Digital Personal Assistant Intent Scheduling for Conflict Management
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Solution Overview
Problem
Conventional digital personal assistants lack the ability to efficiently schedule activities based on inferred user intent and manage conflicts, requiring manual user intervention.
Innovation Solution
Implement intent-based scheduling logic that analyzes user communications and behavioral trends to automatically propose and schedule activities, update calendars, and manage conflicts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional digital personal assistants are used to schedule activities, then basic task execution is possible, but manual user intervention is required and scheduling efficiency is low
Solution Approach 1:
The system enables self-service scheduling by automatically analyzing user communications and behavioral trends to infer scheduling intent, eliminating the need for manual user intervention in the scheduling process while maintaining ease of use
Solution Approach 2:
The patent replaces manual mechanical scheduling operations with automated computational analysis of communications and behavioral data, substituting human effort with intelligent system processing to improve scheduling efficiency
2Productivity
If automated intent-based scheduling is implemented, then scheduling efficiency and accuracy improve, but system complexity increases
Solution Approach 1:
The digital personal assistant is enhanced with multi-functionality to perform both traditional task execution and new intent-based scheduling functions, consolidating diverse capabilities into a single system rather than adding separate complex systems
Solution Approach 2:
The system uses communication analysis and behavioral trend data as intermediary inputs to infer scheduling intent, creating a layered approach that manages complexity by processing information through intermediate stages rather than direct complex decision-making
3Measurement precision
If communication analysis is performed to infer user intent, then scheduling accuracy improves, but processing time and resource consumption increase
Solution Approach 1:
The system performs partial analysis of communications and behavioral trends, focusing on key indicators of scheduling intent rather than complete exhaustive analysis, achieving sufficient accuracy while reducing processing resources
Solution Approach 2:
The system pre-processes and stores communication and behavioral data for efficient retrieval during scheduling operations, performing preliminary organization of information to reduce real-time processing requirements and resource consumption
Data Source
AI summary
Techniques are described herein that are capable of performing intent-based scheduling via a digital personal assistant. For instance, an intent of user(s) to perform an action (a.k.a. activity) may be used to schedule time (e.g., on a calendar of at least one of the user(s)) in which the action is to be performed. Examples of performing an action include but are not limited to having a meeting, working on a project, participating in a social event, exercising, and reading.