Social Network Image Comparison via Metadata and Comment Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing image comparison methods on social networks fail to effectively identify and present similar images, including those with related metadata and user comments, limiting users' ability to aggregate and rank relevant content.
Innovation Solution
A computer-implemented method that compares data associated with a first image within a social network to a plurality of images, identifying a subset of similar images based on metadata and user comments, and presenting them to a user's computing device, while analyzing social affinity and user credentials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing image comparison methods are used on social networks, then basic image searching is possible, but users cannot effectively identify and aggregate related images with metadata and comments, limiting content aggregation capability
Solution Approach 1:
The patent segments the image comparison task into multiple comparison dimensions: visual similarity comparison, metadata comparison, and user comment comparison. Each dimension is handled separately through specialized comparison modules, allowing comprehensive content aggregation while maintaining system manageability and improving identification accuracy.
Solution Approach 2:
The patent merges multiple comparison results (visual, metadata, comments) into a unified similarity score. By combining these different data types and weighing them appropriately, the system achieves effective content aggregation that considers multiple aspects of image relatedness, resolving the information loss problem.
2Measurement precision
If comprehensive data comparison is performed including metadata and comments, then identification accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The patent applies partial action by performing comprehensive comparison only when necessary. The system first performs quick visual similarity comparison, then selectively performs metadata and comment comparisons only when visual similarity indicates potential matches. This staged approach maintains high accuracy for identified similar images while significantly reducing overall processing time.
Solution Approach 2:
The patent performs preliminary visual similarity comparison before diving into more time-consuming metadata and comment analysis. This preliminary filtering action identifies potential candidates for deeper analysis, preventing unnecessary comprehensive comparisons and reducing total processing time while maintaining identification accuracy.
3Reliability
If multiple comparison criteria (visual, metadata, comments) are applied, then content relevance improves, but system complexity increases
Solution Approach 1:
The patent segments the comparison system into distinct independent modules: visual comparison module, metadata comparison module, and comment comparison module. Each module operates independently with its own algorithms and parameters, making the complex multi-criteria system manageable and easier to maintain while improving content relevance through comprehensive comparison.
Data Source
AI summary
A computer-implemented method and computing system for comparing, on a computing device, data concerning a first image within a social network to data concerning a plurality of images within the social network. A subset of similar images is identified, chosen from the plurality of images, based, at least in part, upon the comparison. At least a portion of the subset is presented to a computing device associated with a user.