Poll-Based Matching System Using Distributed Match Servers
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Solution Overview
Problem
Existing social networking and ecommerce sites fail to provide real-time matching of users with products, goods, and services based on cumulative poll answers, as they only match user profiles against predefined categories rather than progressively polling and matching across all available options.
Innovation Solution
A data processing system with multiple match servers and a match aggregator that receives user poll answers, compares them against product and service profiles, and generates a likelihood of match based on cumulative answers, providing real-time results by using a distributed architecture and in-memory arrays for efficient comparison and aggregation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing sites match user profiles against predefined categories, then the matching process is simple and fast, but the matching accuracy and relevance are insufficient because they do not progressively poll and match against all available options
Solution Approach 1:
The patent segments the matching system into multiple independent match servers, each responsible for a specific category or subset of products/services. This allows the system to perform comprehensive progressive polling across all categories while maintaining manageable complexity through modular architecture. Each server independently processes matching for its assigned segment, enabling accurate comprehensive matching without overwhelming system complexity.
Solution Approach 2:
The patent introduces a match aggregator as an intermediary component that coordinates between users, poll servers, and multiple match servers. The aggregator collects poll responses, distributes them to appropriate match servers, and aggregates the results back to the user. This intermediary layer enables the complex progressive matching process to be managed systematically, maintaining both accuracy and manageable complexity.
2Measurement precision
If the system progressively polls and matches users against all products, goods and services after each query, then the matching relevance is improved, but the processing time and computational load increase significantly
Solution Approach 1:
By dividing the product catalog into segments managed by different match servers, the system can process matching requests in parallel across multiple servers simultaneously. This segmentation enables comprehensive progressive polling without sequential processing delays, maintaining high matching relevance while reducing overall processing time through concurrent operations.
Solution Approach 2:
The system performs preliminary actions by pre-organizing products and services into categorized segments assigned to specific match servers. This preliminary structuring allows incoming user poll responses to be quickly routed to the appropriate servers for immediate processing, eliminating the need for ad-hoc comprehensive searches and significantly reducing processing time while maintaining matching relevance.
3Productivity
If multiple match servers are used to handle matching operations, then the system scalability and processing capacity are improved, but the system architecture becomes more complex
Solution Approach 1:
The match aggregator serves as a universal component that handles multiple functions: receiving user poll responses, distributing requests to appropriate match servers, collecting results from multiple servers, and presenting aggregated results to users. This multi-functional intermediary simplifies the overall architecture by providing a single point of coordination, reducing the complexity that would otherwise arise from direct peer-to-peer interactions between multiple match servers.
4Ease of operation
If the system provides real-time matching results, then the user experience is improved, but the computational resources and processing speed requirements increase
Solution Approach 1:
The segmentation of matching operations across multiple specialized servers enables parallel processing of user poll responses. This parallelism provides real-time matching results to users while distributing computational resource consumption across the server cluster, preventing any single server from being overwhelmed and reducing overall energy requirements compared to a centralized real-time processing system.
Data Source
AI summary
Described is a poll-based system that provides an on-line network of products, goods and services that are determined through polling each of the users. This system polls a user with a variety of questions. The system compares, in real-time, the current user's responses with all products, goods and services to identify which most similarly match the answered questions to that of the user. As the user progressively answers questions, the system updates the matching and presentation of products, goods and services. Thus, as the user answers polling questions, the selected answers are compared against the selected descriptions of other products, goods and services to generate a likelihood of match between the user and each of the products, goods and services. The profiles of products, goods and services that have a likelihood of match within a predetermined threshold are then presented, including links within the profile for specific purchases.