Dynamic Contact Ranking for Personalized Online Service Feeds
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Solution Overview
Problem
Existing online services lack effective personalization methods to curate relevant content for users based on their interactions and communications, leading to information overload and inefficient use of user time.
Innovation Solution
A system and method that stores person profiles associated with communications received by a user, filters data using a processor to rank contacts based on relevance, and creates dynamic lists for personalized content presentation on various devices, allowing users to follow important contacts without explicitly following them.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually follow every contact they want to receive updates from, then they can ensure they receive all relevant information, but this requires significant time and effort to maintain
Solution Approach 1:
The system automatically analyzes user communications and email patterns to identify and rank important contacts without user intervention. The processor autonomously creates dynamic lists of people the user should follow based on communication frequency, recency, and importance, eliminating manual follow management while ensuring comprehensive information coverage
Solution Approach 2:
The system performs preliminary analysis of communication patterns and contact importance before the user needs to follow anyone. By pre-processing communication data and ranking contacts in advance, the system prepares ready-to-follow lists that users can adopt immediately without time-consuming manual selection
2Reliability
If users follow many contacts to ensure they don't miss important information, then information completeness improves, but information overload and noise increase
Solution Approach 1:
The system applies different quality thresholds and filtering criteria to different contact groups. Important contacts identified through communication analysis receive higher priority and their information is filtered differently than less important contacts, ensuring that only high-quality, relevant information from each segment reaches the user's feed
Solution Approach 2:
The system dynamically adjusts information filtering parameters based on contact importance rankings. For highly-ranked contacts, the system applies more permissive filtering to ensure completeness, while for lower-ranked contacts, stricter filtering reduces noise, optimizing the balance between information completeness and noise reduction
3Ease of operation
If the system provides personalized content curation, then user experience improves, but system complexity increases
Solution Approach 1:
The system introduces an intermediary processing layer that automatically analyzes communication patterns, ranks contacts, and generates dynamic following lists. This intermediary processor handles the complexity of personalization algorithms, user behavior analysis, and contact ranking, shielding users from system complexity while delivering personalized content curation
4Measurement precision
If the system dynamically ranks contacts based on communication patterns, then personalization accuracy improves, but data processing requirements increase
Solution Approach 1:
The system applies partial analysis to the full contact database by focusing computational resources on the most recently communicated contacts and those with highest communication frequency. Rather than continuously re-ranking all contacts, the system updates rankings selectively based on new communication events, reducing overall processing energy while maintaining personalization accuracy
Data Source
AI summary
An Internet or other online service is personalized or customized based on data collected for a user of a computing device. In one embodiment, a method includes: storing a plurality of person profiles for persons associated with communications received by a user of a computing device; receiving data associated with an online service; and filtering, using at least one processor, the data based on the plurality of person profiles, wherein the filtered data is for display to the user on the computing device.