Delivery Search Facets Using Arrival Time Confidence Scores
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Solution Overview
Problem
Existing search technologies consume excessive computing resources and fail to provide accurate and certain arrival times for items, leading to repetitive user inputs and inefficient search results, particularly in large item catalogs.
Innovation Solution
A search system that employs arrival times and confidence scores as search facets, determined using machine learning models trained on historical fulfillment and delivery data, to efficiently filter and sort items based on delivery-related information such as arrival times, environmental scores, and delivery costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional search technologies are used to search large item catalogs, then search results can be provided, but computing resource consumption increases and repetitive user inputs occur
Solution Approach 1:
The system pre-calculates and stores arrival time estimates and confidence scores for items in the catalog before user search queries are executed. This preliminary computation of delivery-related metadata allows the search system to provide more accurate and relevant results without requiring extensive real-time computing resources for each search query, thereby reducing overall computing resource consumption while improving search efficiency.
2Measurement precision
If traditional search technologies are used, then items can be identified, but accurate and certain arrival times cannot be provided
Solution Approach 1:
The system incorporates confidence scores that reflect the reliability of arrival time predictions based on historical fulfillment and delivery data. These confidence scores provide feedback on the accuracy and certainty of arrival time estimates, allowing the system to communicate the reliability of delivery predictions to users. The confidence scores are derived from analyzing patterns in historical data, enabling the system to provide both accurate arrival times and a measure of certainty about those times.
3Ease of operation
If comprehensive delivery information is provided for all items, then search result quality improves, but system complexity increases
Solution Approach 1:
The system extracts and provides only the most relevant delivery-related information (arrival time and confidence score) rather than comprehensive delivery details for all items. This selective information extraction maintains search result quality by providing essential delivery metrics that help users make informed decisions, while avoiding the complexity of implementing and managing a comprehensive delivery information system that would require tracking every possible delivery parameter, carrier, and shipping condition.
Data Source
AI summary
A search system employs arrival times with associated confidence scores as search facets for identifying items. The search system identifies a plurality of items based on search input. An arrival time and associated confidence score are determined for each item from the plurality of items. Search results are provided for the plurality of items in response to the search input. The search results are provided based at least in part on the arrival times and associated confidence scores for the plurality of items.