Persona-Based Content Recommendations for Contextual Relevance
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Solution Overview
Problem
Conventional content recommendation systems lack relevance to users, presenting results without context, leading to perceived irrelevance.
Innovation Solution
Implement a system that generates and displays content recommendations using personas tailored to individual user preferences, based on device data, to create personalized and relevant content groupings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional content recommendation systems present results without context, then the system complexity is reduced, but the relevance to users deteriorates
Solution Approach 1:
The patent segments the content recommendation system into multiple personas, each representing different user interests and preferences. Instead of presenting all content recommendations in a single undifferentiated list, the system divides recommendations into persona-specific groupings (e.g., sports enthusiast, movie buff, music lover), allowing users to select the persona that best matches their current mood or interest. This segmentation maintains system simplicity while improving relevance by contextualizing recommendations according to user preferences.
2Reliability
If content recommendations are personalized using personas, then relevance to users is improved, but device complexity increases
Solution Approach 1:
The patent implements personas as universal templates that can be applied across different content types and platforms. Each persona serves multiple functions: it aggregates content across different categories, provides contextual framing for recommendations, and can be selected by users based on their current preferences. This multi-functionality allows the system to achieve personalization without proportionally increasing complexity, as the same persona structure handles diverse content recommendation scenarios.
3Ease of operation
If users must search or browse for content without contextual groupings, then the ease of operation is reduced, but the loss of time is minimized
Solution Approach 1:
The patent applies preliminary action by pre-organizing content recommendations into persona-specific groupings before the user requests them. When the system generates recommendations, it proactively categorizes content according to different personas (e.g., grouping sports content together, movie content together) rather than requiring users to manually search or filter. This preliminary organization significantly reduces the time users spend searching while maintaining ease of operation, as users can quickly scan persona groupings and select their preference.
Data Source
AI summary
Systems and methods for generating and displaying groupings of content recommendations using personas are provided. The system determines content for each of the plurality of personas. The determined content for each of the plurality of personas comprises content that shares a common genre or theme for each persona. The system populates each of the plurality of personas using the determined content for each of the plurality of personas. The system then causes display of at least some of the plurality of personas on a viewing device of a user. The at least some of the plurality of personas is selected for the user based on device data corresponding to the user, whereby the device data indicates user preferences and interactions with previous content.