Entity Image Selection via Dual Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current search systems struggle to accurately identify and rank images that are evocative of specific entities, such as persons, countries, or organizations, as they lack effective methods to assess the topical relatedness and visual characteristics of images in relation to the entities they represent.
Innovation Solution
The system identifies entity queries for an entity, performs image searches, determines entity-image and entity-resource scores to assess topical relatedness, and assigns images to entities based on these scores, while also considering visual characteristics and the number of resources each image is featured in, to select an image that is evocative of the entity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system uses only basic image search methods, then the search process is simple and fast, but the accuracy of identifying entity-evocative images is low
Solution Approach 1:
The patent segments the image evaluation process into two distinct scoring components: entity-image scores (assessing visual characteristics and direct entity representation) and entity-resource scores (assessing topical relatedness of hosting resources). This segmentation allows the system to evaluate images from multiple dimensions independently, improving identification accuracy while maintaining manageable system complexity through modular scoring.
Solution Approach 2:
The patent introduces a dual-parameter scoring system that transforms the single-dimension image search into a multi-dimensional evaluation framework. By calculating both entity-image scores (based on visual features) and entity-resource scores (based on resource topicality), the system changes the evaluation parameters to achieve more precise image-entity matching without overwhelming complexity.
2Measurement precision
If the system assigns images to entities based on multiple scoring criteria, then the image-entity matching accuracy improves, but the computational time and processing complexity increase
Solution Approach 1:
The patent performs preliminary actions by pre-calculating and storing entity-resource scores for resources in the system. When an image search is conducted, the system can quickly retrieve pre-computed resource scores rather than calculating them in real-time, significantly reducing processing time while maintaining the accuracy benefits of the dual-scoring approach.
Solution Approach 2:
The patent introduces resource scores as an intermediary component that bridges images and entities. Instead of directly comparing images to entities, the system uses the hosting resource as an intermediary with its own topicality score. This intermediary approach distributes the computational workload and enables more accurate matching through indirect evaluation pathways.
3Measurement precision
If the system evaluates both visual characteristics and topical relatedness of images, then the relevance of selected images to entities improves, but the difficulty of detecting and measuring increases
Solution Approach 1:
The patent uses the hosting resource as an intermediary to measure topical relatedness. Instead of directly analyzing the complex relationship between image content and entity meaning, the system evaluates the topicality of the resource that hosts the image. This intermediary approach simplifies the measurement process while maintaining relevance accuracy, as resources are typically well-structured with clear topical associations to entities.
Solution Approach 2:
The patent replaces complex mechanical analysis of image-content-to-entity-meaning relationships with a more manageable system that evaluates resource metadata and topicality indicators. By substituting direct semantic analysis with resource-based topicality scoring, the system reduces the difficulty of detection and measurement while preserving measurement precision.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying an image for an entity. In one aspect, a method includes identifying a set of resources. Each resource can include at least one image and reference at least one entity. Each image is assigned to a particular entity based on an overall entity scores for the image relative to the entities. The overall entity score for an image and an entity can specify a measure of topical relatedness between the image and the entity. For each individual entity referenced by at least one of the resources, a group of images that have been assigned to the individual entity is identified. An image evocative of each individual entity is selected from the group based on image rank scores. The image rank score for an image can be determined based on visual characteristics of the image.