Tagged-Element Video Matching for Faster Content Discovery
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Solution Overview
Problem
The exponential growth of streaming content makes it difficult for users to find content of interest, as conventional search tools are inadequate for navigating the vast array of available options.
Innovation Solution
A system and method that identifies and recommends media content based on the relatedness of elements tagged in videos, using components like identification, matching, and recommendation components to suggest videos with similar tagged elements, considering user interactions and relationships.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional search tools are used to navigate streaming content, then users can perform basic content searches, but the tools are inadequate for finding relevant content among millions of options
Solution Approach 1:
The patent segments videos into discrete tagged elements (objects, people, concepts) that can be independently identified and matched. This segmentation allows the system to break down the vast content library into manageable, comparable units, enabling precise matching without requiring users to search through all content manually.
Solution Approach 2:
The patent introduces tagged elements as intermediaries between users and video content. Instead of directly searching through millions of videos, users interact with tagged elements that mediate the search process, making content discovery more efficient and accurate by serving as a intermediary layer between the user query and the vast content repository.
2Ease of operation
If manual searching through streaming content is performed, then users can find specific content, but the process becomes increasingly difficult with exponential content growth
Solution Approach 1:
The patent performs preliminary action by pre-tagging videos with relevant elements before users search. This advance preparation of metadata (tagged elements) allows for rapid content discovery without requiring users to manually examine content, significantly reducing search time while maintaining ease of operation through simple tag-based queries.
Solution Approach 2:
The patent replaces manual mechanical searching with an automated electronic matching system. Instead of users manually browsing through content, the system automatically matches tagged elements from user queries with tagged elements in the video database, substituting manual effort with automated computational processes that are both faster and easier to use.
3Productivity
If automated content identification tools are developed, then content recommendation capability improves, but system complexity increases
Solution Approach 1:
The patent implements a universal tagging system that serves multiple functions: identifying objects, people, and concepts; enabling content recommendation; and supporting various types of content queries. This multi-functional approach increases productivity without proportionally increasing complexity, as the same tagged element infrastructure supports diverse recommendation needs.
Solution Approach 2:
The patent manages complexity by focusing on changing key parameters (tagged elements) rather than redesigning the entire system. By modifying and matching tagged element parameters across videos, the system achieves efficient content recommendation through parameter-based filtering and matching, avoiding the need for complex artificial intelligence or machine learning systems.
Data Source
AI summary
Systems and methods for identifying related videos based on elements tagged in the videos are presented. In an aspect, a system includes an identification component configured to identify tagged elements in a video, a matching component configured to identify other videos that include one or more of the tagged elements, and a recommendation component configured to recommend the other videos for viewing based on a current or past request to play the video.