Digital Assistant Intent Scheduling for Calendar Conflict Management
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Solution Overview
Problem
Conventional digital personal assistants lack the ability to efficiently infer user intents and automatically schedule activities or meetings based on user interactions and behavioral trends, requiring manual intervention for scheduling and conflict management.
Innovation Solution
Implementing intent-based scheduling logic that analyzes user communications and behavioral patterns to automatically propose and schedule activities, update calendars, and manage conflicts, using digital personal assistants to infer user intents and automate scheduling processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional digital personal assistants react to specific user requests, then they can perform basic scheduling tasks, but they lack the ability to efficiently infer user intents and automatically schedule activities
Solution Approach 1:
The system enables self-service by automatically inferring user intent from communications and behavioral patterns, then autonomously scheduling activities without requiring explicit user commands. The digital personal assistant analyzes communication data, identifies meeting intents, checks calendar availability, and schedules events automatically, allowing the system to serve itself in the scheduling process.
Solution Approach 2:
The system performs preliminary action by proactively analyzing communications and behavioral patterns before the user explicitly requests scheduling. It infers user intent in advance, prepares scheduling options based on calendar availability, and presents scheduled activities to the user for confirmation, thereby performing the scheduling work before the user becomes aware of the need for it.
2Productivity
If manual intervention is used for scheduling and conflict management, then scheduling accuracy can be maintained, but scheduling efficiency and productivity are reduced
Solution Approach 1:
The system implements feedback by continuously monitoring user responses to scheduled activities and using this information to refine future scheduling decisions. When users accept, modify, or reject scheduled events, the system learns from this feedback to improve its intent inference accuracy and scheduling timing, creating a closed-loop system that progressively improves productivity while reducing manual effort.
Solution Approach 2:
The system replaces the mechanical system of manual scheduling with an automated information processing system. Instead of users manually checking calendars, identifying conflicts, and coordinating schedules, the digital personal assistant uses communication analysis and pattern recognition to automatically perform these tasks, substituting human manual effort with automated computational processes that increase productivity and eliminate time loss.
3Extent of automation
If the digital personal assistant analyzes communications to infer user intent, then automatic scheduling capability is improved, but resource consumption increases
Solution Approach 1:
The system applies partial action by selectively analyzing only the communications and behavioral patterns that contain scheduling-related intent signals, rather than processing all user data. It uses targeted analysis of communication content, sender-receiver relationships, and contextual patterns to infer intent, performing only the necessary processing to achieve automatic scheduling without excessive resource consumption on irrelevant data.
Solution Approach 2:
The system changes parameters by adjusting the depth and scope of communication analysis based on the context and confidence level of intent detection. When communications clearly indicate scheduling intent, the system performs comprehensive analysis; when intent is ambiguous, it reduces analysis depth and seeks additional contextual clues, thereby dynamically optimizing resource usage while maintaining effective intent inference capability.
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.