Image Retrieval Intent Analysis and Screen-Aware Selection

The patent segments the image retrieval process into multiple stages: initial keyword-based retrieval to get candidate images, followed by secondary filtering based on user preferences, image attributes, and relevance scoring. This segmentation allows the system to first cast a wide net with keywords, then systematically narrow down results through multiple filtering layers, reducing the time users spend searching through massive result sets.

The patent introduces an intermediary retrieval system that acts as a mediator between the user's keyword search and the image database. This intermediary layer processes keywords through semantic analysis, applies filtering rules, and ranks results before presenting them to users. The intermediary transforms the raw keyword search into a refined, prioritized list of images, significantly reducing the effective search time users experience.

The patent extracts and applies multiple filtering criteria from user profiles, image metadata, and contextual information to filter the massive set of keyword-matched images. By taking out and applying these additional filtering conditions (user preferences, image attributes, relevance scores), the system extracts only the most relevant subset of images from the keyword search results, dramatically reducing the quantity of results presented to users while maintaining ease of search.

The patent changes multiple parameters simultaneously to refine search results: it adjusts relevance scoring weights, applies dynamic filtering thresholds, modifies result ranking criteria, and adapts to user preference parameters. By changing these parameters based on user context and image characteristics, the system transforms the raw keyword match results into a refined, manageable set of highly relevant images, reducing the overall quantity of results while improving quality.

The patent performs preliminary analysis of user intent by analyzing search keywords, user profiles, and contextual information before executing the actual image retrieval. It pre-processes user queries to extract intent signals, pre-filters candidate images based on user preferences, and pre-ranks results according to predicted relevance. This preliminary action ensures that when images are retrieved, they are already optimized for the specific user's intent and display context, preventing loss of intent information throughout the retrieval process.

The patent implements dynamic adaptation of retrieval parameters based on real-time analysis of user intent and screen display status. The system dynamically adjusts search depth, filtering criteria, result ranking algorithms, and image selection based on detected user preferences and device characteristics. This dynamic approach ensures the retrieval process continuously adapts to preserve and act upon user intent information, rather than using static, one-size-fits-all retrieval methods.