Unified Ranking Model for Multi-Context Search Results
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Solution Overview
Problem
Traditional web rankers are inefficient and difficult to maintain due to their narrow configuration, requiring multiple rankers for different attributes and struggling to blend analysis results across various contexts, and they fail to adapt results based on the device used for querying.
Innovation Solution
A unified ranking model that considers multiple signals such as location, form-factor, time, entry points, and personalization to rank results data, allowing for a single ranker to handle diverse contexts and provide personalized results across different devices and platforms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple individual web rankers are used to rank different attributes, then the analysis thoroughness is improved, but the system complexity and maintenance overhead increase
Solution Approach 1:
The patent combines multiple individual web rankers into a single unified ranker that processes multiple attributes simultaneously. The unified ranker integrates location-based ranking, relevance-based ranking, and other attribute-specific ranking functions into one system, reducing the number of separate components while maintaining comprehensive analysis capabilities.
Solution Approach 2:
The unified ranker is designed to perform multiple ranking functions across different attributes and contexts. It can rank results based on location, relevance, device type, and other attributes within a single system, making the ranker universal and multi-functional rather than requiring specialized rankers for each attribute.
2Adaptability or versatility
If multiple individual web rankers are used for different attributes, then the ranking coverage is improved, but the difficulty in blending analysis results increases
Solution Approach 1:
The unified ranker merges multiple ranking analyses into a single integrated process. Instead of separately executing location-based ranking, relevance-based ranking, and other attribute-specific rankings then attempting to blend results, the unified ranker performs all rankings simultaneously within one system, eliminating the blending complexity.
Solution Approach 2:
The unified ranker acts as an intermediary that receives query results and automatically applies multiple ranking criteria. It mediates between the raw search results and the final ranked output, incorporating location, relevance, device type, and other attributes through a single coordinated process rather than requiring manual integration of multiple separate ranking systems.
3Ease of operation
If traditional web rankers are used, then the system simplicity is maintained, but the adaptability to different devices and contexts is reduced
Solution Approach 1:
The unified ranker is designed as a universal system that adapts to different devices (desktop, tablet, mobile) and contexts automatically. It incorporates device-type detection and context-aware ranking capabilities, allowing a single system to serve multiple purposes and adapt to varying user scenarios without requiring separate rankers for each device type.
Solution Approach 2:
The unified ranker employs dynamic ranking capabilities that adjust ranking criteria based on detected context such as device type, user location, and query characteristics. The system can dynamically modify its ranking behavior to suit different situations while maintaining a single, simple interface for operation.
4Ease of manufacture
If a unified ranking model is implemented, then the maintenance overhead is reduced, but the processing complexity within the unified model increases
Solution Approach 1:
The unified ranking model is organized into distinct functional modules or layers that handle different ranking criteria separately but coordinate them through a unified framework. This segmentation allows the complex processing to be divided into manageable components, making the model easier to maintain while still achieving comprehensive multi-attribute ranking.
Data Source
AI summary
Non-limiting examples of the present disclosure describe a unified ranking model that may be used by a plurality of entry points to return ranked results in response to received query data. The unified ranking model is provided as a service for a plurality of entry points. A query is received from an entry point of the plurality of entry points. Results data for the query data is retrieved. A unified ranking model is executed to rank the results data. Execution of the unified ranking model manipulates feature data of the unified ranking model based on user context signals associated with the received query data and acquired result retrieval signals corresponding with the retrieved results data. Execution of the unified ranking model generates ranked result data. Ranked results data is returned to the processing device corresponding with the entry point. Other examples are also described.