Trip-Aware Content Recommendation Suppression
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Solution Overview
Problem
Content platforms often recommend content that is already available on other platforms the user will access during trips, leading to a lack of engaging content for users during travel or transit.
Innovation Solution
A system and method that modify content recommendations by identifying content items available on platforms the user will access during trips, comparing user preferences with available content, and suppressing recommendations for content already available on those platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If content recommendations are based on user viewing history and preferences, then content relevance to user interests is improved, but content redundancy with other platforms increases
Solution Approach 1:
The system performs preliminary actions by checking calendar data to identify future trips and content platform availability before generating recommendations. It proactively determines which content will be available on other platforms during upcoming trips and suppresses those recommendations in advance, preventing redundancy before it occurs.
Solution Approach 2:
The system implements feedback by continuously monitoring user calendar data for trip information, checking content availability on other platforms, and using this information to adjust recommendations. The recommendation system receives feedback about user location and platform accessibility, then modifies its output accordingly to avoid suggesting content already available elsewhere.
2Productivity
If content recommendations are generated without considering other platform availability, then recommendation processing speed is improved, but user content consumption quality deteriorates
Solution Approach 1:
The system performs preliminary checks of trip calendar data and content platform availability before the recommendation generation process. By pre-identifying time periods when users will have access to other platforms and pre-determining which content to suppress, the system avoids adding computational overhead during the actual recommendation generation, thus maintaining speed while improving quality.
3Measurement precision
If the system checks calendar data and other platform content availability, then content recommendation quality is improved, but system complexity increases
Solution Approach 1:
The system achieves multi-functionality by using the existing user profile and recommendation engine for both traditional content recommendations and trip-aware recommendations. The same recommendation infrastructure is leveraged to handle both standard cases and trip-modified cases, reducing the need for separate complex systems while improving recommendation quality.
Data Source
AI summary
Systems and methods are described herein for modifying content recommendations based on what content items will be available on content platforms to which the user will have access during a trip. Content items to be recommended to the user on a first content platform are identified by comparing characteristics of each available content item to a profile associated with the user. A second content platform to which the user will have access during a particular time period in the near future is also identified. The second content platform is queried to identify content items that will be available during the particular time period. If any content item available on the second content platform during the particular time period also appears in the set of content items identified for recommendation, recommendation of that content item is suppressed.