Alimentary Provider Selection via Pre-Trained Classifier
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Solution Overview
Problem
Current systems for fulfilling food orders, especially those requiring customization, face challenges in efficiency due to issues of timing, speed, quality, and necessity, with existing selection and communication processes falling short of ideal solutions.
Innovation Solution
A system and method using a computing device to receive user inputs for food requests and parameters, generating a list of alimentary preparation providers based on these parameters through a classification algorithm trained with parameter training data, allowing for optimal provider selection and load balancing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a classification algorithm is used to match users with providers, then matching accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-training the classification algorithm with parameter training data before actual use. The classifier is generated in advance by receiving parameter training data that correlates request parameters to ordered lists, and training the classification algorithm using this pre-prepared data, so that when a request comes in, the matching can be done quickly and accurately without complex real-time processing
Solution Approach 2:
The patent introduces a request parameter classifier as an intermediary component between the user request and the provider selection. This classifier acts as a mediator that processes the request parameters and generates an ordered list of providers, simplifying the overall system architecture by separating the complex matching logic into a dedicated intermediate layer that can be trained and optimized independently
2Reliability
If multiple providers are considered for each request, then service quality is improved, but processing time increases
Solution Approach 1:
The system generates an ordered list of providers in advance based on the classification algorithm and request parameters. By pre-processing and ranking providers before the actual assignment, the system能够快速返回结果而不需要实时复杂计算，从而在保证服务质量的同时减少了处理时间
Solution Approach 2:
The classification algorithm generates an ordered list of providers, and the system assigns the request to the first provider in the list. This partial action approach processes multiple providers through classification but only selects the top candidate, avoiding the need to evaluate all providers in detail and thus reducing processing time while maintaining service quality
Data Source
AI summary
A system of determining an alimentary preparation provider is disclosed. The system comprises a computing device. The computing device is configured to receive input from a user device at a current geographical location. The input comprises an alimentary request and a plurality of request parameters. The computing device generates a plurality of alimentary preparation providers as a function of the plurality of request parameters. A request parameter classifier is generated by the computing device. The computing device classifies, by the request parameter classifier, the plurality of request parameters and the plurality of alimentary preparation providers. The classification outputs an ordered list of request parameters. The computing device assigns the alimentary request to a first alimentary preparation provider as a function of an ordered list of request parameters. A method for determining an alimentary preparation provider is disclosed.