Search Result Ranking Explanation System
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Solution Overview
Problem
Conventional search result ranking methods fail to accurately reflect user interests due to intrinsic uncertainties and lack of real-time personalization, as they cannot sense 'ad-hoc' user contexts and do not provide transparent ranking calculations.
Innovation Solution
A system that processes search results to calculate rankings, determines relevant parameters, and presents explanations for these rankings to users, allowing them to modify parameters and values based on their context, enabling personalized search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If search results are ranked based on internal system ranking algorithm, then search results can be automatically ordered, but the results may not truly reflect user interests at particular time due to inability to sense ad-hoc context
Solution Approach 1:
The patent implements feedback mechanisms where users can provide corrections to search result rankings. The system processes user feedback and adjusts ranking parameters accordingly, creating a closed-loop system that continuously improves personalization. Users can indicate preferred results, and the system learns from these preferences to refine future rankings, thereby adapting to user context while maintaining automated operation.
Solution Approach 2:
The patent makes the ranking system dynamic by allowing parameters to change in real-time based on user interactions and context. Rather than static ranking algorithms, the system dynamically adjusts weighting factors and ranking criteria according to user preferences, device type, location, and temporal context, enabling adaptation to ad-hoc situations while preserving automation.
2Productivity
If conventional ranking methods are used, then search results can be generated quickly, but the results lack real-time personalization for specific users
Solution Approach 1:
The patent implements preliminary action by pre-calculating and storing ranking parameters, weights, and user profile data before search queries are executed. When a user searches, the system retrieves pre-prepared ranking configurations and applies them immediately, rather than computing everything from scratch. This allows rapid generation of personalized results by combining pre-processed data with current query context.
Solution Approach 2:
The patent enables real-time personalization through parameter changes by dynamically adjusting ranking weights and thresholds based on user profiles, device characteristics, and contextual factors. The system modifies parameters such as relevance weights, freshness factors, and user preference multipliers in real-time, allowing personalized results to be generated quickly without fixed, static ranking criteria.
3Reliability
If user feedback is allowed, then search results can be improved, but users are unaware of the particular variables that go into calculating the ranking
Solution Approach 1:
The patent introduces an intermediary layer between the complex ranking algorithm and the user. This intermediary presents simplified explanations of ranking factors, showing users which parameters (such as relevance, freshness, popularity) influenced their results without exposing the underlying complexity. Users can see which factors boosted or lowered specific results, enabling informed feedback while maintaining system sophistication.
Solution Approach 2:
The patent segments the ranking explanation into distinct, understandable components. Rather than presenting a single opaque score, the system breaks down rankings into separate factors (relevance matching, recency, user preferences, popularity) and displays their individual contributions. This segmentation makes the ranking process transparent and allows users to understand and feedback on specific aspects without being overwhelmed by complexity.
4Ease of operation
If search results are highly personalized, then user satisfaction improves, but the system complexity increases due to multiple parameters and real-time adjustments
Solution Approach 1:
The patent implements self-service by enabling users to directly control and adjust ranking parameters through an intuitive interface. Users can manually weight different factors, prioritize specific criteria, and customize their experience without requiring complex backend processing for each adjustment. The system adapts to user preferences through direct user control rather than complex inference, reducing system complexity while maintaining high personalization.
Data Source
AI summary
An approach is provided for providing user-corrected search results. The explanation platform processes and/or facilitates a processing of one or more search results to calculate a ranking of the one or more search results. Next, the explanation platform determines one or more parameters related to calculating the ranking, one or more values of the one or more parameters, or a combination thereof. Then, the explanation platform causes, at least in part, a presentation of one or more representations of at least one of the one or more parameters as one or more explanations for the ranking.