Multi-mode intelligent calendar management system and method based on artificial intelligence

Abstract

The invention discloses a multi-mode intelligent calendar management system and method based on artificial intelligence, and belongs to the technical field of artificial intelligence and schedule management. The system comprises a multi-mode input processing module, an AI intelligent analysis module, an event management module, an intelligent reminding module and a data analysis module. The system supports two input modes of natural language texts and images, automatically identifies and extracts key information such as time, places, events and the like in the texts and the images through a pre-training language model and a computer vision technology, and converts the key information into standardized calendar events. The system has the functions of automatic classification, intelligent reminding, batch processing and the like. The technical problems that traditional calendar management is low in efficiency, insufficient in intelligent degree, single in input mode and the like are solved, multi-mode intelligent analysis and automatic event creation are achieved, and the schedule management efficiency is remarkably improved. The method is especially suitable for processing picture type schedule information such as curriculum schedules and conference notices, and supports Chinese oral expression and relative time identification. The method has the technical advantages of high processing efficiency, high accuracy, good user experience and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of artificial intelligence and schedule management, and specifically to an intelligent calendar management system and method based on multimodal AI technology, which can intelligently parse schedule information in text and images and automatically create calendar events. It belongs to the technical field of the cross-integration of artificial intelligence, natural language processing, computer vision and office software. Background Art

[0002] With the accelerating pace of work and increasingly complex lifestyles in modern society, people are increasingly in need of efficient schedule management tools. Traditional calendar management systems rely primarily on users manually entering detailed schedule information, which presents the following technical issues:

[0003] 1. Cumbersome operation: Users need to manually fill in information such as event title, time, and location, which is inefficient. 2. Low intelligence: The system cannot automatically recognize and parse key information such as time, location, and event in natural language.

[0004] 3. Single input method: Only text input is supported and images containing schedule information, such as class schedules and meeting notices, cannot be processed;

[0005] 4. Lack of intelligent analysis: Lack of intelligent analysis of user schedule patterns and the ability to provide personalized recommendations;

[0006] 5. Simple reminder function: The reminder mechanism lacks intelligence and cannot be personalized according to the importance of the event and user habits. Summary of the Invention

[0007] Purpose of the Invention

[0008] The purpose of the present invention is to provide a multimodal intelligent calendar management system and method based on artificial intelligence to solve the technical problems of low schedule management efficiency, insufficient intelligence, and single input method in the existing technology, and to realize multimodal intelligent analysis, automatic event creation and personalized management.

[0009] Technical Solution

[0010] To achieve the above object, the present invention adopts the following technical solutions:

[0011] A multimodal intelligent calendar management system based on artificial intelligence, comprising:

[0012] (1) Multimodal input processing module

[0013] Used to receive and pre-process text information or image information input by users, supporting two input methods: natural language text input and image upload.

[0014] (2) AI intelligent analysis module

[0015] This is the core technical module of the system, including:

[0016] ● Natural language processing submodule: Based on a pre-trained large language model, it performs semantic understanding of text information; ● Computer vision processing submodule: It performs image recognition and OCR processing on image information;

[0017] ●Information fusion submodule: converts the extracted information into a standardized calendar event data format.

[0018] (3) Event Management Module

[0019] Responsible for the creation, storage, update and deletion of calendar events, and has intelligent classification capabilities.

[0020] (4) Intelligent reminder module

[0021] Generate personalized smart reminders based on the time information and importance level of the event.

[0022] Beneficial effects

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] 1. Significantly improve efficiency: Through AI intelligent analysis, efficiency is increased by more than 80%;

[0025] 2. Multimodal intelligent processing: For the first time, dual-modal calendar information processing of text and images is realized;

[0026] 3. Powerful natural language understanding capabilities: supports Chinese colloquial expressions and relative time recognition;

[0027] 4. High degree of intelligence: with functions such as automatic classification, intelligent reminder, and data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 : The main interface of the smart calendar system shows the overall layout of the system and the main function entrances

[0029] Figure 2 : Intelligent text parsing function interface, showing the natural language input and parsing process

[0030] Figure 3 : Image intelligent recognition function interface, presenting the image input and analysis process

[0031] Figure 4 : Intelligent reminder function interface, presenting the system to remind users of events based on practice

[0032] Figure 5: Results of batch event extraction in the image, showing the results after intelligent recognition and extraction of batch calendar events DETAILED DESCRIPTION

[0033] Example 1: Intelligent text analysis

[0034] User input: "Project discussion meeting will be held in Conference Room A at 2:00 PM tomorrow"

[0035] The system automatically parses and creates calendar events.

[0036] Example 2: Multimodal Image Analysis

[0037] The user uploads a picture of the course schedule, and the system extracts course information in batches and creates multiple calendar events.

