Task Management Application Context Filtering

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Solution Overview

Problem

Electronic task management systems often overwhelm users with irrelevant or contextually inappropriate tasks, degrading the user experience and wasting computing resources.

Innovation Solution

A unified interface is provided for accessing and manipulating task items from multiple sources, using relational data and user interactions to filter out irrelevant tasks and improve task management efficiency, with features like proxy tasks, heuristic engines, and context listeners to present relevant tasks based on user behavior and context.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If tasks are added easily to an electronic task manager, then task management functionality is enhanced, but users become overwhelmed with irrelevant or contextually inappropriate tasks

Engineering Contradiction:

Improvetask management functionalityVSAvoiduser overwhelm from irrelevant tasks

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

The system implements feedback mechanisms by monitoring user interactions with tasks (completion, dismissal, marking as irrelevant) and using this feedback to train machine learning models that predict task relevance, thereby reducing irrelevant tasks in future recommendations

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system performs self-service by automatically filtering and prioritizing tasks based on learned user preferences and contextual data, reducing manual user effort in managing irrelevant tasks while maintaining enhanced task management functionality

Inventive Principle:

Principle #25Self-service

2Quantity of substance

If tasks from multiple sources are aggregated, then task comprehensiveness is improved, but computing resources are wasted on processing unwanted tasks

Engineering Contradiction:

Improvetask comprehensivenessVSAvoidcomputing resource waste

Core Design Contradiction:

Quantity of substanceVSLoss of energy

Solution Approach 1:

The system extracts only the most relevant tasks from multiple sources using machine learning predictions and contextual filtering, discarding unwanted tasks before they consume significant computing resources, thereby maintaining task comprehensiveness while reducing resource waste

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system changes parameters by dynamically adjusting task priority scores and relevance thresholds based on user behavior patterns and contextual data, allowing efficient resource allocation by focusing processing on high-priority tasks while minimizing processing of low-priority unwanted tasks

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS11823105B2Efficiency enhancements in task management applications

Publication Date: 2023.11.21 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Efficiency improvements for electronic task managers and an improved user experience are realized when more relevant and fewer irrelevant tasks are presented to users and users are given greater control in manipulating those task items. By heuristically determining times, locations, and semantics associated with task relevance and integrating the management of tasks into more applications, the functionality of the systems providing for electronic task management is improved, as computer resources are spent with greater utility to the users and the user experience is improved for the users.