Hierarchical Mind Map Generation for Video Content Indexing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current technologies fail to provide a hierarchical representation of video file contents as an interactive Mind map, lacking the ability to establish relationships between video files and supporting files like PDFs, Word documents, or image files, and do not offer editable transcription or timestamped content searches with confidence scores.
Innovation Solution
A system that programmatically generates a hierarchical Mind map for video files, including a Mind map Generation Unit that creates a hierarchical representation of topics with timestamps, and an Index table generation Unit that establishes relationships between video and supporting files, using units like Input, Transcription, Hierarchy Extraction, and Object Detection to generate clickable and editable content links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual indexing and linear representation of video content is used, then implementation is simple, but knowledge assimilation efficiency is reduced and navigation is cumbersome
Solution Approach 1:
The patent segments video content into hierarchical topics and subtopics, creating a structured mind map representation. This segmentation transforms linear video content into organized knowledge units that can be efficiently navigated and assimilated, directly improving knowledge assimilation efficiency without requiring complete manual reorganization of the entire video.
Solution Approach 2:
The patent transitions from linear one-dimensional video playback to a two-dimensional hierarchical mind map structure with multiple levels of topics and subtopics. This dimensional change enables users to navigate content vertically through hierarchy levels and horizontally through topic relationships, significantly improving navigation efficiency and knowledge assimilation.
2Ease of operation
If hierarchical Mind map representation with interactive hyperlinks is implemented, then navigation efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary automatic generation of the hierarchical mind map structure before user interaction. Topics, subtopics, and hyperlinks are pre-extracted and organized from video content and supporting files, so that users immediately encounter a ready-to-navigate structure without requiring real-time processing during interaction.
Solution Approach 2:
The system automatically extracts topics, generates hierarchical structures, and creates hyperlinks without requiring manual intervention. The automatic indexing and mind map generation processes enable the system to serve itself in creating the navigational structure, reducing the need for complex manual configuration while maintaining high navigation efficiency.
3Loss of information
If relationship mapping between video files and supporting files is established, then content connectivity is improved, but processing complexity increases
Solution Approach 1:
The patent implements a universal topic extraction and relationship mapping mechanism that works across multiple file types including video files, PDF documents, Word documents, and image files. The same processing framework identifies topics and establishes relationships regardless of the source file type, improving content connectivity without requiring separate complex processing pipelines for each file format.
Solution Approach 2:
The patent uses topics as intermediary elements that connect video content with supporting files. Instead of directly mapping complex relationships between entire files, the system uses extracted topics as mediators to establish connections, simplifying the relationship mapping process while maintaining comprehensive content connectivity across different file types.
4Extent of automation
If automatic transcription and topic extraction is implemented, then manual intervention is reduced, but accuracy of topic identification may decrease
Solution Approach 1:
The system implements feedback mechanisms where extracted topics are validated against multiple sources including video content, supporting files, and metadata. The hierarchical structure allows for verification at multiple levels, and the system can refine topic identification based on consistency checks across different file types and content sources, maintaining high accuracy while fully automated.
Solution Approach 2:
The patent combines multiple automated extraction processes including transcription, topic identification, and relationship mapping into an integrated system. By merging these processes and cross-validating results across video content, supporting files, and extracted topics, the system achieves high topic identification accuracy through collective verification rather than relying on a single automated process.
Data Source
AI summary
This invention relates to a System and Method for generating Primary Output and a Secondary Output programmatically. The method may include extracting a transcript, topics, a hierarchy of the topics of a video file, and generating a Primary Output and a Secondary Output programmatically. The Primary Output comprises a visual, editable, clickable, and hierarchical Mind map for the video file. It further comprises a Unique address of parent and child nodes in the hierarchical Mind map and Time-stamps of corresponding topics. The Secondary Output comprises an index table of a Proximity score, details on whether a Secondary Input is found or not in the video file, a Unique address P[u,m,n], From and To Time-stamps, and a corresponding topic in the video file.