Personalized Template Selection via User Edit History Analysis
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Solution Overview
Problem
Existing design creation systems fail to personalize templates for individual users based on their editing tendencies, leading to inefficient template selection and editing processes.
Innovation Solution
An information processing apparatus that stores multiple templates and acquires user-specific edit history information to output templates that align with the user's editing tendencies, allowing for personalized template customization and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If templates are provided in a standardized format without personalization, then the system structure remains simple and easy to manage, but the template selection accuracy and user satisfaction deteriorate due to lack of personalization
Solution Approach 1:
The system performs preliminary actions by acquiring and analyzing user edit history information before template selection. The management device stores edit history data and pre-processes it to identify user editing tendencies, so that when a template is needed, the system can quickly retrieve and apply the appropriate personalized template without requiring complex real-time analysis
Solution Approach 2:
The system implements feedback by using user edit history information to continuously improve template recommendations. The management device analyzes past editing patterns and feeds this information back into the template selection process, creating a closed-loop system that adapts to user preferences over time while maintaining a relatively simple overall structure
2Adaptability or versatility
If the system analyzes and stores detailed user edit history information, then personalized template recommendations improve, but the information processing complexity and storage requirements increase
Solution Approach 1:
The system extracts only the essential and useful information from user edit history data, specifically focusing on editing tendencies and patterns rather than storing and processing all raw editing details. This selective extraction approach enables personalization while keeping information processing complexity manageable by filtering out unnecessary data
Solution Approach 2:
The system applies different processing levels to different aspects of user data. Instead of uniformly analyzing all edit history information, it focuses specifically on extracting editing tendencies and patterns that are relevant to template selection, applying detailed analysis only where needed while keeping other aspects simpler
3Ease of operation
If multiple user-specific templates are generated and stored, then user experience and template relevance improve, but the storage space and data management requirements increase
Solution Approach 1:
The system creates templates that serve multiple functions: they are personalized to individual users based on their editing tendencies, yet they maintain consistency with the overall template library structure. Each user-specific template can be used both for immediate selection and as a basis for future personalizations, maximizing the utility of stored data while managing storage efficiency
Data Source
AI summary
An information processing apparatus includes: a memory that stores a plurality of templates which define different designs from each other with respect to a target object; an acquiring unit that acquires, for individual user, edit information indicating a history of editing performed by the user for the template; and an output unit that outputs information about the template that meets an editing tendency of the user for the template, for the individual user, the editing tendency being acquired from the edit information.