Electronic Book Supplemental Content Generation via Noun Context Matching
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Solution Overview
Problem
Electronic books lack dynamic and automatic generation of supplemental content such as audio, video, and images that relate to the text, providing minimal contextual information to users during reading.
Innovation Solution
The system identifies nouns and related words in the text, searches content structures for matching objects, and generates new content structures to create supplemental content segments, which can include virtual modeling data for 3D animations, and determines output duration based on reading speed, allowing for real-time presentation within the margins of the page.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If electronic books include only static illustrations and hyperlinks, then the device complexity remains low, but the contextual information provided to users is minimal and not dynamically generated
Solution Approach 1:
The patent applies preliminary action by pre-defining content structures with objects, attributes, and relationships before the reading process. These pre-prepared structures enable dynamic content generation without requiring complex real-time processing, thus reducing device complexity while still providing rich contextual information.
Solution Approach 2:
The system applies self-service by automatically generating supplemental content based on the text being read, without requiring manual curation or external intervention. The content generation engine autonomously queries the content structures and renders appropriate multimedia content, reducing the need for human effort while enhancing information delivery.
2Loss of information
If electronic books provide comprehensive supplemental content, then the information quality improves, but the processing time and complexity increase
Solution Approach 1:
Content structures are prepared in advance with all possible objects, attributes, and relationships defined. This preliminary organization allows the system to quickly retrieve and assemble relevant content during reading without performing complex real-time analysis, thus reducing processing time while maintaining comprehensive information quality.
Solution Approach 2:
The patent segments content into discrete objects with specific attributes and relationships. This segmentation allows the system to efficiently query and assemble only the relevant portions needed for the current context, rather than processing entire content sets, thereby reducing processing time while delivering comprehensive information.
3Adaptability or versatility
If electronic books include dynamic content generation, then the adaptability to user context improves, but the device complexity increases
Solution Approach 1:
The content generation system operates autonomously by automatically analyzing the text context and selecting appropriate supplemental content from pre-defined structures. This self-service approach provides high contextual adaptability without requiring complex real-time processing or human intervention, thus managing device complexity effectively.
Solution Approach 2:
The patent creates universal content structures that can serve multiple purposes and contexts. These multi-functional structures allow the same framework to generate various types of supplemental content (images, audio, video, annotations) based on different reading contexts, enhancing adaptability without proportionally increasing system complexity.
4Loss of information
If electronic books present supplemental content outside page margins, then the content visibility improves, but the layout complexity and space utilization worsen
Solution Approach 1:
The patent presents supplemental content in alternative dimensions or spaces rather than competing for the same two-dimensional page space. Content can be displayed in side panels, pop-up windows, or separate viewing areas, improving visibility without complicating the main page layout and maintaining efficient space utilization.
Data Source
AI summary
Systems and methods are disclosed herein for generating supplemental content for media content. One disclosed technique herein generates for display a page of an electronic book. A noun, and a word contextually related to the noun, are identified from the displayed page of the electronic book. Content structures are searched for a content structure that includes a matching object having an object name matching the noun. The content structure includes objects, where each object has attribute table entries. Upon finding an identified attribute table entry of the matching object that matches the related word, a new content structure is generated. The new content structure includes the matching object and the identified attribute table entry. A content segment is generated for output (e.g., for display on the electronic book) based on the new content structure.