Message Aggregation Exclusion for Important Senders
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Solution Overview
Problem
Users face the challenge of manually sifting through numerous redundant and uninteresting messages in social media and messaging applications, leading to important messages being overlooked due to their proximity to repetitive or uninteresting content.
Innovation Solution
An AI-powered system that groups similar messages and allows users to treat them as a single entity, with options to expand and review individual messages, while considering attributes like sender relationship, message content, and sender stature to exclude unique or important messages from aggregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If messages are aggregated into groups based on common topics, then the volume of messages to review is reduced, but important messages from specific senders may be overlooked
Solution Approach 1:
The system applies different aggregation rules to different senders based on their importance attributes. Messages from important senders (celebrities, family members, close contacts) are excluded from aggregation and displayed individually, while messages from other senders are aggregated into groups. This local differentiation resolves the contradiction by preserving important messages while still reducing overall message volume.
Solution Approach 2:
The message stream is segmented into two distinct categories: aggregated messages from regular senders and individual messages from important senders. This segmentation allows the system to apply different processing rules to different segments, ensuring that important messages are not lost in aggregation while still providing volume reduction for non-critical messages.
2Productivity
If all messages with common topics are grouped together, then message volume is reduced, but the ability to identify unique important messages is diminished
Solution Approach 1:
The system evaluates each message's sender attributes locally to determine whether it should be aggregated or displayed individually. Messages with unique attributes (from important senders) are identified and treated differently from standard messages, preserving their distinctiveness while allowing bulk aggregation of non-unique messages.
Solution Approach 2:
Instead of aggregating all messages with common topics and then trying to identify important ones, the system inverts the approach by first identifying important messages based on sender attributes and excluding them from aggregation. This ensures that unique important messages are preserved before the aggregation process begins.
3Reliability
If manual review of each message is performed to identify important messages, then message importance is accurately identified, but the process becomes tedious and error-prone
Solution Approach 1:
The system automatically performs the task of identifying important messages by evaluating sender attributes (celebrity status, relationship to recipient, etc.) without requiring manual user intervention. This self-service approach resolves the contradiction by automating the reliability-critical task of importance identification, eliminating the need for tedious manual review while maintaining accurate identification.
Solution Approach 2:
The manual mechanical process of reviewing each message is replaced with an automated computational system that evaluates message attributes and applies aggregation rules. This substitution eliminates human effort and error while maintaining reliable identification of important messages through algorithmic analysis of sender characteristics.
Data Source
AI summary
Messages, such as text messages, emails, and social media posts, are a popular way to communicate, however, messages can be overwhelming. In order to better manage messages, messages may be grouped, such as those having a common topic. A recipient may then address the grouped messages as a group. However, certain messages may have a common topic but have an attribute that warrants maintaining the message as individual messages, excluded from the group. For example, the message may be from someone who rarely communicates with the recipient, a celebrity, an important figure at work or in politics, a family member, or other attribute that would warrant exclusion from a common topic group.