Intelligent task management method based on OCR and AI technologies

Abstract

The invention discloses an intelligent task management method based on OCR (optical character recognition) and AI (artificial intelligence) technologies, which comprises the following steps: S1, information source identification: a user intercepts a screenshot of a task message through a shortcut key, and analyzes the screenshot content through an image identification technology to judge which communication tool the message source is; s2, OCR (Optical Character Recognition) and task analysis: identifying text content in the screenshot through an OCR technology, and analyzing key information of a task in combination with an AI (Artificial Intelligence) natural language processing technology; s3, attachment identification and path positioning: automatically positioning a storage path of a task attachment in a user computer through an OCR (Optical Character Recognition) technology and a file type identification function; and S4, automatic task recording: associating the analyzed task information with the identified attachment, and then automatically inputting the task information into a task management system. Compared with the tedious process that a traditional task management tool needs to manually input, sort and manage task information, the operation steps of the user are greatly reduced, and the overall efficiency of task management is improved.

Description

Technical Field

[0001] The present invention relates to the field of computer science and technology, and in particular to an intelligent task management method based on OCR and AI technology, which combines OCR (optical character recognition) and AI (artificial intelligence) technology to realize automatic recognition, processing and management of task information from multiple communication tools (such as WeChat, QQ, Feishu, etc.). The tool is mainly used for office automation to solve the problem of task management of multi-source information. Background Art

[0002] In the modern office environment, employees need to handle a large amount of task information from different communication tools (such as WeChat, Lark, QQ, WeChat for Business, and email, etc.). These task information usually exist in various forms, such as text messages, attachments, images, etc. Currently, users need to manually enter these task information into the task management system. This manual operation process is not only cumbersome and time-consuming, but also prone to omissions or errors, especially when faced with complex task information.

[0003] Traditional task management tools, such as Todoist and Microsoft To Do, can help users manage tasks, but they mainly rely on users to manually enter detailed information about the task. This information includes the task title, description, deadline, priority, related attachments, and participants. The process of manually entering task information not only increases the user's workload, but also leads to inefficient task management.

[0004] In addition, existing technologies have difficulty in achieving automated management when processing tasks from multiple sources of information. Different communication tools have different information interfaces and expressions, and users have to frequently switch between multiple platforms to manually collect and organize task content, which further increases the complexity of task management.

[0005] The problems and shortcomings of the background technology mainly include: Manual data entry is cumbersome: Users need to manually enter detailed information about the task, which increases the workload and is prone to errors.

[0006] Difficulty in managing multi-source information: The formats of task information for different communication methods are different. Especially when using instant communication tools, there will be a large amount of colloquial information expressions, which makes it difficult to manage them uniformly with existing tools, resulting in inefficient task management.

[0007] Lack of intelligent analysis: Existing technologies lack the ability to intelligently analyze and automatically process task information. They are unable to efficiently process complex task information, nor can they process minimal text expressions in context.

[0008] The specific manifestations are: Insufficient ability to parse complex task information: Existing technologies often fail to effectively extract and understand all key content when faced with task information that contains a lot of details. For example, some task information may contain multiple elements (such as time, location, participants, etc.), and existing systems may miss or incorrectly parse some of these elements, resulting in inefficient task management.

[0009] Difficulty in processing extremely simple textual expressions: Extremely simple task information usually contains only a few keywords. Although this information is concise, it requires a high level of contextual understanding. When processing such information, existing systems often fail to accurately understand its intent. For example, when parsing task information such as "The leader requires the weekly report to be submitted next Tuesday" or "Is there a meeting next Wednesday?", the system may not be able to determine the specific date of "next Tuesday" or "next Wednesday", nor can it be clear who made the task requirement.

[0010] Insufficient context association capabilities: Existing technologies usually rely on preset rules or simple keyword matching, and often fail to correctly parse task information that requires contextual understanding. For example, in a continuous conversation, such as "Zhang San asked: 'Is there a meeting next Wednesday?' Li Si replied: 'Yes, at 8:02'", the existing system may not be able to associate the two messages and extract complete task information (such as meeting time and location).

[0011] Inconvenient attachment management: The attachments involved in the task information need to be manually downloaded, sorted and associated with the corresponding tasks, which increases the complexity of user operations.

[0012] In view of the problems existing in the prior art, the present invention proposes an intelligent task management tool based on OCR (optical character recognition) and AI (artificial intelligence) technology to solve the above problems. The tool can automatically identify and parse task information from a variety of communication tools, automatically enter the management system, and associate related attachments, which greatly simplifies the task management process and improves the work efficiency of users.