Claims

1. A multimodal intelligent calendar management system based on artificial intelligence, characterized in that: include: A multimodal input processing module, configured to receive text information or image information input by a user, wherein the text information is a schedule described by the user in natural language, and the image information is a picture file containing the schedule; AI intelligent analysis module, used for: Performing natural language processing on the text information to identify and extract time information, location information, event topic, and priority information using a pre-trained large language model; Performing image recognition and optical character recognition on the image information, extracting text information from the image and performing structured analysis; Convert the extracted unstructured information into a standardized calendar event data format containing event title, start time, end time, location, category, and priority; An event management module, which is used to create, store, update, and delete calendar events based on the standardized calendar event data output by the AI ​​intelligent analysis module, and has an event automatic classification function, capable of classifying events into preset categories such as work, study, life, and entertainment; An intelligent reminder module, which is used to generate personalized intelligent reminders based on the time information and importance level of the calendar event, and supports multiple reminder time settings and reminder methods; The user interface module is used to display calendar events to the user, receive user operation instructions, and present the parsing results to the user for confirmation or modification.

2. The intelligent calendar management system according to claim 1, characterized in that: The natural language processing function of the AI ​​intelligent analysis module supports the recognition of Chinese colloquial expressions, including: Absolute time expression recognition: Recognizes formats such as "June 15, 2025", "June 15th", and "6 / 15"; Relative time expression recognition: Recognize expressions such as "tomorrow", "the day after tomorrow", "next Tuesday", and "next month"; Time period expression recognition: Recognize time period descriptions such as "morning", "afternoon", "evening", and "early morning"; Fuzzy time expression recognition: Recognizes fuzzy time descriptions such as "this week", "soon", and "end of the month".

3. The intelligent calendar management system according to claim 1, characterized in that: The image recognition processing functions of the AI ​​intelligent analysis module include: Image preprocessing: denoising, contrast enhancement, and geometric correction of uploaded images; Text region detection: using deep learning models to locate text regions in images; Optical character recognition: Perform character recognition on the detected text area and generate text content; Structured parsing: Analyze table structure and layout relationships to extract key information such as time, location, and events; Batch event generation: Batch create multiple calendar events based on the parsing results.

4. The intelligent calendar management system according to claim 1, characterized in that: The event management module also includes: Event conflict detection function: automatically detect events with overlapping time and prompt the user; Event correlation analysis function: analyze the correlation between related events; Event statistics analysis function: statistics on users' schedule patterns and time allocation; Event search and filtering function: supports filtering events by time range, category, keyword and other conditions.

5. The intelligent calendar management system according to claim 1, characterized in that: The intelligent reminder module has the following functions: Multi-level reminder settings: support reminders at multiple time points such as 15 minutes, 30 minutes, and 1 hour before the event starts; Importance assessment: Automatically assess the importance of events based on event categories, keywords, and user historical behavior; Personalized reminder strategy: Adjust reminder method and frequency based on user habits and preferences; Reminder status management: Track the status of reminders sent and user responses.

6. The intelligent calendar management system according to claim 1, characterized in that: Also includes: The Quick Add module allows users to quickly create calendar events using short natural language expressions. The module understands spoken time and event descriptions and automatically completes missing information. The data statistics analysis module is used to perform statistical analysis on the user's schedule data and generate analysis reports including the number of events today, the distribution of events this week, and event category statistics.

7. A multimodal intelligent calendar management method based on artificial intelligence, characterized in that: The following steps are involved: S1: Input receiving step, receiving text information or image information input by the user, and performing format checking and preprocessing on the input data; S2: Intelligent parsing step, performing corresponding parsing processing according to the input data type: S2.1: If the information is text, natural language processing algorithms are used to identify and extract key information such as time, location, and event. S2.2: If the information is image information, first perform OCR recognition to obtain the text content, and then perform structured analysis; S3: Information extraction step, converting the parsed unstructured information into a standardized calendar event data format; S4: Event creation step, automatically creating calendar events based on the extracted information and performing intelligent classification; S5: User confirmation step, showing the analysis results to the user and receiving the user's confirmation or modification instructions; S6: Storage management step, storing the confirmed events in the database and setting corresponding intelligent reminders.

8. The intelligent calendar management method according to claim 7, characterized in that: The natural language processing algorithm in step S2.1 includes: Lexical analysis: segmenting and tagging input text; Syntactic analysis: analyzing sentence structure and grammatical relationships; Semantic analysis: understanding the meaning of sentences based on pre-trained language models; Information extraction: Use named entity recognition technology to extract key information such as time, place, and people; Time Normalization: Convert relative time expressions to absolute time.

9. The intelligent calendar management method according to claim 7, characterized in that: The image processing algorithm in step S2.2 includes: Image quality assessment: Evaluate image clarity and readability; Image enhancement: Perform pre-processing such as denoising and sharpening based on the evaluation results; Layout analysis: Identify structured content such as tables and lists in images; Text detection: Locate text areas in images; Character recognition: perform OCR recognition on text areas; Structured parsing: extracting event information based on layout structure.

10. The intelligent calendar management method according to claim 7, characterized in that: The intelligent classification function in step S4 adopts the following algorithm: Keyword matching-based classification: preliminary classification is performed based on the preset keyword dictionary; Feature classification based on machine learning: extract event text features and classify them using a trained classification model; Personalized classification based on user historical behavior: Analyze user historical classification habits and make personalized classification recommendations; Classification confidence assessment: Provides a confidence score for each classification result, and prompts the user to confirm low-confidence results.

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