Dynamic Reference List Prioritization via User Interest Detection
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Solution Overview
Problem
Users face difficulty in finding desired transaction objects from a large reference list, as existing methods do not effectively reflect user interest in the display order, leading to increased time and effort in accessing desired information.
Innovation Solution
An information processing apparatus that specifies user interest based on browsing history and displays relevant transaction objects more prominently, prioritizing recently browsed items and excluding those with short browsing periods, to enhance visibility and accessibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the reference list is arranged in the order of reference dates or reference frequencies or in alphabetical order, then the arrangement method is simple and easy to implement, but the display order does not reflect the user's current interest in the transaction objects, making it difficult for users to find desired items quickly
Solution Approach 1:
The reference list dynamically changes its arrangement order based on real-time user behavior. When a user views a transaction object, the system detects this action and automatically adjusts the display order to prioritize objects related to the viewed item, making the list adaptive rather than static
Solution Approach 2:
The system continuously monitors user viewing actions and uses this feedback to adjust the reference list arrangement. By detecting which transaction objects users view and calculating relationships between objects, the system dynamically reorders the list to reflect current user interests, creating a closed-loop feedback mechanism
2Quantity of substance
If the reference list contains a large number of transaction objects, then the reference list stores comprehensive information, but it costs more time and labor for the user to find a desired transaction object
Solution Approach 1:
The reference list is effectively segmented by prioritizing and highlighting objects related to currently viewed transaction objects. This creates a visual and positional segmentation that guides users to relevant items without requiring them to scan the entire list, thus managing large quantities of data efficiently
Solution Approach 2:
The system performs preliminary arrangement of the reference list by pre-calculating and positioning related transaction objects in prominent locations before users need to search. This proactive reorganization based on viewing history reduces the time users spend searching through large numbers of items
Data Source
AI summary
Provided is an apparatus and method which prioritizes transaction objects included on a reference list. The reference list contains transaction object information corresponding to the transaction objects. The apparatus stores a user's history of actions performed on the transaction objects and an interest parameter based on the user's history of actions. The interest parameter is used to select one or more transaction objects. The apparatus displays the reference list in an order prioritizing the selected transaction objects over non-selected transaction objects.


