Resource Sorting by User State Categories for Relevance Ranking
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Solution Overview
Problem
Existing information retrieval and recommendation systems struggle to accurately sort resources based on the dynamic and implicit preferences of users, leading to suboptimal resource recommendation.
Innovation Solution
A method and apparatus that determine a target object's state feature, match it with candidate state categories to identify a target state category, and adjust resource order in a candidate resource set based on associated target resource features, utilizing data dimension reduction, cluster analysis, and resource similarity calculations to enhance sorting accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional resource sorting methods are used, then the system structure remains simple, but the accuracy of resource sorting deteriorates due to inability to capture dynamic and implicit user preferences
Solution Approach 1:
The patent segments the resource sorting process into distinct modules: user state identification module that determines user states from behavioral data, resource matching module that matches resources to user states, and resource sorting module that ranks resources based on matching results. This segmentation allows complex sorting logic to be implemented while maintaining manageable system structure through modular design.
Solution Approach 2:
The patent performs preliminary classification of user states and resource types before the actual sorting process. User behavioral data is pre-processed to identify user states, and resources are pre-categorized into types. This preliminary action enables the sorting algorithm to work with structured, pre-processed data, improving accuracy without proportionally increasing complexity.
2Measurement precision
If comprehensive user preference analysis is implemented, then resource sorting accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent applies local quality by focusing computational resources on analyzing only the behavioral data and features most relevant to each user's current state and each resource type. Instead of uniformly processing all user data and resource attributes, the system adapts the analysis depth and scope to local requirements, improving accuracy for critical factors while reducing unnecessary computational overhead.
Solution Approach 2:
The patent dynamically adjusts processing parameters based on user state and resource type. Different user states trigger different analysis depths, and different resource types require different matching criteria. This parameter adaptation allows the system to maintain high sorting accuracy while optimizing processing time by avoiding uniform exhaustive analysis across all scenarios.
Data Source
AI summary
Provided is a method for sorting resources, an electronic device and a storage medium, relating to the field of artificial intelligence technology, and specifically to the fields of intelligent search, information flow, intelligent question and answer, and other technologies. The method includes: determining a state feature of a target object; matching the state feature with a plurality of candidate state categories of the target object to obtain a matched candidate state category as a target state category; and adjusting a resource order in a candidate resource set of the target object based on a target resource feature of the target object associated with the target state category.