Dynamic Media Trailer Generation via Clip Tagging
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Solution Overview
Problem
Pre-generated movie trailers often include content undesirable for specific viewers, such as spoilers or scenes not aligning with individual interests, making it challenging to customize trailers based on user preferences.
Innovation Solution
A computing environment dynamically generates customized media trailers by parsing media files to automatically tag clips based on scene types and user preferences, combining clips from media files associated with selected tags, and allowing user input for personalized trailers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If pre-generated movie trailers are used, then production efficiency is improved, but relevance to individual user preferences deteriorates
Solution Approach 1:
The system transitions from static pre-generated trailers to dynamic on-demand trailers. The trailer generation process is activated dynamically when a user selects a movie, automatically extracting and assembling relevant clips based on real-time user preferences and viewing history, thereby adapting content to individual users while maintaining production efficiency through automation.
Solution Approach 2:
The system performs self-service by automatically analyzing user preferences, viewing history, and movie content to generate personalized trailers without manual intervention. The automated clip extraction and assembly process eliminates the need for human editors while delivering customized content, resolving the contradiction between efficiency and personalization.
2Ease of manufacture
If pre-generated movie trailers are used, then manufacturing cost is reduced, but quality of user experience deteriorates
Solution Approach 1:
The system employs self-service automation where algorithms automatically analyze user preferences, extract relevant movie clips, and assemble personalized trailers. This eliminates manual production costs while maintaining high quality through intelligent content selection based on user viewing history and preferences, thereby improving user experience without increasing manufacturing cost.
Solution Approach 2:
The system changes the parameters of trailer generation by using automated algorithms that analyze multiple dimensions of user data (viewing history, preferences, demographics) to select and assemble clips. This parameter-driven approach ensures consistent high-quality user experiences while reducing manufacturing costs through automation and scalability.
3Productivity
If automated clip extraction is implemented, then productivity is improved, but complexity of the system deteriorates
Solution Approach 1:
The system uses a universal automated framework that handles multiple functions: user preference analysis, movie content analysis, clip extraction, and trailer assembly. This multi-functional approach consolidates complexity into a single integrated system, improving productivity through automation while managing complexity through unified processing rather than separate specialized components.
Data Source
AI summary
Disclosed are various embodiments for dynamically generating media trailers for communication over a network. A request for a dynamically generated media trailer is received by a computing environment over the network. Clips are extracted from media files or previews associated with the media files according to media titles in lists and/or tags identified by a user. A customized media trailer is generated by coalescing the clips extracted from the media file or a preview associated with the media file according to a determined order. The media trailer is communicated to one or more client device over the network.