Dynamic Resource Quota Allocation for User-Specific Transfer
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Solution Overview
Problem
Conventional resource transfer methods on network platforms are inflexible, as they typically provide fixed resource quotas to all users, which does not effectively enhance user experience or conversion rates.
Innovation Solution
A method and device that determine user-specific resource quotas by analyzing profile data across multiple dimensions, including historical access behavior, transaction data, and user description data, to dynamically assign varying resource amounts based on user labels and historical transfer records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If fixed resource quotas are transferred to all access users, then the resource transfer process is simple and quick, but the user experience and conversion rates cannot be effectively enhanced
Solution Approach 1:
The patent implements dynamic resource quota allocation by transitioning from fixed quotas to user-specific variable quotas. The system dynamically determines resource quotas based on user profile data, labels, and multiple dimensions of user characteristics, allowing the resource transfer amount to adapt automatically to each user's needs and behaviors.
Solution Approach 2:
The patent applies local quality by providing different resource quotas to different users based on their individual characteristics. Instead of uniform treatment, the system analyzes user-specific data (profile data, labels, behavior patterns) to allocate resources locally optimized for each user, thereby enhancing user experience while maintaining operational efficiency through automated determination.
2Ease of manufacture
If fixed resource quotas are set by service provider experience, then the implementation is straightforward, but the flexibility and precision of resource allocation are insufficient
Solution Approach 1:
The system implements self-service by enabling automated determination of resource quotas through user profile data analysis. Instead of relying on service provider experience and manual setting, the system autonomously analyzes user characteristics, generates user labels, and calculates appropriate resource quotas automatically, improving both precision and operational efficiency.
Solution Approach 2:
The patent replaces the mechanical system of experience-based manual quota setting with an automated information processing system. The system uses user profile data, label determination algorithms, and computational methods to substitute human judgment with precise automated analysis, thereby achieving higher allocation precision while maintaining implementation feasibility.
3Device complexity
If uniform resource quotas are provided to all users, then the system complexity is low, but the conversion rates and user engagement are limited
Solution Approach 1:
The patent applies segmentation by dividing users into different segments based on their profile data and characteristics. The system determines user labels across multiple dimensions and allocates resources according to these segmented user groups, allowing differentiated resource distribution that enhances conversion rates while managing complexity through structured segmentation approaches.
Solution Approach 2:
The system implements parameter changes by varying resource quota parameters based on user-specific factors. Instead of using a single fixed parameter for all users, the system adjusts resource allocation parameters dynamically according to user profile data, labels, and analyzed characteristics, thereby improving conversion rates through personalized parameter optimization.
Data Source
AI summary
Implementations of this disclosure provide for resource transfer operations. An example method performed by a computing device includes receiving a resource transfer request that includes a user identifier of a user; obtaining profile data for a plurality of dimensions of the user; determining for each dimension, a field value of a feature field corresponding to the dimension; generating for each dimension, one or more user label values for the user, based on the field value of the feature field corresponding to the dimension; determining, for each of the one or more user label values for the user, an initial resource quota corresponding to the user label value for the user; determining a final resource quota for the user based on initial resource quotas; and transferring, by the computing device, resources to the user based on the final resource quota.