[0013] The information disclosed in this background technology section is only intended to deepen the understanding of the overall background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0014] The purpose of the present invention is to provide an intelligent task management method based on OCR and AI technology, which can automatically identify and parse task information from a variety of communication tools, automatically enter the management system, and associate related attachments, thereby greatly simplifying the task management process and improving the user's work efficiency.

[0015] In order to achieve the above object, the present invention adopts the following technical solutions: The present invention provides an intelligent task management method based on OCR and AI technology, the method comprising the following steps: S1. Information source identification: Users use shortcut keys to take screenshots of task messages, and use image recognition technology to analyze the screenshot content to determine which communication tool the message source is; S2, OCR recognition and task analysis: Use OCR technology to recognize the text content in the screenshot, and combine AI natural language processing technology to analyze the key information of the task; S3. Attachment identification and path location: Automatically locate the storage path of task attachments in the user's computer through OCR technology and file type recognition function; S4. Automated task recording: After the parsed task information is associated with the identified attachments, it is automatically entered into the task management system.

[0016] Further, the specific implementation process of step S1 is as follows: Step 1: First, analyze the screenshots taken by the user to identify the application icons or interface layout elements in the interface; Step 2: Use OCR technology to recognize the text content in the screenshot and obtain text data; Step 3: Combine the identified interface elements and text information, further analyze through the AI ​​model, and finally determine the source of the information (such as WeChat, Feishu, QQ, etc.); Step 4: Based on the information source, enter the corresponding follow-up processing flow, including task analysis and attachment identification.

[0017] Further, the specific implementation process of step S2 is as follows: Step 1: First, extract the text content in the screenshot using OCR technology; Step 2: The extracted text content is parsed through the AI ​​natural language processing module to identify the core elements of the task; the core elements include task name, time, and participants; Step 3: Further analyze whether the task information involves attachments and identify the file type of the attachments.

[0018] Further, the specific implementation process of step S3 is as follows: Step 1: Analyze the attachment information in the screenshot, including the file name and file type; Step 2: Infer the default storage path of the attachment based on the information source; Step 3: If the file name is incomplete, infer the specific storage location of the attachment based on the file receiving time and partial file name.

[0019] Further, the specific implementation process of step S4 is as follows: Step 1: After the task information is parsed, the identified attachments are associated with the task information; Step 2: Automatically enter all related information into the task management application; Step 3: In the case where the attachment cannot be accurately located, possible file options are listed for the user to choose from, ensuring the completeness and accuracy of task management.

[0020] By adopting the above technical solution, the present invention has the following beneficial effects: Through a series of technical innovations, the present invention effectively solves many problems in traditional task management tools, significantly improves the efficiency, accuracy and convenience of task management, and has significant technical, economic and social value. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 A flowchart of an intelligent task management method based on OCR and AI technology provided in an embodiment of the present invention.

[0023] Figure 2 A flow chart of information source identification provided by an embodiment of the present invention.

[0024] Figure 3 A flowchart of OCR recognition and task analysis provided by an embodiment of the present invention.

[0025] Figure 4 A flowchart of attachment identification and path positioning provided by an embodiment of the present invention.

[0026] Figure 5 A schematic diagram of path inference provided by an embodiment of the present invention.

[0027] Figure 6 This is a flowchart of an automated task record provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0029] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0030] Combination Figure 1 As shown, an embodiment of the present invention provides an intelligent task management method based on OCR and AI technology, and the method includes the following steps: S1. Information source identification: Users use shortcut keys to take screenshots of task messages, and use image recognition technology to analyze the screenshot content to determine which communication tool the message source is; S2, OCR recognition and task analysis: Use OCR technology to recognize the text content in the screenshot, and combine AI natural language processing technology to analyze the key information of the task; S3. Attachment identification and path location: Automatically locate the storage path of task attachments in the user's computer through OCR technology and file type recognition function; S4. Automated task recording: After the parsed task information is associated with the identified attachments, it is automatically entered into the task management system.

[0031] Combination Figure 2 As shown, the specific process of information source identification of the present invention is as follows: First, the user uses the shortcut key to take a screenshot of the task message, and the system uses image recognition technology to analyze the screenshot content to determine which communication tool (such as WeChat, QQ, Feishu) the message source is. The specific process is as follows: After the system receives the screenshot taken by the user, it first performs image processing to extract the interface elements in the screenshot (such as application icons, interface layout, etc.).

[0032] Use OCR technology to identify the text content in the screenshot, and combine it with the identified interface elements to determine the specific source of the information through the AI ​​model.

[0033] Once the information source is identified, the system records the information source in the metadata of the task information, providing basic data for subsequent task analysis.

[0034] Use image processing libraries (such as OpenCV) to analyze interface elements in screenshots and determine the source of information through feature matching or machine learning model classification.

