Chat Highlights System for Social Media Message Retrieval
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Solution Overview
Problem
Users face difficulty in finding specific past messages in social media platforms due to their disorganized nature, requiring significant time and effort, which leads to missed opportunities for reconnecting with friends and inefficient use of storage resources.
Innovation Solution
The system automatically scores and highlights relevant conversation segments based on criteria such as message frequency, time elapsed, and content type, presenting interactive visual indicators to users, allowing easy access to previously important messages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually search through all past messages to find specific interactions, then they can locate the desired message, but it requires significant time and effort
Solution Approach 1:
The system pre-processes and analyzes message content in advance, generating summaries, extracting key entities, and organizing messages by topic or importance before the user needs to search. This preliminary organization enables rapid retrieval without manual scanning through all past messages.
Solution Approach 2:
The patent introduces an intelligent search intermediary that acts as a bridge between the user and the message database. This intermediary automatically understands search queries, filters relevant messages using NLP techniques, and presents ranked results, eliminating the need for users to manually browse through all messages.
2Reliability
If all past messages are stored for future reference, then users can revisit conversations, but storage resources are inefficiently used
Solution Approach 1:
The system extracts only the most essential and relevant information from complete message conversations, storing condensed representations rather than full message histories. Key entities, topics, and important exchanges are preserved while redundant or less significant content is summarized or omitted, reducing storage requirements while maintaining conversation accessibility.
Solution Approach 2:
Different levels of detail are stored for different messages based on their importance and relevance. Frequently accessed or significant conversations are preserved in full detail, while less important messages are stored as summaries or metadata. This differential storage strategy optimizes both accessibility and storage efficiency.
3Stability of the object's composition
If messages are organized chronologically without filtering, then all conversations are preserved, but users cannot quickly identify meaningful content
Solution Approach 1:
The message database is segmented into multiple organized categories including chronological sequences, topic-based groups, importance-ranked collections, and interaction-type classifications. Users can access messages through any relevant segment rather than browsing a single undifferentiated list, making meaningful content immediately identifiable.
Solution Approach 2:
The system applies visual indicators and highlighting to differentiate message importance, types, and relevance. Key messages are visually distinguished through formatting, icons, or positioning, enabling users to quickly identify meaningful content without reading every message in chronological order.
Data Source
AI summary
Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for presenting chat highlights. The program and method include generating a group profile for a plurality of users that includes a plurality of conversation segments; identifying a group of consecutively exchanged messages in a first of the plurality of conversation segments for which a difference between a starting time stamp of a first message in the group of consecutive messages and an ending time stamp of a last message in the group of consecutive messages is less than a threshold time interval representing consecutively exchanged messages; generating for display an interactive visual representation of the identified group of consecutive messages; and in response to receiving a user input that selects the interactive visual representation, generating for display a portion of the identified group of consecutive messages.