Image Matching System Using Multi-Method Search Prioritization
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Solution Overview
Problem
Current search engines lack efficient methods to match content items with relevant images, resulting in unattractive search results, as they fail to effectively evaluate and present images alongside content.
Innovation Solution
A system that performs multiple image searches using different methods based on keywords, content IDs, content providers, distribution plans, and locality, prioritizing image searching methods based on user interactions and ranking algorithms to select and integrate images with content items, enhancing the presentation of search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple image searching methods are used to match images with content items, then the attractiveness and relevance of search results is improved, but the system complexity and computational resources required increase
Solution Approach 1:
The patent segments the image matching process into multiple independent searching methods (keyword-based, content-based, provider-based, distribution plan-based, and locality-based searching). Each method operates as a separate module that can be independently executed and evaluated, allowing the system to achieve comprehensive matching accuracy while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The patent creates a universal image searching system that performs multiple types of searches (keyword, content, provider, distribution plan, locality) through a unified framework. This multi-functional system handles diverse matching requirements using a single integrated platform, reducing overall system complexity while improving matching precision across different scenarios.
2Measurement precision
If multiple image searching methods are implemented with prioritization based on user interactions, then the relevance of matched images is improved, but the time and computational resources required for processing increase
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing user interaction data, ranking algorithms, and matching scores for different image searching methods. This preprocessing allows the system to quickly retrieve and apply pre-evaluated matching results during actual search operations, reducing real-time processing time while maintaining high image relevance through pre-optimized matching criteria.
Solution Approach 2:
The patent introduces dynamic prioritization where the selection and weighting of different image searching methods adjusts based on real-time user interaction patterns and historical data. The system dynamically modifies search priorities and matching thresholds to balance relevance and processing speed, optimizing performance based on current operational conditions and user behavior.
3Adaptability or versatility
If images are integrated with content items based on multiple searching methods, then user engagement is enhanced, but the complexity of result presentation and integration increases
Solution Approach 1:
The patent segments the result integration process into distinct components: image retrieval, matching evaluation, prioritization based on user interactions, and presentation formatting. Each component handles a specific aspect of the integration task independently, reducing overall integration complexity while enabling versatile and engaging result presentation through modular composition.
Solution Approach 2:
The patent introduces an intermediary ranking and selection module that mediates between multiple image searching methods and the final content presentation. This intermediary layer evaluates images from different searching methods, applies prioritization based on user interactions, and selects the most relevant images for integration with content items, simplifying the overall integration process while enhancing user engagement through carefully selected imagery.
Data Source
AI summary
According to one embodiment, in response to a search query received from a client, a search is performed in a content database to identify a list of one or more content items based on one or more keywords of the search query. A first search is performed in an image store to identify a first set of one or more images using a first image searching method. A second search is performed in the image store to identify a second set of one or more images using a second image searching method that is different than the first image searching method. A search result is transmitted to the client, the search result having at least a portion of the content items to the client. Each content item is associated with one of the images selected from the first set of images or the second set of images.