Content Selection Module Balancing Exploitation and Exploration Scores
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Solution Overview
Problem
Large organizations face challenges in optimizing the selection of electronic content for delivery to customers, as existing solutions struggle to balance maximizing return on message transmission while exploring new content, especially under constraints like limited message frequency and delayed user feedback.
Innovation Solution
A content selection module using machine learning to compute exploitation and exploration scores for candidate content, ranking them for optimal selection and dynamic updating based on user feedback, allowing for effective content delivery through various channels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the organization limits the number of messages sent to each customer to one per day, then the customer experience is improved by avoiding message overload, but the ability to explore new content and maximize return on transmission is worsened
Solution Approach 1:
The system implements feedback loops where user responses to sent messages are collected and used to update the selection model. This allows the system to learn from actual user behavior and improve content selection over time, maximizing the return from each transmitted message while respecting the one-message-per-day constraint.
Solution Approach 2:
The system dynamically adjusts selection parameters based on accumulated feedback data. By changing the parameters of the selection model in response to observed user responses, the system can optimize content selection for each individual customer within the message frequency constraint, balancing exploration of new content with exploitation of known effective content.
2Productivity
If the organization sends more messages to explore new content, then content exploration effectiveness is improved, but the customer experience deteriorates due to increased message volume
Solution Approach 1:
The system applies different selection strategies to different customers based on their individual characteristics and response histories. By customizing the content selection approach for each customer rather than using a uniform strategy, the system can effectively explore new content for some customers while maintaining optimal delivery frequencies for others, avoiding general message overload.
Solution Approach 2:
The message frequency and content selection are made dynamic rather than static. The system adapts the exploration-exploitation balance over time based on accumulated feedback, allowing more aggressive content exploration when data is scarce and more conservative approaches when confidence in content effectiveness is high, all within customer-specific frequency constraints.
3Device complexity
If the organization uses traditional content selection methods, then the system complexity is reduced, but the ability to optimize content selection under constraints is worsened
Solution Approach 1:
The patent introduces a content selection module as an intermediary between the message delivery system and the customers. This modular component handles the complex optimization calculations and feedback processing, isolating the complexity from the rest of the system. The module acts as a mediator that translates business constraints and user feedback into optimized content selections without requiring complex changes throughout the entire system.
Data Source
AI summary
Technologies for optimized selection of content for delivery to a user that both optimizes the expected return from the delivery of the content to the user and that enables exploration of delivery of new content to users are disclosed. Content is selected for delivery to a user based on an exploitation score that defines an estimate of the feedback expected from the delivery of the content to the user and an exploration score that varies inversely with the number of times that the content has been transmitted to all users. The use of the exploration score enables the exploration of delivery of new content to users. The content might be delivered via e-mail messages, a web site, or using another mechanism.