connect to a target system;

[0115] An import unit, configured to import tasks generated by the target system into the intelligent workbench and generate a task list.

[0116] In one embodiment, the classification unit 910 is specifically configured to:

[0117] Pre-define different task categories and the corresponding keyword lists for each task category;

[0118] Traverse each task in the task list and extract the keywords in the task content;

[0119] Use a pre-trained word vector model to convert the keywords into text vectors and calculate the TF-IDF values of each word in the text vectors;

[0120] Match the TF-IDF values with the keyword lists;

[0121] If the match is successful, classify the corresponding task into the corresponding category to obtain a classified task.

[0122] In one embodiment, the issuing unit 920 is specifically configured to:

[0123] Pre-set the task content, task metrics, priorities, and deadlines of each task in the classified task;

[0124] Designate a task handler as the target user according to the priority and issue the corresponding task;

[0125] It is also used for:

[0126] Obtain the number of currently assigned tasks of the designated task agent and the completion progress of each task;

[0127] If the number of currently assigned tasks is greater than the first predetermined number and the completion progress of each task is less than 50%, replace the task agent, or, if the number of tasks with higher priority among the designated task agents is greater than the second predetermined number, replace the task agent, where the first predetermined number is greater than the second predetermined number.

[0128] In one embodiment, the marking unit 930 is specifically configured to:

[0129] Obtain a task list by calling the task interface of the target user and perform identity verification based on a preset interface protocol;

[0130] After the identity verification is successful, obtain the deadline of the to-do tasks in the task list, uniformly convert the deadline into a timestamp format, and sort based on the sequence of the timestamps;

[0131] During the sorting process, if there are multiple identical timestamps, perform secondary sorting according to the priority levels of the to-do tasks.

[0132] In one embodiment, the marking unit 930 is also specifically configured to:

[0133] If the deadline of the to-do task is less than the first predetermined time from the current time, it is marked as very urgent;

[0134] If the deadline of the to-do task is greater than or equal to the first predetermined time and less than the second predetermined time from the current time, it is marked as urgent; wherein, the first predetermined time is earlier than the second predetermined time;

[0135] If the deadline of the to-do task is greater than or equal to the second predetermined time from the current time, it is marked as normal;

[0136] If the set deadline of the to-do task is empty, it is marked as not urgent.

[0137] In one embodiment, the task processing method further includes:

[0138] A recording unit, configured to record the total completion duration of the corresponding to-do task when the task progress of the to-do task is in a completed state;

[0139] A new task issuing unit, configured to compare the deadline with the total completion duration when a new task is issued by the intelligent workbench;

[0140] A first sub-unit for issuing new tasks, configured to issue the corresponding task to the current task agent if the deadline is greater than or equal to the total completion duration;

[0141] A second sub-unit for issuing new tasks, configured to replace the task agent and issue the corresponding task to the replaced task agent if the deadline is less than the total completion duration.

[0142] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as Figure 11 shown. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the server side of a data verification method for big data cluster migration.

[0143] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as Figure 12As shown in the figure. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it realizes the functions or steps of a data verification method for big data cluster migration.

[0144] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are realized:

[0145] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are realized:

[0146] It should be noted that for the functions or steps that the above computer-readable storage medium or computer device can achieve, reference can be made to the relevant descriptions on the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described in detail here.

[0147] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the various embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0148] Those skilled in the art can clearly understand that, for the convenience and conciseness of description, only the above-mentioned division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above.

[0149] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A task processing method for an intelligent workbench, characterized in that: include: Obtaining a task list of the intelligent workbench, and classifying all tasks in the task list according to task content to obtain classified tasks; Presetting task parameters for each task in the classification task, and sending the corresponding task to the target user according to the task parameters; Obtaining a task list of the target user, sorting the to-do tasks in the task list by deadline, and marking each sorted to-do task to confirm whether it is urgent; When the to-do task is marked as an urgent level, the target user is reminded and the task progress of the to-do task is updated.

