Email Task Extraction via Word Numbering and GUI Hero Cards
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Solution Overview
Problem
Current email communication systems lack efficient methods for identifying and tracking actionable requests, leading to decreased user efficiency and increased likelihood of missed tasks due to manual tracking processes.
Innovation Solution
A system and method that extracts actionable items from emails by assigning numbers to words using a library, determining actionable content, and presenting it on a graphical user interface (GUI) through highlighting, hero cards, and statistical representations to facilitate tracking and reminders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual tracking methods (writing down, calendar input, flagging) are used to track actionable items, then users can remember tasks, but users spend excessive time searching through emails and to-do lists to locate pending tasks
Solution Approach 1:
The patent extracts actionable items from email content using natural language processing and machine learning. The system identifies and separates actionable portions (tasks) from the rest of the email, presenting them in a dedicated task list or hero card. This extraction eliminates the need for users to manually search through email threads to find pending tasks, directly reducing search time while maintaining reliable task tracking.
Solution Approach 2:
The patent introduces an intermediary layer (the email client's automated processing system) that acts as a mediator between incoming emails and the user's task management. This intermediary automatically parses emails, identifies actionable items, and integrates them into the user's task tracking system, eliminating the manual intermediary steps of writing down tasks and manually checking to-do lists.
2Ease of operation
If users manually identify and track actionable items in emails, then they can manage tasks, but their overall efficiency decreases due to the manual nature of the process
Solution Approach 1:
The patent enables the email system to serve itself by automatically identifying and extracting actionable items without user intervention. The machine learning model autonomously parses email content, determines what constitutes an actionable item, and presents it to the user in a structured format. This self-service capability eliminates manual effort entirely while improving productivity through automated processing of multiple emails simultaneously.
Solution Approach 2:
The patent replaces the mechanical manual process of reading, analyzing, and tracking tasks with an automated computational system. Natural language processing algorithms and machine learning models substitute for human cognitive effort in identifying actionable items, transforming a manual cognitive task into an automated computational process that scales efficiently.
3Device complexity
If users rely on memory to remember tasks, then they don't need external tracking, but they easily forget to complete tasks
Solution Approach 1:
The patent segments the task management function from the email reading process. Actionable items are extracted and presented in a separate, dedicated interface (task list or hero card) distinct from the email content. This segmentation allows users to focus on reading emails while the system separately manages task tracking, providing reliable reminders without adding complexity to the email interface itself.
Data Source
AI summary
Systems and methods herein assist users by identifying actionable tasks in an email and providing reminders and other tracking mechanisms for those tasks. For example, a method can include extracting a portion of the email and assigning a number to each word of the extracted portion of the email according to a library. The method can further include determining, based on the assigned numbers, whether the extracted portion of the email includes at least one actionable portion. In response to determining that the extracted portion of the email includes at least one actionable portion, at least one actionable portion can be presented to the user on a GUI associated with the user's device.