Message Affinity Grouping Across Heterogeneous Messaging Channels
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Solution Overview
Problem
Existing message processing systems lack effective methods to group and cluster messages across different messaging techniques, limiting user ability to organize and relate messages efficiently.
Innovation Solution
A method and apparatus that create message address affinity groups by determining related message addresses based on probability and timestamp analysis, allowing for the organization of messages and threads into meaningful clusters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If messages are grouped using traditional email threading or manual folder rules, then basic message organization is achieved, but the system cannot effectively cluster messages across different messaging techniques (email, instant messaging, social network messaging, cellular messages)
Solution Approach 1:
The patent applies universality by creating a unified message affinity group system that works across multiple messaging techniques (email, instant messaging, social network messaging, cellular messages). Instead of maintaining separate threading systems for each message type, the invention uses a single affinity group mechanism based on message address analysis that can cluster messages from different sources, achieving multi-functional message organization capability.
Solution Approach 2:
The patent introduces message address affinity groups as an intermediary structure that mediates between raw messages from different sources and the user's organizational needs. These affinity groups serve as a intermediate layer that captures message relationships through address analysis, enabling cross-messaging-type clustering without requiring direct integration of each messaging platform's native organization system.
2Productivity
If no automated clustering is implemented, then user control over message organization is maintained, but message management efficiency decreases and users must manually organize large collections of messages
Solution Approach 1:
The patent applies self-service by implementing automated affinity group computation that operates without continuous user intervention. The system automatically analyzes message addresses, computes affinity groups, and organizes messages into clusters based on detected relationships. This automated self-organizing capability improves message management efficiency while the algorithm processes messages in the background without requiring user awareness or action.
Solution Approach 2:
The patent replaces manual mechanical message organization (drag-and-drop, folder creation, rule-based filing) with an automated computational system. Instead of users physically organizing messages through manual operations, the system uses affinity group algorithms to automatically compute and establish message relationships, substituting mechanical user actions with computational processes that scale to large message collections.
3Measurement precision
If affinity groups are computed using all message addresses, then comprehensive message clustering is achieved, but computational resources and processing time increase
Solution Approach 1:
The patent applies partial action by computing affinity groups based on selected message addresses rather than exhaustively processing all addresses in every message. The system strategically chooses which addresses to analyze for affinity computation, focusing on key addresses that provide the most meaningful clustering information. This selective approach maintains adequate clustering accuracy while reducing computational overhead and processing time compared to analyzing every single address.
Data Source
AI summary
A method and apparatus of a device that focuses messages is described. In an exemplary method, the device receives a first and second group of message. The device further selects a related message from the second group of messages that is related to each message in the first group. This selecting is based on an affinity group, where the affinity group includes a message address that occurs in at least one of the messages in the second group and the affinity group is determined using the message addresses contained in the first and second groups.