Service Sequence Update Logic for On-Demand Platforms
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing on-demand service systems fail to provide a customized sequence of services to users without frequent updates, leading to inefficient user experience and outdated service recommendations.
Innovation Solution
A system and method that determine an updated sequence of services based on user behavior analysis, including historical requests, current availability, and location-specific data, to prioritize services likely to be requested by the user, ensuring the sequence is updated only when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the sequence of services is updated frequently to provide customized recommendations, then the relevance of service recommendations is improved, but the system complexity and computational resources increase
Solution Approach 1:
The system changes parameters such as update frequency thresholds, service selection criteria, and user behavior analysis parameters to optimize the balance between recommendation relevance and system complexity. By adjusting these parameters dynamically, the system can provide customized service sequences without excessive computational overhead.
2Ease of operation
If the sequence of services is updated frequently to reflect user behavior changes, then the user experience is improved, but the loss of time and computational resources increases
Solution Approach 1:
The system implements periodic updates of the service sequence based on predetermined time intervals and user activity thresholds. Instead of continuous real-time updates, the system periodically analyzes user behavior and refreshes the service sequence when significant changes are detected, reducing unnecessary computational waste while maintaining relevant recommendations.
3Adaptability or versatility
If the sequence of services is customized for each user, then the adaptability is improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The system applies local quality by customizing the service sequence for each user based on their specific behavior patterns, location, and preferences, while using standardized processing algorithms. This allows personalized recommendations without requiring completely separate systems for each user, thus managing complexity efficiently.
4Measurement precision
If the system monitors user behavior continuously to update service sequences, then the accuracy of service recommendations is improved, but the energy consumption and processing load increase
Solution Approach 1:
The system performs partial monitoring of user behavior by focusing on key events and significant changes rather than continuously analyzing all user actions. This selective approach maintains recommendation accuracy by capturing essential behavior patterns while reducing overall processing load and energy consumption.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
The present disclosure relates to systems and methods for updating a sequence of services. The systems may perform the methods to establish a network communication with the user terminal; obtain, from the user terminal, an identification associated with a user account registered with the system; obtain a current sequence of the plurality of services associated with the identification; determine whether a condition for updating the current sequence is satisfied, when the condition for updating the current sequence is not satisfied, send the current sequence of the plurality of services to the user terminal; and when the condition for updating the current sequence is satisfied, determine an updated sequence of the plurality of services displayed on the display of the user terminal.