Information Processing Device Multi-Trait Service Determination
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Solution Overview
Problem
Conventional techniques fail to determine a service to be performed to a user based on multiple traits estimated from device operations or user behavior.
Innovation Solution
An information processing method that acquires action information from user device operations and behaviors, estimates multiple user traits, determines a service based on these traits, and outputs service information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional techniques are used to estimate user traits, then single-trait estimation is achieved, but multi-trait-based service determination is not possible
Solution Approach 1:
The patent segments user action information into multiple distinct traits (e.g., trait A, trait B, trait C) rather than estimating a single aggregated trait. Each trait is independently estimated from the same action information, allowing the system to capture different aspects of user behavior and preferences separately, enabling multi-trait-based service determination.
Solution Approach 2:
The patent transitions from single-trait estimation to multi-trait estimation by adding dimensional depth to the user profile. Instead of one-dimensional trait estimation, the system estimates multiple traits simultaneously, creating a multi-dimensional user characteristic space that enables more nuanced and adaptable service determination.
2Measurement precision
If action information is acquired from device operations and behaviors, then user trait estimation accuracy is improved, but service determination based on multiple traits cannot be performed
Solution Approach 1:
The patent merges multiple trait estimations into a unified service determination process. Instead of estimating traits separately and handling them independently, the system combines multiple trait estimates and their associated intensities into a single integrated framework that determines services based on the collective trait profile, achieving both accuracy and adaptability.
Solution Approach 2:
The patent creates a universal service determination framework that can handle multiple traits simultaneously. The determination part is designed to process any combination of estimated traits and their intensities, making the system multi-functional and adaptable to various service scenarios without requiring separate processing mechanisms for each trait.
3Adaptability or versatility
If multiple traits are estimated from action information, then service personalization is enhanced, but system complexity increases
Solution Approach 1:
The patent performs preliminary estimation of multiple traits and their intensities before the actual service determination process. By pre-calculating and storing trait estimates and intensity values, the system prepares user profiles in advance, reducing the computational complexity during the service determination phase and enabling efficient personalization when needed.
Solution Approach 2:
The patent introduces trait intensity as an intermediary element that mediates between raw action information and service determination. The intensity values serve as intermediate representations that simplify the relationship between multiple traits and service selection, reducing the complexity of the determination process by providing a standardized intermediate format for trait evaluation.
Data Source
AI summary
An information processing method by a computer includes acquiring action information indicative of at least one of a device operation and a behavior of a user, estimating a plurality of traits of the user on the basis of the action information, determining a service to be performed to the user on the basis of the traits, and outputting service information indicative of the service.