Collaborative Image Selection System with Community Rating
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Solution Overview
Problem
Users face challenges in finding and selecting interesting digital images from large collections, and in sharing and assembling image compilations due to the overwhelming number of images available, which increases the time and effort required for review and curation.
Innovation Solution
A system and method for sharing and collaborating on image selection, where users can access, rate, recommend, and compile images within communities, using metrics to rank images based on user interest, allowing for automatic selection and presentation of images for electronic or physical compilations like photo books.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If images are made freely accessible to all users, then image sharing and collaboration are improved, but the time and effort required to review and find interesting images increases
Solution Approach 1:
The patent introduces a rating system and recommendation engine as intermediaries between the large image collection and users. Community members rate images, and these ratings serve as a mediator to guide users to interesting images without requiring them to review all available images manually.
Solution Approach 2:
The system implements feedback loops where user ratings and recommendations are processed to generate personalized image recommendations. This feedback mechanism allows the system to learn from community interactions and improve image selection over time, reducing the time users spend searching.
2Adaptability or versatility
If a large number of images are made available for selection, then the quality and variety of compilations can be improved, but the complexity of selecting and arranging images increases
Solution Approach 1:
The patent enables images to serve themselves through automated rating and recommendation systems. Instead of requiring manual curation of all images, the system allows images to be evaluated and recommended based on community ratings and algorithmic processing, reducing the complexity of the selection process.
Solution Approach 2:
The manual mechanical process of reviewing and selecting images is replaced with an automated electronic system that processes ratings, calculates recommendations, and generates compilation suggestions algorithmically, significantly reducing the complexity burden on users.
3Measurement precision
If manual review of all images is performed to ensure quality, then selection accuracy is improved, but productivity decreases
Solution Approach 1:
Instead of requiring complete manual review of all images, the system applies partial action by using automated rating systems and recommendation algorithms to pre-filter and prioritize images. This allows the system to achieve sufficient selection accuracy without the exhaustive manual review that would reduce productivity.
Data Source
AI summary
A system and method for sharing images and collaborating in the selection of images likely to be interest to a user. Images (e.g., photos) are shared within a community of users, by allowing user to access any unrestricted community image, recommend an image to another user, assemble compilations of any images the user can access, etc. Various metrics regarding user activity are tracked, such as how often an image was viewed, downloaded, recommended, included in a compilation, printed, edited, etc. The metric values may be normalized, and then weighted and combined to produce, for each image, a ranking or rating personalized to an individual user. Ratings of images for a user may be used to order them for electronic presentation, assemble a set of images for an electronic compilation (e.g., an online album) or physical compilation (e.g., a photo book, a yearbook) or for some other purpose.