Visual Feature Matching for Anonymous User Recommendations
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Solution Overview
Problem
Conventional approaches to recommending items in electronic environments often fail to provide optimal user experiences, especially for new users or those without logged-in accounts, as they rely on limited data, neglecting appearance-related criteria like color and pattern, leading to irrelevant recommendations and increased resource consumption.
Innovation Solution
The system analyzes images to identify visually related items by training classifiers using convolutional neural networks (CNNs) to generate descriptors for color and pattern recognition, allowing for the recommendation of accessories that match or complement the color and category of apparel items, even without user-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional recommendation approaches are used that rely on user-specific data, then recommendations can be personalized for logged-in users, but new users or anonymous users receive irrelevant recommendations based solely on category or similar items
Solution Approach 1:
The patent introduces color and visual feature descriptors as intermediary representations that bridge the gap between user preferences and item characteristics. By extracting color descriptors from images and comparing them against user profile colors, the system enables recommendation for anonymous users through visual feature matching rather than requiring user-specific data
Solution Approach 2:
The patent replaces the traditional mechanics-based recommendation system (which relies on explicit user data, purchase history, and category matching) with a visual-based system using color descriptors and image analysis. This substitution allows the system to function effectively for anonymous users by using visual features as the primary matching criterion
2Productivity
If conventional recommendation systems display items based on limited data, then system resources are consumed to display content, but the recommendations may not be of interest to the user
Solution Approach 1:
The patent performs preliminary action by pre-computing and storing color descriptors for all items in the database, and pre-establishing user color profiles. This preparation work is done in advance so that when a recommendation request comes in (even for anonymous users), the system can quickly perform color-based matching without consuming excessive resources during the actual recommendation generation
3Measurement precision
If visual feature analysis using CNNs is implemented, then color and pattern recognition accuracy is improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent segments the complex visual analysis task into distinct components: color descriptor extraction, pattern recognition, and similarity comparison. By using CNNs specifically for color descriptor extraction and then using these descriptors for matching, the system breaks down the complex problem into manageable stages, reducing overall system complexity while maintaining high accuracy
Data Source
AI summary
Approaches attempt to determine information that can help to produce more useful recommendations to be displayed in a situation where no, or little, information is available that indicates a relationship between content provided through an electronic marketplace or other content provider. For example, data available that relates to an item in a product catalog, for example color data, can be analyzed and aggregated in order to attempt to locate other items that are related and relevant to the item, at least as it relates to color and categorization of the content. Such approaches can include, for example, analyzing images, articles, and other sources of electronic content to attempt to locate items that might be relevant to the item of interest. In a clothing example, this can include accessory items that might be worn with an apparel item of interest, match the apparel item of interest, be frequently utilized or exhibited with the apparel item of interest, include a matching and/or complementary color to the apparel item of interest, etc.