Personalized Spam Filtering via User Interaction Monitoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional spam filtering techniques often result in false positives due to varying user definitions of spam, leading to legitimate emails being filtered out, which can frustrate users and diminish their email experience.
Innovation Solution
A personalized spam filtering system that monitors user interaction with messages, such as time spent on each email, to develop a reputation for senders and filter subsequent messages based on user interest, thereby determining the relative importance of messages and organizing them for display in a user interface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If generalized spam filters are used to detect spam by analyzing message signatures, then spam filtering capability is improved, but false positives increase causing legitimate emails to be filtered out
Solution Approach 1:
The patent segments the spam filtering approach by dividing users into different groups (spam recipients and non-spam recipients) based on their interaction patterns, and applies different filtering strategies to each segment. This allows the system to maintain high reliability in spam detection while reducing false positives for legitimate emails by adapting to individual user preferences and behaviors.
Solution Approach 2:
The system dynamically adapts the spam filtering behavior based on monitored user interactions with messages. As users engage with emails (opening, deleting, marking as spam), the system continuously updates its understanding of what constitutes spam for that specific user, making the filtering criteria dynamic rather than static. This resolves the contradiction by allowing the filter to be both reliable (consistent spam detection) and precise (accurate distinction based on user context).
2Device complexity
If generalized spam filters are applied uniformly to all users, then implementation simplicity is improved, but user experience deteriorates due to false positives filtering out interesting emails
Solution Approach 1:
The system enables users to effectively customize their own spam filtering experience without manual configuration. By automatically monitoring user interactions with messages and inferring spam preferences from these behaviors, the system allows each user to self-define what spam means to them. This maintains implementation simplicity while dramatically improving user experience, as the filter adapts to individual needs without requiring complex setup or maintenance by the user.
3Measurement precision
If user interaction monitoring is implemented to personalize spam filtering, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system achieves universal applicability by designing a monitoring and adaptation mechanism that works across all users and message types without requiring user-specific configuration. The same core infrastructure monitors interactions, learns patterns, and applies filtering across diverse user contexts. This multi-functional approach allows the system to achieve high measurement precision for each user while avoiding the complexity of implementing separate customized systems for different users.
Data Source
AI summary
Embodiments of message organization and spam filtering based on user interaction are presented herein. In an implementation, user interaction with a plurality of messages in a user interface is monitored, which includes analyzing an amount of time spent by a user in interacting with each message. Subsequent messages may then be filtered based on the monitored user interaction. In another implementation, messages are processed that are received via a network using a spam filter that was generated based on monitored interaction of a user with previous messages. The processing results in a value describing a relative likelihood of importance of each of the processed message to the user. The processed messages are then arranged for display in an order, one to another, in a user interface based on respective values.