Contextual Feedback Suggestions Through Modular Content Analysis
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Solution Overview
Problem
Existing solutions do not provide contextually relevant information options for viewers to share feedback while viewing content items.
Innovation Solution
A system and method that utilizes contextual modules to analyze content items, determining contextual information and classifications, and provides contextually relevant suggestions such as emojis or messages that can be overlaid during content viewing, with user interaction and metadata storage for personalized feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contextual modules analyze content items to provide contextually relevant suggestions, then the relevance and quality of feedback options improve, but the system complexity and processing time increase
Solution Approach 1:
The system divides content analysis into separate contextual modules (audio analysis module, visual analysis module, closed captions module, commentary module), each handling specific aspects of content analysis independently. This segmentation allows the system to achieve comprehensive contextual understanding while maintaining manageable complexity through modular architecture.
Solution Approach 2:
The contextual modules serve multiple functions: they analyze different content types (audio, visual, textual), generate contextual information, determine classifications, and provide suggestions for feedback. This multi-functionality reduces the need for separate specialized systems for each task.
2Measurement precision
If multiple contextual modules analyze content to determine contextual information and classifications, then the accuracy of feedback suggestions improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs content analysis and generates contextual information in advance, before the user needs to provide feedback. The contextual modules pre-process content items to determine classifications and generate suggestions, so that when users interact with the content, relevant feedback options are already prepared and available immediately.
Solution Approach 2:
The system combines results from multiple contextual modules (audio, visual, captions, commentary) to generate comprehensive contextual information and unified feedback suggestions. This merging approach achieves high accuracy by integrating multiple analysis perspectives while presenting a cohesive set of suggestions to users.
Data Source
AI summary
Provided herein are methods and systems for enabling users to provide contextually relevant information, such as feedback, relating to a content item. A computing device may receive a request for a content item. The computing device may receive the request and analyze a first portion of the content item to determine contextual information associated with the first portion. The computing device may determine one or more suggestions for contextually relevant items, such as symbols, to enable use of the symbols to provide information. The computing device may send the one or more suggestions with the first portion of the content item.