Content Recommendation Storage Segmentation for Faster Personalization
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Solution Overview
Problem
Consumers face challenges in discovering new content due to the vast array of choices available, leading to dissatisfaction and inefficiency in content selection, despite advancements in content access technologies like EPGs and personal video recorders.
Innovation Solution
A content recommendation system that maintains user data in both a first storage resource (e.g., hard disk) and a second storage resource (e.g., RAM) during a recommendation session, generating personalized recommendations using user data and content information, and updating user data in real-time to enhance content suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If content recommendation system maintains user data in both first storage resource (hard disk) and second storage resource (RAM) during recommendation session, then content recommendation speed and personalization accuracy are improved, but system complexity and memory resource consumption increase
Solution Approach 1:
The patent divides user data storage into two segments: a first storage resource (hard disk) for long-term persistent storage and a second storage resource (RAM) for temporary session-based storage. This segmentation allows the system to load only necessary user data into memory during recommendation sessions, enabling fast personalized recommendations while maintaining overall system manageability through clear separation of permanent and temporary data storage functions.
2Loss of time
If user data is stored in contiguous physical locations in storage resource, then data access speed and recommendation generation time are improved, but storage flexibility and data organization complexity increase
Solution Approach 1:
The patent implements preliminary action by pre-organizing user data in contiguous physical storage locations and pre-loading relevant user data into the second storage resource (RAM) before the recommendation generation process begins. This preliminary organization and loading of data in sequential memory locations eliminates access delays during actual recommendation generation, significantly reducing recommendation generation time while the contiguity requirement is managed through systematic data structure design.
3Adaptability or versatility
If the system maintains content recommendation sessions for a plurality of users simultaneously in the second storage resource, then user service capability and recommendation personalization are improved, but memory resource consumption and system load increase
Solution Approach 1:
The patent applies partial action by maintaining only the necessary portion of user data in the second storage resource (RAM) during recommendation sessions - specifically, only the user profile information and preference data needed for generating recommendations are kept in memory, while complete user histories and less frequently accessed data remain in the first storage resource. This selective partial loading enables the system to serve multiple users simultaneously with personalized recommendations while controlling memory resource consumption by loading only essential data for each active session.
Data Source
AI summary
The method may include providing one or more content item recommendations, by opening a content recommendation session for a selected user, retrieving some user data for the selected user from a first storage resource, obtaining content information concerning content available from content sources, using the user data and the content information to generate a content item recommendation for the user and providing the content item recommendation to the user. The user data for the selected user may be stored at contiguous physical locations at the first storage resource.