Image Search Semantic Entity Association
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Solution Overview
Problem
Current image search engines struggle to accurately identify semantic entities in images due to the ambiguity of text queries, often returning irrelevant results as they rely on text associations rather than contextual understanding.
Innovation Solution
A system and method that associate images with semantic entities by analyzing image labels and documents to identify similar images, determining a semantic entity for a target image based on similarity and confidence scores, and using this entity to provide relevant search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If text queries are used for image search, then search simplicity is improved, but search accuracy deteriorates due to ambiguity
Solution Approach 1:
The patent introduces semantic entities as an intermediary layer between text queries and image results. Instead of directly matching text to images, the system first resolves text queries to semantic entities (disambiguated concepts), then finds images associated with those entities. This mediator resolves the ambiguity problem while preserving query simplicity.
Solution Approach 2:
The system performs preliminary disambiguation of text queries into semantic entities before conducting the actual image search. By pre-resolving ambiguities and establishing clear semantic meanings upfront, the search process becomes more accurate without requiring users to formulate complex queries.
2Productivity
If image search relies on text associations, then processing speed is improved, but result relevance deteriorates
Solution Approach 1:
Semantic entities serve as a meaningful intermediary that preserves both efficiency and relevance. The system maintains fast processing by using pre-computed semantic associations, while improving relevance by ensuring that images are matched based on their actual semantic content rather than superficial text associations.
Solution Approach 2:
The system changes the parameter of association from simple text matching to semantic entity-based matching. This parameter change allows the system to maintain efficient processing through structured data relationships while significantly improving result relevance by matching images based on their true semantic meaning.
3Measurement precision
If semantic entity analysis is performed on all images, then search accuracy is improved, but computational complexity increases
Solution Approach 1:
The system performs semantic entity analysis in advance during an indexing phase, before actual search queries are processed. By pre-computing and storing semantic entity associations for images in a database, the system avoids performing complex analysis during each search operation, thus maintaining high accuracy while reducing real-time computational complexity.
Solution Approach 2:
The patent segments the search process into distinct phases: an offline indexing phase where semantic analysis is performed on images, and an online query phase where pre-computed semantic associations are used. This segmentation allows complex computation to be done once during indexing, while queries benefit from the pre-processed information without repeating the heavy computational work.
Data Source
AI summary
A system and computer-implemented method for associating images with semantic entities and providing search results using the semantic entities. An image database contains one or more source images associated with one or more images labels. A computer may generate one or more documents containing the labels associated with each image. Analysis may be performed on the one or more documents to associate the source images with semantic entities. The semantic entities may be used to provide search results. In response to receiving a target image as a search query, the target image may be compared with the source images to identify similar images. The semantic entities associated with the similar images may be used to determine a semantic entity for the target image. The semantic entity for the target image may be used to provide search results in response to the search initiated by the target image.