Image Entity Recognition via Similar Image Metadata Analysis
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Solution Overview
Problem
Current search engines face challenges in accurately determining the subject matter of an image query, as users often receive a set of related images but must manually identify the subject, which can be time-consuming and inefficient.
Innovation Solution
A system and method where a search engine identifies similar images to a query image, extracts metadata, and uses machine learning to determine a most-likely entity name, matching it to a known entity to generate relevant search results pages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If a search engine provides only similar images in response to an image query, then the user can view related images, but the user must manually identify the subject matter which is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary analysis of image metadata and determines the subject matter before presenting results to the user. Search result pages are pre-generated with identified entity information, eliminating the need for users to manually investigate each image to determine its subject matter.
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes image metadata and generates search result pages with identified subject matter. This intermediary system acts as a mediator between the image database and the user, automatically determining entity names and presenting organized information without requiring direct user investigation of individual images.
2Measurement precision
If the search engine analyzes metadata from multiple similar images to determine entity names, then accurate subject matter identification is achieved, but the processing complexity and time increase
Solution Approach 1:
The system analyzes metadata from a selected subset of similar images rather than all available images. By processing only the necessary portion of metadata required to determine the subject matter with sufficient accuracy, the system achieves effective entity identification without the excessive complexity of analyzing every possible metadata element from every similar image.
3Loss of information
If the search engine generates comprehensive search result pages with entity information, then users receive complete information about the subject matter, but the time and resources required to generate these pages increase
Solution Approach 1:
The system pre-generates search result pages with entity information before user requests. By performing the information gathering and organization in advance, the system can quickly retrieve and present comprehensive entity details when a user submits an image query, without having to generate the information on-demand.
Data Source
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AI summary
Systems and methods for responding to an image query from a computer user are provided. According to the disclosed subject matter, in response to receiving an image query, a search engine identifies the subject matter of the query image according to similar images. An entity name is determined from the similar images and is mapped to a known entity of the search engine. Based on the known entity, related information regarding the known entity is obtained and one or more search results pages directed to the known entity are generated. At least one of the generated search results pages is returned to the computer user as a response to the image query.