Custom Search Attributes via Image Analysis
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Solution Overview
Problem
Existing search technologies are inefficient in capturing user intent due to limited filter options and repetitive search queries, leading to increased computing resource consumption and user frustration.
Innovation Solution
A search system that generates custom attributes based on user input, allowing users to specify attributes for items, which are then used as search facets to filter and order search results, reducing the need for repetitive queries by analyzing images of items to determine attributes like dimension, color, or material.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional search engines use limited filter options, then the search interface remains simple, but user intent is not accurately captured and repetitive search queries are required
Solution Approach 1:
The system automatically generates custom attributes by analyzing item images without requiring users to manually define search criteria. The image analysis system extracts attributes such as color, pattern, and style automatically, allowing the system to serve itself in capturing user intent rather than requiring complex manual filtering by the user.
Solution Approach 2:
The patent replaces manual mechanical filtering processes with automated image analysis technology. Instead of users manually selecting from predefined filters, the system uses computer vision and machine learning models to automatically extract and generate custom attributes from item images, substituting the mechanical filtering process with an automated intelligent system.
2Measurement precision
If users perform repetitive search queries to refine results, then search accuracy improves, but computing resource consumption increases
Solution Approach 1:
The system performs preliminary image analysis and attribute extraction when items are first loaded or viewed, rather than waiting for users to perform multiple search queries. By pre-processing and extracting custom attributes from item images in advance, the system prepares search results in advance, reducing the need for repetitive queries and associated computing resource consumption.
Solution Approach 2:
The system uses feedback from user interactions with item images to automatically refine and generate custom attributes. When users view or interact with items, the system analyzes their behavior and automatically adjusts the attribute extraction and search results, creating a feedback loop that improves search relevance without requiring repetitive manual queries.
3Measurement precision
If custom attributes are generated through image analysis, then search facet accuracy improves, but processing time and computational load increase
Solution Approach 1:
The system extracts only the necessary custom attributes from item images based on the specific search context and user interests, rather than analyzing all possible attributes exhaustively. By selectively extracting only the relevant attributes needed for the current search query, the system reduces processing time and computational load while maintaining high accuracy for the required search facets.
Data Source
AI summary
A search system generates custom attributes for use as search facets. User input associated with an image of a target item available on a listing platform is received. The image is analyzed to determine an attribute of the target item as a custom attribute. A value for the custom attribute is determined for each of a number of other items available on the listing platform that are of the same item type as the target item. Search results are provided based at least in part on the values of the custom attribute for the other items.