Personalized Product Video Assembly for Query-Relevant Viewing
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Solution Overview
Problem
Conventional product videos are static and fail to cater to individual user interests, leading to decreased user engagement and unnecessary consumption of computing resources as users search for relevant information.
Innovation Solution
Dynamic video generation tailored to user interests and preferences using generative models, incorporating user data such as search queries and interaction history to create optimized videos in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If static product videos are used, then video content is simple to produce, but user engagement decreases and computing resources are wasted as users search for relevant information
Solution Approach 1:
The patent transforms static product videos into dynamic, personalized video experiences by automatically generating different video content based on user profiles, search queries, and interaction data. The system dynamically selects and sequences product assets to create customized videos for each user, making the video content adaptive rather than fixed.
Solution Approach 2:
The system changes multiple parameters of video content including duration, content selection, asset sequencing, and information density based on user characteristics. Videos are generated with optimized durations (e.g., 15-60 seconds) and tailored content parameters that match user preferences and intent, rather than using a single static video for all users.
2Loss of information
If comprehensive product information is included in videos, then information completeness improves, but video length increases causing user abandonment
Solution Approach 1:
The system extracts and selects only the most relevant product information and assets for each user based on their profile, search query, and interaction data. Instead of including all product information in every video, the system takes out and presents only the subset of information that is most valuable to the specific user, reducing video length while maintaining information quality.
Solution Approach 2:
The patent applies partial action by providing just enough information to satisfy user intent without overwhelming them. Videos are optimized to contain the minimum necessary information required to address user needs, rather than providing excessive comprehensive coverage that would increase duration and cause abandonment.
3Productivity
If personalized video content is generated dynamically, then user engagement and information relevance improve, but computing resource consumption increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and organizing product assets, user profiles, and interaction data before video generation. Product catalogs are pre-tagged and structured, user preferences are pre-analyzed, and asset libraries are pre-organized, so that dynamic video generation requires only lightweight real-time assembly rather than intensive processing.
Solution Approach 2:
The patent uses copying by creating video content from pre-existing product assets, templates, and structured data rather than generating entirely new content from scratch. The system copies and recombines standardized video elements, asset clips, and information patterns based on user needs, reducing the computational burden of video generation.
4Adaptability or versatility
If videos are tailored to individual user interests, then user satisfaction increases, but system complexity increases
Solution Approach 1:
The patent segments the video generation system into distinct modular components: user profile analysis modules, asset selection modules, video assembly modules, and template processing modules. Each component handles a specific aspect of personalization, making the overall complex system manageable through functional decomposition and independent optimization of each segment.
Solution Approach 2:
The system achieves versatility through universal templates and asset libraries that can serve multiple user types and product categories. A single set of standardized video templates and asset collections can be universally applied across different users and products by simply changing the input parameters, reducing the need for separate customization systems for each scenario.
Data Source
AI summary
Methods, computer systems, and computer-storage media are provided for efficiently generating an optimized video for a particular user to view the video, among other things. In embodiments, a set of product assets associated with a product is identified based on relevance to intent of a query input by a user. The video summary that provides a manner in which to generate an optimized video associated with the product is generated based on the set of product assets relevant to the intent of the query input by the user and associated with the product. The optimized video associated with the product is generated based on the video summary and an optimal video duration identified for the user. Thereafter, the optimized video that includes content relevant to the intent of the query input by the user and that corresponds with the optimal video duration identified for the user is provided for display.