2. The task processing method according to claim 1, characterized in that: Before you get started, here’s a to-do list for your smart workbench: Pre-constructing request parameters and calling the interface of the intelligent workbench to connect with the target system; The tasks generated by the target system are imported into the intelligent workbench, and a task list is generated.

3. The task processing method according to claim 1, characterized in that: The step of obtaining a task list of the intelligent workstation and classifying all tasks in the task list according to task contents to obtain classified tasks includes: Predefine different task categories and a list of keywords corresponding to each task category; Traversing each task in the task list and extracting keywords from the task content; Use a pre-trained word vector model to convert the keywords into text vectors, and calculate the TF-IDF value of each word in the text vector; Matching the TF-IDF value with a keyword list; If the match is successful, the corresponding tasks are divided into corresponding categories to obtain classified tasks.

4. The task processing method according to claim 1, characterized in that: The step of presetting the task parameters of each task in the classification task and sending the corresponding task to the target user according to the task parameters includes: Presetting the task content, task indicators, priority and deadline of each task in the classified tasks; Designate task handlers as target users based on priority and issue corresponding tasks; The step of presetting task parameters for each task in the classified tasks and sending the corresponding tasks to target users according to the task parameters further includes: Get the number of currently assigned tasks of the specified task agent and the completion progress of each task; If the number of currently assigned tasks is greater than a first predetermined number and the completion progress of each task is less than 50%, the task agent is replaced; or, if the number of high-priority tasks among the designated task agents is greater than a second predetermined number, the task agent is replaced, wherein the first predetermined number is greater than the second predetermined number.

5. The task processing method according to claim 4, characterized in that: The step of obtaining the target user's task list and sorting the to-do tasks in the task list according to the earlier or later deadlines includes: Obtaining a task list by calling the target user's task interface, and performing identity authentication based on a preset interface protocol; When the identity authentication is successful, the deadlines of the pending tasks in the task list are obtained, and the deadlines are uniformly converted into a timestamp format, and the tasks are sorted based on the time stamps; During the sorting process, if there are multiple tasks with the same timestamp, they are sorted again according to their priorities.

6. The task processing method according to claim 1, characterized in that: The urgency level includes urgent and very urgent. Each sorted to-do task is marked to confirm whether it is urgent, including: If the deadline of the to-do task is less than the first scheduled time from the current time, it is marked as very urgent; If the deadline of the to-do task is greater than or equal to the first scheduled time and less than the second scheduled time from the current time, it is marked as urgent; wherein the first scheduled time is earlier than the second scheduled time; If the deadline of the to-do task is greater than or equal to the second scheduled time from the current time, it is marked as normal; If the deadline set for a to-do task is empty, it will be marked as not urgent.

7. The task processing method according to claim 5, characterized in that: Also includes: When the task progress of the to-do task is in the completed state, the total completion time of the corresponding to-do task is recorded; When the intelligent workbench issues a new task, the deadline is compared with the total completion time; If the deadline is greater than or equal to the total completion time, the corresponding task will be sent to the current task agent; If the deadline is less than the total completion time, the task agent is replaced and the corresponding task is sent to the replaced task agent.

8. A task processing device of an intelligent workbench, used to implement the task processing method according to any one of claims 1 to 7, characterized in that: include: A classification unit, used for obtaining a task list of the intelligent workbench, and classifying all tasks in the task list according to task contents to obtain classified tasks; A sending unit, used to pre-set task parameters of each task in the classified tasks, and send the corresponding task to the target user according to the task parameters; a marking unit, configured to obtain a task list of the target user, sort the to-do tasks in the task list by deadline, and mark each sorted to-do task to confirm whether it is urgent; The reminder unit is used to remind the target user and update the task progress of the to-do task when the to-do task is marked as urgent.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor implements the task processing method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the task processing method according to any one of claims 1 to 7 is implemented.

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