[0035] - Sample code: ```Python import cv2 source = cv2.imread('screenshot.png') Use feature matching or pattern recognition source_type = recognize_source(source) ``` Combination Figure 3 As shown, the specific process of OCR recognition and task analysis of the present invention is as follows: After the information source is identified, the system will use OCR technology to identify the text content in the screenshot and combine AI natural language processing technology to analyze the key information of the task. The specific process is as follows: The system calls the OCR engine to convert the text content in the screenshot into text data.

[0036] Use natural language processing (NLP) algorithms to parse text data and extract key elements of the task, such as task name, description, deadline, and participants.

[0037] The system automatically checks the analysis results to ensure the completeness and accuracy of task information.

[0038] Use OCR libraries (such as Tesseract) to recognize text content in screenshots, and use NLP models (such as BERT or custom models) to parse task-critical information.

[0039] - Sample code: ```Python import pytesseract from nlp_model import NLPModel text = pytesseract.image_to_string('screenshot.png') nlp_model = NLPModel() task_info = nlp_model.parse(text) Combination Figure 4 As shown, the specific process of attachment identification and path positioning of the present invention is as follows: In order to better manage tasks, the system also provides attachment identification and path positioning functions. This function can automatically identify attachments in task information and automatically infer the storage path of the attachments based on the source of the task. The details are as follows: Information source identification: The system first identifies that the task information comes from WeChat.

[0040] OCR and AI parsing: Use OCR to identify the file name and some of its contents in the screenshot, such as the file type (e.g., .doc, .pptx, etc.) and the time the file was received (e.g., August 2024).

[0041] Path inference: The system combines the information source and the time the file was received to automatically infer that the attachment is stored in the default path, which is the WeChat file storage path mentioned above.

[0042] Combination Figure 5 As shown in the figure, assuming that a user receives a file through WeChat in August 2024, the system will infer by default that the file is stored in the following path after parsing the task information source as WeChat through the above "1. Information Source Identification" analysis task: C:\Users\username\Documents\WeChatFiles\wxid_userID\FileStorage\File\2024-08 Similarly, when a user receives an attachment on Lark, after the system parses the task information as Lark, it will infer by default that the file is stored in the following path: C:\Users\username\Downloads\Feishu Precise positioning: If the file name is long and cannot be fully displayed, the system will combine the file reception time, partial file name and file type to further accurately locate the attachment by searching for files in the directory.

[0043] Multiple recommendations: When multiple files exist, the system will provide possible file options for the user to confirm to ensure the accuracy of positioning.

[0044] This process effectively solves the problem of users having difficulty quickly locating attachments when task information is complex and file paths are diverse, and improves the automation and convenience of task management.

[0045] The attachment storage path is inferred through the file name, file type and information source, and accurately located by combining the file time and partial name.

[0046] - Sample code: ```Python def locate_attachment(file_name, source_type): base_path = get_base_path(source_type) full_path = find_file(base_path, file_name) return full_path Combination Figure 6 As shown, the specific process of automated task recording of the present invention is as follows: Finally, the system associates the parsed task information with the identified attachments and automatically enters them into the task management system. This step not only simplifies the user's operation, but also greatly improves work efficiency. The specific process is as follows: The system associates the parsed task information with the attachments and generates a complete task record.

[0047] The system sets corresponding reminder functions according to the urgency and deadline of the task, and automatically saves the task records to the task management system.

[0048] Users can view and edit entered tasks in the task management system to ensure flexibility and accuracy of task management.

[0049] The automated task record flow chart shows the detailed process of automated task record processing.

[0050] After the system associates the parsed task information with the attachment path, it automatically saves it to the task management database and provides multiple recommendations for files that cannot be located.

[0051] - Sample code: ```Python def save_task(task_info, attachment_path): if not attachment_path: recommendations = recommend_files(task_info) task_info['attachment'] = recommendations save_to_db(task_info) ``` Through the above specific implementation methods, the present invention can effectively solve the problems of cumbersome manual input and complex information management in traditional task management, and realize automatic management and efficient processing of task information.

[0052] The present invention has significant advantages and beneficial effects in the following aspects: 1. Greatly simplify the operation process and improve the efficiency of task management: Traditional task management systems rely on users to manually input task information, which is cumbersome and error-prone. In the present invention, users can complete almost all operations of task management by simply taking a screenshot. The system will automatically identify the task information in the screenshot, perform intelligent analysis, and automatically enter the relevant information into the task management system. Compared with the cumbersome process of manually inputting, organizing and managing task information in traditional task management tools, the present invention greatly reduces the user's operating steps and improves the overall efficiency of task management.

