Image Matching Module for Search Result Visual Enhancement
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Solution Overview
Problem
Conventional search engines fail to effectively match images with search results, leading to unattractive and unengaging search outputs, as they lack an efficient mechanism to associate relevant images with content items in real-time.
Innovation Solution
A system is implemented that uses query-image matching rules to map predetermined keywords to image identifiers, incorporating semantically similar keywords and filtering based on metadata to dynamically match and rank images with content items, enhancing the search result's attractiveness by integrating images as backgrounds or complements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional search engines return content items as is without modification, then the search process is simple and fast, but the search results are unattractive and unengaging
Solution Approach 1:
The patent introduces an image matching module as an intermediary between the search engine and search results. This module automatically selects and matches relevant images to content items based on metadata analysis, transforming plain text results into visually engaging presentations without requiring user intervention or complex manual curation
Solution Approach 2:
The system performs preliminary actions by pre-processing and analyzing metadata of both content items and images before the search query is executed. This includes extracting features, building indexes, and preparing matching criteria in advance, so that when a search occurs, images can be quickly matched and integrated into results without adding significant latency
2Difficulty of detecting and measuring
If images are manually curated and matched with content items, then the visual appeal of search results improves, but the complexity and time consumption of the search process increases significantly
Solution Approach 1:
The patent implements a self-service mechanism where the image matching module automatically selects and matches images to content items without human intervention. The system uses metadata analysis, feature extraction, and automated ranking algorithms to perform the matching task independently, eliminating the need for manual curation while maintaining high visual quality
Solution Approach 2:
The patent replaces the mechanical/manual system of manual image curation with an automated computational system. This includes using metadata analysis algorithms, feature extraction techniques, and automated matching mechanisms that process and match images based on content relevance rather than human judgment, significantly reducing complexity and time consumption
3Difficulty of detecting and measuring
If images are matched with content items in real-time, then the visual appeal and relevance of search results improve, but the processing time and computational resources increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing metadata, extracting features, and building indexes for both content items and images before search queries are executed. This advance preparation enables the system to quickly retrieve and match relevant images during real-time search operations without adding significant processing delay
Solution Approach 2:
The system applies partial action by selectively matching images only to certain content items based on relevance criteria and confidence thresholds. Rather than attempting to match images with all search results, the system focuses computational resources on content items where image enhancement would provide the most value, thereby reducing overall processing time while maintaining high relevance
Data Source
AI summary
According to one embodiment, in response to a search query received at a server from a client device for searching content, a search is performed in a content database or via a content server based on one or more search terms of the search query to identify a first list of one or more content items. A search is performed in an image store based on the one or more search terms to identify a list of one or more images. Each content item of the first list is associated with one of the images. A second list of one or more content items having at least a portion of the images integrated therein is generated. The second list of content items is transmitted to the client device, such that each content item of the first list is presented with one of the images.