Adaptive Video Navigation via Fragment Clustering
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Solution Overview
Problem
Current online video streaming platforms fail to provide personalized, dynamic, and adaptive video experiences to users as they do not account for dynamically changing user interests or perform meta-tagging based on search queries, resulting in inefficient video navigation and assembly.
Innovation Solution
A method that involves receiving user preference data, fragmenting and clustering videos into logical segments, mining semantic context information, and inserting interactive navigation options to enable real-time navigation to discrete segments of assembled videos, tailored to individual user preferences and viewing behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If videos are assembled based on complete set of tags without dynamic user interest consideration, then video assembly is simplified, but user personalization and content relevance deteriorate
Solution Approach 1:
The system performs preliminary actions by pre-tagging video fragments with multiple metadata tags before assembly, and pre-computing user profiles based on historical data. This allows the system to quickly assemble personalized videos by matching pre-prepared tags with user preferences without complex real-time processing
Solution Approach 2:
The video assembly process transitions from static tag-based assembly to dynamic user-interest-driven assembly. The system dynamically adjusts video fragment selection based on real-time user preferences, viewing behavior, and contextual factors, making the assembly process adaptable to individual user needs while maintaining efficiency through automated algorithms
2Device complexity
If platforms don't perform dynamic meta-tagging based on user search queries, then processing complexity is reduced, but navigation precision and content retrieval efficiency deteriorate
Solution Approach 1:
The system segments videos into smaller fragments and applies multiple tags to each fragment based on user search queries and viewing behavior. This segmentation allows precise navigation to specific video segments that match user interests without requiring complex processing of entire videos, improving both navigation precision and retrieval efficiency
3Ease of operation
If interactive navigation options are inserted in assembled video, then user engagement and navigation capability are improved, but device complexity and processing requirements increase
Solution Approach 1:
The system introduces an intermediary layer of navigation options that mediate between the user and the video content. These navigation options include clickable thumbnails, chapter markers, and recommendation overlays that are inserted into the assembled video, enabling easy user navigation without requiring complex client-side processing
4Adaptability or versatility
If videos are assembled in real-time based on user preferences, then content relevance is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing videos into tagged fragments and pre-computing user profiles based on historical data. This allows real-time personalized video assembly by simply matching pre-prepared tags with user preferences, significantly reducing processing time while maintaining high content relevance
Data Source
AI summary
The present disclosure provides a system and method for enabling navigation to one or more discrete segments of a real time dynamic and adaptive non-linear, non-sequentially assembled video. The method includes reception of a set of preference data associated with a user from a pre-defined selection criteria and a set of user authentication data. Accordingly, the method includes fetching of one or more tagged videos related to the set of preference data. The method includes fragmentation of the one or more tagged videos into the one or more tagged fragments. Further, the method includes clustering of one or more mapped fragments in a pre-defined order of preference. Furthermore, the method includes insertion of one or more interactive navigation options in one or more regions. Also, the method includes serving of the assembled video and inserted one or more interactive navigation options to the user.