Search Engine Product Matching via Binary Mask Caching
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Solution Overview
Problem
Existing content provider systems face increased latency and computational resource usage when integrating ancillary products or services with main products, leading to a negative impact on user experience due to the significant computational costs associated with processing and pricing these additional offerings.
Innovation Solution
A distributed computing environment utilizing a product cache database and an inventory database, where main products are associated with reference binary masks representing ancillary products, allowing for efficient matching and availability determination through Bloom filters, thereby reducing unnecessary computations and improving response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the search engine processes and integrates ancillary products with main products during the search process, then the user receives comprehensive product information, but the system latency increases and computational resources are consumed
Solution Approach 1:
The patent pre-computes and stores ancillary product information, pricing, and availability in a cache database before search requests arrive. When a search request comes in, the engine only needs to retrieve pre-processed data rather than computing everything in real-time, thus providing comprehensive product information without significantly increasing latency
Solution Approach 2:
The patent extracts ancillary product integration from the main search processing path. By separating ancillary product retrieval into a parallel or post-processing step using pre-computed cache data, the system avoids the computational overhead of integrating ancillary products during the critical search path, thereby reducing latency while still providing complete product information
2Reliability
If the search engine integrates ancillary products and computes their availability during search processing, then the user receives accurate product availability information, but computational resources are significantly consumed
Solution Approach 1:
The system pre-computes ancillary product availability, pricing, and compatibility information and stores it in a cache database. This allows the search engine to retrieve pre-validated availability data without performing complex computational checks during each search, maintaining reliability while reducing computational resource consumption
Solution Approach 2:
The patent creates a cached copy of ancillary product information that mirrors the structure and validity of the main product database. This copy contains pre-processed availability and pricing data that can be queried efficiently without accessing the full computational complexity of the source systems, thus maintaining accuracy while reducing energy consumption
Data Source
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AI summary
A search engine is configured to determine a set of main products that match search criteria of a search request. A search binary mask is generated based on the search criteria indicated in the search request which identify one or more ancillary products. If the search binary mask matches a reference binary mask representing the requested ancillary products, the main products are selected for the response to the search request. The search engine also verifies a cur-rently availability of the ancillary products associated with the selected main products and returns at least one of the main products for which the current availability has been deter-mined.