[0053] 2. Realize unified management of multi-source task information: When processing task information from different communication tools, the existing technology often requires users to frequently switch between multiple platforms, which easily leads to information omission or management confusion. The present invention can automatically determine the source of task information (such as WeChat, QQ, Feishu, etc.) through information source identification technology, and uniformly enter it into the task management system, realizing the centralized management of multi-source task information and avoiding the management difficulties caused by information dispersion.

[0054] 3.Automated attachment management and path positioning: Attachment management has always been a major problem in task management, especially when a task involves multiple attachments. Users need to manually organize and associate the attachments, which increases the complexity of management. The present invention can automatically identify the attachments in a task and infer their storage paths through the intelligent attachment recognition and path positioning functions, greatly simplifying the attachment management process. Users do not need to manually search and associate attachments, the system will automatically complete this process, further improving the convenience of task management.

[0055] 4. Traceability of information source: The invention can accurately identify the source of task information. Whether it is WeChat, QQ, or Feishu, the system can automatically determine and record the source of information through OCR and AI technology. This function ensures that the source of task information is clear and traceable, avoiding management confusion caused by confusion of information sources. This traceability function is particularly important in multi-tasking and cross-platform collaboration.

[0056] 5. Improve the accuracy and completeness of task management: Traditional task management tools rely on manual input by users, which inevitably leads to incomplete or erroneous information input, affecting the accuracy and completeness of task management. The present invention uses AI technology to intelligently analyze and verify task information to ensure the completeness and accuracy of task information. In addition, the system also provides an automatic reminder function to help users follow up on tasks in a timely manner and avoid management problems caused by omissions or delays.

[0057] 6. Significant economic and social benefits: The present invention not only has significant technical advantages, but also has significant effects in terms of economic and social benefits. First, by improving the efficiency and accuracy of task management, the time cost of enterprises or individuals in task management can be significantly reduced, thereby improving work efficiency. Secondly, the multi-source information management and automation functions of the system can help enterprises better cope with complex task management needs and improve overall operational efficiency. At the same time, with the popularization of information management, the wide application of the present invention will further promote the development of office automation and bring positive social benefits.

[0058] In summary, the present invention effectively solves many problems in traditional task management tools through a series of technological innovations, significantly improves the efficiency, accuracy and convenience of task management, and has significant technical, economic and social value.

[0059] 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 replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An intelligent task management method based on OCR and AI technology, characterized in that: The method comprises the following steps: S1. Information source identification: Users use shortcut keys to take screenshots of task messages, and use image recognition technology to analyze the screenshot content to determine which communication tool the message source is; S2, OCR recognition and task analysis: Use OCR technology to recognize the text content in the screenshot, and combine AI natural language processing technology to analyze the key information of the task; S3. Attachment identification and path location: Automatically locate the storage path of task attachments in the user's computer through OCR technology and file type recognition function; S4. Automated task recording: After the parsed task information is associated with the identified attachments, it is automatically entered into the task management system.

2. The intelligent task management method based on OCR and AI technology according to claim 1, characterized in that: The specific implementation process of step S1 is as follows: Step 1: First, analyze the screenshots taken by the user to identify the application icons or interface layout elements in the interface; Step 2: Use OCR technology to recognize the text content in the screenshot and obtain text data; Step 3: Combine the identified interface elements and text information, further analyze through the AI ​​model, and finally determine the source of the information; Step 4: Based on the information source, enter the corresponding follow-up processing flow, including task analysis and attachment identification.

3. The intelligent task management method based on OCR and AI technology according to claim 1, characterized in that: The specific implementation process of step S2 is as follows: Step 1: First, extract the text content in the screenshot using OCR technology; Step 2: The extracted text content is parsed through the AI ​​natural language processing module to identify the core elements of the task; the core elements include task name, time, and participants; Step 3: Further analyze whether the task information involves attachments and identify the file type of the attachments.

4. The intelligent task management method based on OCR and AI technology according to claim 1, characterized in that: The specific implementation process of step S3 is as follows: Step 1: Analyze the attachment information in the screenshot, including the file name and file type; Step 2: Infer the default storage path of the attachment based on the information source; Step 3: If the file name is incomplete, infer the specific storage location of the attachment based on the file receiving time and partial file name.

5. The intelligent task management method based on OCR and AI technology according to claim 1, characterized in that: The specific implementation process of step S4 is as follows: Step 1: After the task information is parsed, the identified attachments are associated with the task information; Step 2: Automatically enter all related information into the task management application; Step 3: In the case where the attachment cannot be accurately located, possible file options are listed for the user to choose from, ensuring the completeness and accuracy of task management.

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