Highlighting Frequent Words in Lecture Content
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Solution Overview
Problem
Existing information processing systems fail to effectively highlight frequently discussed topics during video lectures, leading to participants missing important information due to lack of clear representation of attention words within the content.
Innovation Solution
An information processing apparatus that acquires character information from multiple viewers and changes the representation form of frequently occurring words within the content, using a server apparatus to extract and highlight participant attention words in image and audio materials, ensuring all participants focus on key topics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If character information from multiple viewers is collected and analyzed to identify frequent words, then participant engagement and focus on key topics is improved, but system complexity and processing time increases
Solution Approach 1:
The system segments the lecture content into discrete character information units from multiple viewers, processes them individually to identify frequent words, and then applies representation changes. This segmentation allows the complex task of analyzing multiple viewers' inputs to be broken down into manageable steps, reducing overall system complexity while maintaining engagement benefits
Solution Approach 2:
The server apparatus acts as an intermediary that collects character information from multiple viewers, processes it to identify frequent words, and then applies representation changes to the lecture content. This intermediary approach manages the complexity of multi-viewer data processing centrally while keeping individual viewer interfaces simple
2Reliability
If representation form of frequent words is changed to highlight key topics, then information retention and understanding is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary analysis of character information from multiple viewers to identify frequent words before the actual lecture content is fully processed. By pre-identifying key topics and their representation forms, the system reduces processing time during live delivery while ensuring information retention is maintained
Solution Approach 2:
The system changes parameters of word representation (such as visual highlighting, formatting, or emphasis) to distinguish frequent words from regular content. These parameter changes are applied selectively based on frequency analysis results, improving information retention without requiring complete reprocessing of all content
3Adaptability or versatility
If all participant inputs are processed uniformly to identify attention words, then fairness and comprehensive coverage is improved, but processing efficiency decreases
Solution Approach 1:
The system processes character information from multiple viewers uniformly to ensure comprehensive coverage of all participant inputs, but applies representation changes only to the identified frequent words rather than all content. This partial action approach maintains fairness in analysis while improving processing efficiency by focusing changes on key topics only
Data Source
AI summary
An information processing apparatus includes an acquisition unit and a changing unit. The acquisition unit acquires character information input by a viewer to content. The changing unit changes a representation form of a frequent word which is character information with a high appearance frequency among character information input by multiple viewers to the content.