Statistical Amount Selection for User Priority in Information Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for prioritizing and displaying activities of other users in social services, such as timelines or news feeds, fail to effectively manage large volumes of information and do not provide a clear method for setting priorities based on user-specific features, making it difficult to preferentially view users with specific features or information.
Innovation Solution
An information processing apparatus and method that selects statistical amounts showing user features, sets priorities based on these amounts, and controls the display of users or information using a priority setting unit and display control unit, allowing for the preferential viewing of users with specific features by adjusting display order, size, and prominence based on calculated priorities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the number of followed users increases to provide more social connections, then the quantity of user information increases, but the information becomes difficult to read and manage
Solution Approach 1:
The patent segments user information by introducing multiple statistical dimensions (activity frequency, interaction depth, content quality metrics) to categorize and prioritize users. This segmentation allows the system to divide the large volume of user data into manageable priority groups, making it easier to read and navigate without being overwhelmed by the total quantity of information
Solution Approach 2:
The patent changes the parameters used to evaluate and sort user information by introducing multiple statistical amounts that quantify different aspects of user activity and relationship strength. By changing from simple chronological or alphabetical sorting to multi-parameter statistical evaluation, the system transforms the presentation of large quantities of user data into a more readable and manageable format
2Extent of automation
If general recommendation methods are applied to user activities, then information provision can be automated, but user-specific features cannot be effectively prioritized
Solution Approach 1:
The patent applies local quality by calculating distinct statistical amounts for different aspects of user interaction (activity frequency, interaction depth, content quality) rather than using a single general metric. This allows the automated system to precisely identify and prioritize specific user features locally, improving measurement precision while maintaining automation
Solution Approach 2:
The patent changes the parameters of automated recommendation by introducing multiple statistical dimensions that specifically measure user features and interaction qualities. This transforms general automated information provision into a precision-oriented system that can accurately identify and prioritize users with specific features through multi-parameter evaluation
Data Source
AI summary
There is provided an information processing apparatus including a statistical amount selecting unit that selects, from a plurality of statistical amounts showing features of users, a statistical amount to be used based on distribution of each of the statistical amounts, a priority setting unit that sets priorities of a plurality of users, based on the selected statistical amount, and a display control unit that controls display of the plurality of users or a plurality of pieces of information from the plurality of users, based on the set priorities.