Multi-Pass Search Pipeline for Precision-Recall Tradeoff
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Solution Overview
Problem
Electronic commerce websites face challenges in achieving a balance between precision and recall in search results, as single search passes often result in either highly precise but incomplete results or imprecise results with high recall, leading to poor user experience due to irrelevant products.
Innovation Solution
Implementing a multiple context-dependent search engine system that performs multiple search passes with different strategies, using a conditional search flow pipeline based on transition rules and search context information to optimize precision and recall, where each search pass can be progressively less precise and the sequence determined by previous search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single search pass is performed with high precision filtering, then precision is improved, but recall deteriorates (search results become incomplete)
Solution Approach 1:
The search process is divided into multiple sequential search passes, each with different precision and recall characteristics. The first pass uses high precision filtering to ensure accurate results, while subsequent passes use progressively less precise filtering to capture additional relevant results that may have been missed, thereby improving overall recall without sacrificing the precision established in earlier passes.
Solution Approach 2:
The system performs multiple search passes beyond the single traditional pass, applying progressively less precise filtering in each subsequent pass. This excessive action (more passes than necessary for a single threshold) ensures that relevant results are captured even if they require more lenient filtering criteria, thus improving recall while maintaining precision through the sequential nature of the passes.
2Quantity of substance
If a single search pass is performed with high recall filtering, then recall is improved, but precision deteriorates (search results include irrelevant products)
Solution Approach 1:
The search process is segmented into multiple passes where the first pass applies strict precision filtering to establish a high-quality baseline. Subsequent passes then expand the search with progressively less precise filtering to capture additional results, but only after the precision framework has been established by earlier passes, thus improving recall without compromising overall precision.
Solution Approach 2:
The system performs preliminary high-precision filtering in early search passes to establish a quality baseline and identify clearly relevant results. This preliminary action creates a foundation of precise results before subsequent passes with less precise filtering are applied, ensuring that the precision standard is set early and maintained throughout the multi-pass process while still allowing recall to improve.
3Measurement precision
If multiple search passes are performed, then precision and recall are improved, but system complexity increases
Solution Approach 1:
The complex task of achieving both high precision and recall is segmented into multiple simpler search passes, each with a single filtering threshold. This segmentation breaks down the complex optimization problem into manageable sequential steps, where each pass handles a specific precision level, making the overall system more tractable and easier to implement than a single complex pass attempting to optimize both parameters simultaneously.
Solution Approach 2:
The system changes the filtering parameter (precision threshold) across multiple search passes rather than using a single fixed parameter. Each subsequent pass uses a progressively less precise threshold, allowing the system to capture results at different precision levels. This parameter variation approach simplifies the search algorithm by using straightforward threshold adjustments rather than complex adaptive filtering logic.
Data Source
AI summary
A method including the steps of: receiving a search query; executing a first search pass of a conditional search flow pipeline according to a first configuration; generating and storing information based on the executed first search pass as search context information; determining which search pass of the conditional search flow pipeline should be executed as a second search pass based on a transition rule associated with the first search pass and the search context information; executing the second search pass of the conditional search flow pipeline according to a second configuration; generating additional information based on the executed second search pass; updating the search context information based on the additional information; and determining whether to provide updated search context information or proceed to another search pass of the conditional search flow pipeline based on a transition rule associated with the second search pass and the updated search context information.