Experience Broker Content Curation for Secure Personalized Browsing
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Solution Overview
Problem
Existing online platforms fail to dynamically tailor user experiences to individual needs and preferences, particularly for users with accessibility challenges or age-inappropriate content, leading to inconsistent and insecure content delivery across devices.
Innovation Solution
A dynamic experience curation platform utilizing AI and ML techniques, including neural networks and generative models, processes content requests to filter out unwanted content, generate curated content consistent with user preferences, and manage seamless delivery across devices, integrating user profiles and preferences for personalized and secure browsing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is dynamically curated and personalized for each user, then user experience and relevance are improved, but system complexity and processing requirements increase
Solution Approach 1:
The patent introduces an Experience Broker as an intermediary service between users and content sources. This broker dynamically curates content by extracting information from multiple sources, applying user preference rules, and generating personalized responses. The broker handles the complexity of content aggregation and personalization centrally, allowing client applications to remain simple while still delivering highly adapted content to each user.
Solution Approach 2:
The system replaces traditional mechanical content delivery mechanisms with AI-powered natural language processing and generative models. Instead of rigid content filtering and static page layouts, the system uses LLMs to dynamically generate personalized content responses based on user preferences and context, substituting complex mechanical filtering systems with intelligent generation.
2Reliability
If content filtering and curation processes are enhanced, then content quality and safety are improved, but processing time and latency increase
Solution Approach 1:
The system performs preliminary actions by extracting and storing user preference information, content metadata, and classification rules in advance. When a content request arrives, the system quickly retrieves pre-processed user profiles and preference rules rather than analyzing everything from scratch. This preliminary preparation significantly reduces processing latency while maintaining high content quality through thorough curation.
Solution Approach 2:
The Experience Broker maintains continuous operation by running background processes that continuously update user profiles, monitor content sources, and refine classification models. This continuous action ensures that when users make requests, the system already has current information ready, eliminating delays associated with initial system setup or cold-start processing.
3Stability of the object's composition
If user preferences and context are tracked across multiple devices, then personalization consistency is improved, but data management complexity increases
Solution Approach 1:
The Experience Broker implements a universal user profile storage mechanism that serves multiple functions: storing preference data, tracking usage patterns, managing device contexts, and maintaining consistency across different platforms. This single multi-functional system replaces the need for separate data management systems for each device type, simplifying data management while ensuring consistent personalization whether users access content via mobile devices, tablets, or desktops.
Data Source
AI summary
A dynamic experience curation platform utilizing AI and ML techniques, including neural networks and generative models, to enhance user interactions with content on the Internet. The platform employs an Experience Broker (EB) service to disintermediate user devices from the internet (or other content/information sources), improving security and user experience. It processes content requests, extracts relevant information, filters out unwanted content like ads, transforms, combines, and/or mutates existing content, and generates curated content consistent with user preferences and other constraints. The platform's generative AI process renders content into a user interface consistent with user preferences. It allows for personalized content delivery across devices, including virtual and augmented reality environments. The platform supports a spectrum of personalization, allowing users to fine-tune their content consumption experience. Additionally, it manages user sessions across devices and integrates various databases for storing user profiles, preferences, and other relevant information.


