Search Platform Confidence Factor Filtering
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Solution Overview
Problem
Pre-computed or pre-collected search results in database systems often become outdated, leading to incorrect results when underlying primary data changes, limiting the ability to achieve perfect validity or correctness.
Innovation Solution
Assigning confidence factors to pre-collected search results to indicate their validity probability, and using these factors to filter and return only results with confidence values exceeding a specified threshold, thereby increasing the likelihood of returning valid results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If pre-computed or pre-collected search results are maintained in a pool to speed up query response times, then query processing speed is improved, but the validity or correctness of results deteriorates as underlying primary data changes
Solution Approach 1:
The system performs preliminary actions by pre-computing and storing search results in a pool before queries are submitted. This allows rapid query response times while managing the trade-off of potential outdated data through confidence factor tracking and selective re-computation strategies.
Solution Approach 2:
The system changes parameters by introducing confidence factors that quantify the validity probability of pre-computed results. These confidence factors are updated based on data change detection, allowing the system to dynamically adjust result selection criteria to maintain reliability while preserving speed benefits.
2Reliability
If confidence factors are assigned to pre-collected search results to indicate validity probability, then result validity is improved, but system complexity increases
Solution Approach 1:
The system introduces confidence factors as an intermediary element between the pre-computed search results and the query processing logic. These confidence factors serve as a mediator that quantifies validity without requiring complex real-time verification, simplifying the overall system architecture while improving reliability.
3Measurement precision
If only pre-computed search results with confidence factors exceeding a threshold are returned, then result accuracy is improved, but the quantity of returned results may decrease
Solution Approach 1:
The system changes the selection parameter by introducing a confidence factor threshold that filters pre-computed results. This parameter change enables the system to return only results meeting a minimum validity standard, improving accuracy while the threshold can be adjusted to balance result quantity requirements.
Data Source
AI summary
Methods, search platforms, systems, and storage media for handling queries in a database system. The database system includes at least one client and at least one search platform. The search platform maintains pre-collected search results which are associated which confidence factors. A confidence factor indicates a probability of the associated pre-collected search result being valid. The search platform receives a query indicating at least one search criterion to the search platform. The confidence factors associated with the identified pre-collected search results are utilized to increase the mean probability of pre-collected search results returned to the client. For example, pre-collected search results complying with the at least one search criterion and being associated with confidence factors having values exceeding a given threshold are returned to the client.