Automated Meeting Scheduling Using Event Activation Data
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Solution Overview
Problem
Meetings are typically organized manually, and there is a lack of systematic prioritization and use of templates for organization, leading to inefficiencies.
Innovation Solution
A system that gathers data from entities, processes it using feature extraction and a time datum language model, and communicates event activation data to external devices to automate interactions, including event execution and data updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If meetings are organized manually without systematic approaches, then flexibility in organization is maintained, but productivity and efficiency deteriorate due to time-consuming manual processes
Solution Approach 1:
The meeting organization system is segmented into distinct functional modules: data gathering module that collects entity data and event activation data, preprocessing module that performs feature extraction, time datum language model module that refines event activation data, and event execution module that communicates with external devices. This segmentation allows each module to handle specific tasks independently, improving overall productivity while managing system complexity through modular design.
Solution Approach 2:
The system performs preliminary actions by gathering and preprocessing meeting data before actual meeting execution. Entity data and event activation data are collected and refined in advance using feature extraction and language models, allowing meetings to be automatically organized and prioritized without manual intervention during the actual meeting scheduling process.
2Loss of time
If manual meeting organization is used, then system complexity is minimized, but loss of time increases due to lack of automated processing
Solution Approach 1:
The patent replaces manual mechanical meeting organization processes with an automated computational system. The time-consuming manual tasks of gathering entity data, extracting features, refining event activation data, and scheduling meetings are substituted with automated processing using language models and machine learning algorithms, significantly reducing time loss despite increased system complexity.
Solution Approach 2:
The system enables self-service meeting organization by automatically processing entity data and event activation data without requiring manual human intervention. The automated system gathers data, performs feature extraction, refines event timing using language models, and executes meeting scheduling independently, reducing time loss while the system complexity is managed through automated self-processing.
3Productivity
If systematic prioritization and templates are implemented for meeting organization, then productivity improves, but device complexity increases due to additional processing requirements
Solution Approach 1:
The system improves meeting prioritization productivity by changing key parameters through automated data processing. Entity data and event activation data are transformed through feature extraction and language model refinement, converting raw data into structured, prioritized meeting schedules. This parameter transformation enables systematic prioritization while managing complexity through automated computational processes.
Solution Approach 2:
The patent introduces intermediary processing components between data gathering and meeting execution. The preprocessing module with feature extraction and the time datum language model act as intermediaries that refine raw entity data and event activation data into structured formats suitable for automated meeting scheduling, improving productivity while managing system complexity through layered processing architecture.
Data Source
AI summary
Described herein is an apparatus and method for automating interactions. In some embodiments, apparatus may gather system data, determine event activation data as a function of system data, execute an event by communicating event activation data to an external device, and update system data based on execution of an event.