Information Processing Apparatus for Dynamic Advertisement Arrangement
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Solution Overview
Problem
Existing image forming apparatuses display irrelevant or previously viewed advertisements to users, failing to effectively recommend useful application functions based on usage history and viewing frequency.
Innovation Solution
An information processing apparatus that utilizes a memory to store usage history and view frequency data, determining the arrangement of advertisement information to display relevant and unviewed application function advertisements prominently, based on formulas that weight usage history and view frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If advertisements are displayed on the operation panel to recommend application functions, then user awareness of new functions is improved, but users are bothered by irrelevant or previously viewed advertisements
Solution Approach 1:
The system performs preliminary actions by storing usage history and advertisement viewing history before displaying advertisements. It calculates relevance scores based on past behavior patterns, ensuring that only relevant and unviewed advertisements are displayed, thereby preventing user annoyance while maintaining information relevance.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring user interactions with advertisements and updating the relevance calculation accordingly. When users view or interact with advertisements, this information is fed back into the system to refine future advertisement selections, ensuring ongoing relevance and reducing repetitive or irrelevant displays.
2Productivity
If advertisement arrangement is determined randomly or fixed, then system complexity is reduced, but advertisement effectiveness decreases
Solution Approach 1:
The system changes parameters by dynamically calculating relevance scores based on multiple variables including usage history, advertisement viewing history, and frequency metrics. This parameter-driven approach enables effective advertisement recommendation without requiring complex manual management, as the system automatically adjusts display priorities based on calculated scores.
Solution Approach 2:
The system performs self-service by automatically managing advertisement arrangement without requiring external intervention. It autonomously calculates relevance, determines display priorities, and adjusts advertisement presentation based on stored user behavior data, reducing the need for complex manual configuration while maintaining high recommendation effectiveness.
3Ease of operation
If all advertisements are displayed with equal prominence, then implementation is simple, but important advertisements are not highlighted
Solution Approach 1:
The system applies local quality by displaying advertisements with different levels of prominence based on their calculated relevance scores. High-scoring advertisements are displayed more prominently or frequently, while lower-scoring ones receive less emphasis. This differential treatment ensures important information stands out while maintaining relatively simple implementation through automated scoring.
Data Source
AI summary
An information processing apparatus includes a memory that stores a usage history of using an image forming apparatus by a user and a number of times of viewing report information by the user; and circuitry configured to determine an arrangement of the report information relating to a function of an application and display the report information, based on the usage history and the number of times of viewing the report information by the user.