Media Summarization Engine Selecting Tailored Content
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Solution Overview
Problem
Existing summaries for bodies of media are pre-composed and fail to cater to individual consumer preferences, resulting in less-than-desirable experiences.
Innovation Solution
A method and system that determine and select summaries based on various consumer-specific factors, such as age, device characteristics, and preferences, using a summarization engine with modules for interface, factor determination, analysis, and output to provide tailored summaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If pre-composed summaries are used for bodies of media, then the implementation is simple and quick, but the summaries fail to cater to individual consumer preferences resulting in less-than-desirable experiences
Solution Approach 1:
The system pre-determines multiple candidate summaries for different consumer preferences and stores them in advance. When a consumer requests a summary, the system quickly retrieves and selects from these pre-prepared options based on the consumer's profile, avoiding real-time generation complexity while maintaining personalization.
Solution Approach 2:
The system varies summary parameters such as level of detail, tone, and focus areas based on consumer preferences. By changing these parameters across multiple pre-composed summaries, the system offers tailored experiences without requiring complete re-generation of content for each consumer.
2Adaptability or versatility
If multiple candidate summaries are prepared and stored for selection, then individualized summaries can be provided, but more memory resources are required to store the plurality of summaries
Solution Approach 1:
The summary content is segmented into modular components (e.g., plot points, character introductions, key events) that can be independently stored and recombined. This allows the system to store multiple summaries using the same base content segments, reducing overall memory requirements while maintaining variety in the final summaries.
Solution Approach 2:
Instead of storing complete duplicate summaries for each consumer preference, the system stores template summaries with variable parameters. These templates can be copied and customized with different parameter values to generate personalized summaries, significantly reducing the total storage requirement compared to storing fully distinct summaries for each preference type.
Data Source
AI summary
Bodies of media may be summarized in various ways depending on numerous factors, thus resulting in summaries that are tailored to particular desires of consumers. An instruction may be received to provide a summary of at least a portion of the body of media. Software stored in memory may then be executed by a processor to determine one or more factors for providing the summary. The summary may be selected, based on the one or more factors, from a plurality of available summaries stored in memory. The plurality of available summaries corresponds to the at least a portion of the body of media. Finally, the selected summary may be provided to a consumer via an output device.