Universal Relevance Service Framework for Real-Time Ranking
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Solution Overview
Problem
Current relevance systems face issues with duplicate efforts, over-diversification, high development and operational costs due to separate code bases for batch and real-time systems, and inability to scale with business growth, while also struggling to support dynamic offerings with changing attributes in real-time.
Innovation Solution
A universal relevance service framework is implemented, providing a plug-in framework for seamless integration of evolving code, supporting both real-time and batch processing, and enabling horizontal scaling, with a continuous background computation model that decouples signal processing from servicing relevance computation requests, and includes a feature engineering infrastructure and real-time data stores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If separate code bases are used for batch and real-time systems, then each system can be optimized for its specific business use case, but duplicate efforts and over-diversification of architecture occur, leading to high development and operational costs
Solution Approach 1:
The patent implements a universal relevance service framework that serves both batch and real-time processing needs through a single code base. The framework includes a relevance API, data model, and processing engine that can handle different business use cases (search queries, targeted messaging, dynamic offerings) without requiring separate implementations, thereby eliminating duplicate efforts and architectural over-diversification while maintaining use-case optimization
2Adaptability or versatility
If incremental improvements are made to each separate code base in response to short business focus, then specific business needs are addressed, but development and operational costs increase
Solution Approach 1:
The patent merges previously separate batch and real-time code bases into a unified relevance service framework. This consolidation allows incremental improvements to be made in a single code base that benefits all business use cases simultaneously, rather than duplicating improvement efforts across multiple separate systems, thereby reducing development and operational costs while maintaining responsiveness to business needs
3Adaptability or versatility
If the system is designed to support dynamic offerings with changing attributes, then real-time personalization is enabled, but system complexity and computational requirements increase
Solution Approach 1:
The patent implements a continuous background computation model that pre-computes and maintains relevance scores for dynamic offerings as they change attributes. This preliminary action allows the system to handle real-time personalization requests without performing complex computations at query time, thereby enabling support for dynamic offerings while managing system complexity through advance preparation
4Productivity
If the system scales horizontally to accommodate business growth, then capacity increases, but coordination and management complexity increases
Solution Approach 1:
The patent designs the relevance service framework with a modular architecture that segments functionality into independent components (relevance API, data model, processing engine, plugins). This segmentation enables horizontal scaling where each component can be independently replicated and distributed across multiple servers, increasing system capacity while reducing coordination complexity through clear component boundaries and standardized interfaces
Data Source
AI summary
In general, embodiments of the present invention provide systems, methods and computer readable media for a universal relevance service framework for ranking and personalizing items.