Information Processing System for User Feature Identification
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Solution Overview
Problem
Conventional analysis technologies are unable to identify user features based on the registration of related information in social media, particularly distinguishing between users who register information during a groundswell of interest and those who do so after the peak has passed.
Innovation Solution
An information processing system that includes a value identifying unit to determine the level of interest, a period identifying unit to identify when the interest grows over time, and a feature identifying unit to characterize users based on their registration patterns, specifically analyzing the number of posts or social bookmarks per unit time and keyword usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional analysis technology is used to analyze social media registration data, then basic data processing can be performed, but user features cannot be identified based on registration timing relative to interest groundswell periods
Solution Approach 1:
The patent segments the analysis process into three distinct functional units: a value identifying unit that determines interest groundswell levels, a period identifying unit that detects growth periods, and a feature identifying unit that characterizes users based on registration timing. This segmentation enables precise user feature identification while maintaining modular system complexity management.
Solution Approach 2:
The patent performs preliminary identification of interest groundswell values and growth periods before analyzing user registration patterns. By pre-establishing the temporal context of interest fluctuations, the system can accurately classify users based on their registration timing relative to these pre-identified periods, improving measurement precision without proportionally increasing complexity.
2Measurement precision
If detailed analysis of registration timing is performed to identify user features, then user characterization accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system pre-identifies interest groundswell values and growth periods before user feature analysis. This preliminary action creates a ready reference framework that allows rapid classification of users based on their registration timing, reducing the computational burden during actual user analysis while maintaining high accuracy.
Solution Approach 2:
By dividing the analysis into separate functional units that operate independently, the system can process different aspects of user behavior in parallel or staged manner. The value identifying unit, period identifying unit, and feature identifying unit can be executed sequentially with optimized resource allocation, reducing overall processing time while maintaining precision.
Data Source
AI summary
A cluster value identifying unit identifies a value of a parameter representing a level of a ground swell of interest related to provided information, which is determined in accordance with registration of information related to the provided information. A period identifying unit identifies, based on the value of the parameter, a period in which the ground swell of interest related to the provided information grows with a lapse of time. A user feature identifying unit identifies, based on the identified period, a feature of a user who registers the related information. Accordingly, the feature of the user may be identified based on the registration of the information related to the provided information.