Automated Non-Textual Reply Content Attachment
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Solution Overview
Problem
Users face difficulties in efficiently including non-textual reply content, such as documents or links, in electronic communication responses, as they must manually browse and select appropriate content, which is time-consuming and not integrated with the response composition process.
Innovation Solution
The system determines and provides non-textual reply content based on message features of the electronic communication, using machine learning to identify relevant documents from various corpuses, such as cloud storage or local devices, and integrates them into the response independently of user input, using search parameters derived from the communication's content and analyzing past communication patterns to suggest or automatically attach appropriate content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If users manually browse and select non-textual reply content, then they can include relevant documents in replies, but the process becomes time-consuming and inefficient
Solution Approach 1:
The system performs preliminary actions by automatically searching for and identifying relevant non-textual content (documents, images, videos) from the user's device storage before the user completes composing the reply. This advance preparation eliminates the need for manual browsing during the reply composition process, directly resolving the time loss issue while maintaining productivity.
Solution Approach 2:
The system enables self-service by autonomously analyzing the incoming electronic communication, determining appropriate reply content based on message features, and automatically attaching relevant non-textual content without requiring user intervention. The system serves itself by managing the document attachment process independently, thus improving productivity without adding time burden.
2Ease of operation
If the system automatically determines and provides non-textual reply content, then user efficiency is enhanced, but the system complexity increases
Solution Approach 1:
The patent replaces the mechanical manual browsing and selection process with an automated electronic system that analyzes message features and automatically retrieves relevant content. This substitution eliminates the need for complex user interactions while managing system complexity through algorithmic approaches rather than mechanical interfaces.
Solution Approach 2:
The system changes parameters by analyzing various message features (text content, sender, recipient, context) and using these parameters to automatically determine which non-textual content should be attached. By transforming the manual selection process into a parameter-driven automated decision process, the system improves ease of operation while containing complexity through structured parameter analysis.
3Measurement precision
If the system searches through multiple corpuses to identify relevant documents, then the accuracy of suggested content increases, but the search time and processing load increase
Solution Approach 1:
The system performs preliminary indexing and organization of non-textual content across multiple corpuses (device storage, cloud storage, network storage) before they are needed for reply composition. This advance preparation allows the automated search to quickly retrieve accurate content without time-consuming searches during the actual reply process, maintaining precision while reducing time loss.
Solution Approach 2:
The system uses feedback mechanisms where the analysis of message features and the results from searching multiple corpuses are continuously refined. By analyzing which content is most relevant based on message parameters and adjusting the search strategy accordingly, the system improves accuracy over time while optimizing search efficiency to minimize processing time and load.
Data Source
AI summary
Methods and apparatus related to determining non-textual reply content for a reply to an electronic communication and providing the non-textual reply content for inclusion in the reply. Some of those implementations are directed to determining, based on an electronic communication sent to a user, one or more electronic documents that are responsive to the electronic communication, and providing one or more of those electronic documents for inclusion in a reply by the user to the electronic communication. For example, the electronic documents may be automatically attached to the reply and/or link(s) to the electronic documents automatically provided in the reply.