Social Graph Email Filtering for Spam and Delivery Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In enterprise communications networks, users face challenges in managing and filtering email messages due to high volumes of irrelevant or non-urgent communications, making it difficult to distinguish between important and unimportant messages, especially since traditional email filters are less effective within the network and often block necessary communications from known senders.
Innovation Solution
The proposed solution utilizes a social graphing system to categorize and manage email delivery based on the social relationships between senders and recipients, allowing for tagging of senders and automated or manual assignment of metadata to control deliverability, prioritize messages, and block unwanted communications, thereby organizing and filtering messages effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If traditional email filters are used to block messages, then spam and junk email can be blocked, but important messages from known senders within the enterprise may be incorrectly blocked
Solution Approach 1:
The patent applies local quality by differentiating filtering rules based on the sender-recipient relationship context. Instead of uniform filtering, the system creates relationship-specific tags (e.g., supervisor, colleague, friend) that determine different delivery behaviors for different senders to the same recipient, allowing important messages to pass while blocking spam.
Solution Approach 2:
The patent introduces an intermediary social graph layer between the email filter and the message delivery system. This social graph acts as a mediator that evaluates sender-recipient relationships and determines appropriate delivery actions, preventing direct conflict between spam blocking and important message delivery.
2Productivity
If email filters are made more aggressive to block more spam, then spam blocking improves, but the number of false positives increases
Solution Approach 1:
The patent changes the filtering parameter from message content analysis to relationship-based tagging. By transforming the filtering criterion from what the message says to who the sender is in relation to the recipient, the system achieves high spam blocking efficiency without losing important messages, as the relationship context preserves delivery decisions.
Solution Approach 2:
The patent performs preliminary action by pre-tagging senders with relationship information before messages are filtered. This advance classification of senders into relationship categories enables the filtering system to make accurate decisions without needing to analyze message content, reducing false positives while maintaining high spam blocking rates.
3Ease of operation
If manual tagging of senders is implemented to improve message sorting, then message organization improves, but the time and effort required increases
Solution Approach 1:
The patent applies self-service by enabling the system to automatically tag senders based on their interaction patterns with the recipient. The social graph system autonomously analyzes communication history and relationships, assigning tags without requiring manual user input, thus maintaining ease of message organization while eliminating the time cost of manual tagging.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors message interactions and automatically updates relationship tags based on observed patterns. This feedback loop allows the system to self-optimize message organization without user intervention, maintaining ease of operation while minimizing time investment from users.
4Reliability
If comprehensive sender tagging is implemented to improve deliverability control, then message delivery accuracy improves, but system complexity increases
Solution Approach 1:
The patent applies universality by designing the social graph system to serve multiple functions simultaneously: it tags senders, determines delivery rules, organizes messages, and provides filtering decisions. This multi-functional approach consolidates what would otherwise require separate systems into a single framework, managing complexity while maintaining high deliverability control.
Solution Approach 2:
The patent segments the sender population into distinct relationship categories within the social graph (e.g., supervisor, colleague, friend, external). This segmentation allows the system to apply simple, rule-based delivery decisions to each segment, reducing overall system complexity compared to attempting to evaluate each sender individually without categorization.
Data Source
AI summary
Architecture that enables data handling according to types of social relationships. A social graph is used to categorize the types of the social relationships of the tagged messaging users. The social graph can include social relationship categories for friends, family, coworkers, and blocked individuals of the recipient, for example. The social graph can also include metadata related to the tagged users. The metadata defines the social relationship of the tagged users to the recipient. Delivery of messages to the recipient from the tagged messaging users is managed based on the social graph. Delivery management can include blocking messages, allowing the messages through, or delivering the messages with high or low priority, for example. Email messages can be delivered to respective email locations based on the social graph. User information can be imported and/or mined from external sources to augment the social graph.