Promoter Determination Using Feature-Based Priority Recall
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Solution Overview
Problem
Current solutions fail to efficiently determine a suitable promoter that meets a provider's needs, particularly in the context of guiding users to acquire objects through guidance contents, as selecting a suitable promoter from a large number of options is time-consuming and labor-intensive.
Innovation Solution
A method and apparatus for promoter determination that recall candidate promoters based on features of both the target provider and the promoters, using various recall policies such as Field-aware Factorization Machines, collaborative recall, contact establishment, lookalike, popularity, and similar object policies to determine priority levels and select a target promoter.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual selection of promoters from a large number of options is performed, then the provider can select a suitable promoter that meets its needs, but a significant amount of time and manpower costs are needed
Solution Approach 1:
The system enables automatic promoter selection through self-service mechanisms. The promoter determination apparatus automatically recalls candidate promoters, determines their priority levels based on features and historical data, and selects the target promoter without requiring manual intervention, thereby reducing time and manpower costs while maintaining selection quality
Solution Approach 2:
The patent replaces the mechanical manual selection process with an automated computational system. The promoter determination apparatus uses computer-based algorithms to recall candidates, evaluate priorities, and make selections, substituting human manual work with automated mechanical/computational processes that are faster and more efficient
2Measurement precision
If multiple recall policies are used to determine promoter priority, then the selection accuracy is improved, but the system complexity increases
Solution Approach 1:
The patent segments the promoter selection process into multiple independent recall policies (Field-aware Factorization Machines, collaborative recall, contact establishment, lookalike, popularity, and similar object policies). Each policy handles a specific aspect of promoter evaluation, allowing the system to achieve high accuracy through modular, organized components rather than a monolithic complex system
Solution Approach 2:
The promoter determination apparatus is designed with multi-functionality to handle various recall policies within a single unified system. This universal approach allows the same system to perform multiple types of promoter evaluations (based on different policies) without requiring separate systems for each policy, thereby managing complexity while maintaining accuracy
Data Source
AI summary
According to the embodiments of the present disclosure, a method, an apparatus, a device, a storage medium and a program product for promoter determination are provided. The method includes: recalling, from a set of promoters, a plurality of candidate promoters for a target provider, the target provider being capable of providing at least one object available to a user, the plurality of candidate promoters being capable of publishing guidance contents for guiding a user to acquire a corresponding object; determining, based on a first feature of the target provider and second features of the plurality of candidate promoters, priority levels of the plurality of candidate promoters; and determining, based on the priority levels, a target promoter for the target provider from the plurality of candidate promoters.