Media Knowledge Gap Analysis System
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Solution Overview
Problem
Current media services lack the ability to effectively identify and address knowledge gaps in users regarding the media they consume, which can lead to a suboptimal user experience due to missing contextual information.
Innovation Solution
A method and system that utilize a hardware processor to receive user requests for media, retrieve metadata sets, compare user media usage profiles with the metadata, and provide information on identified knowledge gaps, generating gap analysis reports and summaries to fill these gaps, thereby enhancing user knowledge before, during, or after media consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If media services provide only basic media delivery without additional information processing, then service simplicity is maintained, but user knowledge gaps remain unaddressed leading to suboptimal user experience
Solution Approach 1:
The system performs preliminary actions by building user knowledge profiles and analyzing metadata before media delivery. The knowledge gap identification process occurs in advance, allowing the system to prepare targeted information and updates proactively rather than reactively, improving user experience without adding complexity during media consumption
Solution Approach 2:
The system enables self-service by automatically analyzing user media consumption patterns, building knowledge profiles, identifying knowledge gaps, and providing targeted information updates without requiring manual user input. The system serves itself by continuously monitoring and adapting to user needs, maintaining service simplicity while improving reliability
2Loss of information
If the system provides comprehensive metadata and detailed gap analysis information, then user knowledge gaps are effectively filled, but information processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential and relevant information needed to fill specific knowledge gaps, rather than providing comprehensive metadata. By selectively extracting targeted information based on identified gaps, the system reduces processing time while maintaining effective knowledge gap coverage
Solution Approach 2:
The system applies local quality by providing different levels and types of information tailored to specific knowledge gaps rather than uniform comprehensive information. Each user receives customized information relevant to their specific gaps, optimizing processing efficiency while maintaining effectiveness
3Measurement precision
If the system continuously monitors and updates user media usage profiles, then accuracy of knowledge gap identification is improved, but computational overhead and data processing requirements increase
Solution Approach 1:
The system implements periodic action by updating user knowledge profiles at intervals based on media consumption patterns rather than continuously. This periodic update approach maintains measurement precision for knowledge gap identification while significantly reducing computational overhead and energy consumption compared to continuous monitoring
Data Source
AI summary
A method comprising using at least one hardware processor for receiving a request of a user for media, retrieving a first metadata set relating to said media, comparing between: (a) a media usage profile of the user, which profile reflects knowledge of the user, and (b) the first metadata set relating to said media, to identify gaps in the knowledge of the user with respect to said media, and providing to the user information relating to said identified gaps.