Goal Management System Using Linguistic Analysis for Quantitative Conversion
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Solution Overview
Problem
Existing goal management systems require users to input quantitative numerical values for body-related goals, which can be cumbersome and may not accurately reflect the user's objectives.
Innovation Solution
A goal management system that includes a reception unit for qualitative goal input, an identification unit to convert this input into a quantitative goal through linguistic analysis, and a presentation unit to display the quantitative goal, allowing users to set body-related goals without direct numerical input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users input quantitative numerical values for body-related goals, then the goal management system can track and measure progress accurately, but the operation becomes cumbersome and may not accurately reflect the user's true objectives
Solution Approach 1:
The patent introduces a natural language processing intermediary that translates between qualitative user expressions and quantitative goal parameters. The system includes a goal setting module that accepts natural language input and converts it into structured quantitative goals, and a goal analysis module that interprets qualitative feedback into measurable progress indicators. This intermediary layer resolves the contradiction by maintaining measurement precision through automated conversion while preserving ease of operation through natural language interaction.
Solution Approach 2:
The patent replaces the mechanical system of manual numerical input with an automated linguistic analysis system. Instead of requiring users to manually enter quantitative values, the system uses natural language processing, semantic analysis, and automated reasoning to extract and convert quantitative parameters from qualitative expressions. This substitution eliminates the cumbersome input process while maintaining accurate goal measurement through computational linguistics and data processing.
2Measurement precision
If the system requires accurate quantitative input from users, then goal tracking precision is improved, but the complexity of the system increases as users must understand and input multiple body parameters
Solution Approach 1:
The patent implements self-service functionality where the system automatically performs goal parameter extraction, validation, and conversion without requiring users to manually configure multiple parameters. The goal setting module automatically identifies relevant body parameters from natural language input, determines appropriate target values, and structures the goals. The system also self-adjusts by learning from user feedback and refining its parameter extraction algorithms, thereby maintaining high measurement precision while reducing operational complexity.
Solution Approach 2:
The patent creates a universal goal management system that handles multiple types of body-related goals (weight management, fitness, health metrics) through a single integrated platform. The system uses a unified natural language processing framework that can interpret various qualitative expressions and convert them into appropriate quantitative parameters across different goal domains. This multi-functionality reduces complexity by providing a consistent interface for diverse goal types while maintaining precision through domain-specific parameter extraction rules.
3Adaptability or versatility
If users must determine achievable quantitative goals independently, then personalization is improved, but the time and effort required for goal setting increases
Solution Approach 1:
The patent implements feedback mechanisms where the system analyzes user characteristics, historical data, and progress patterns to provide personalized goal recommendations. The goal analysis module continuously monitors user performance and adjusts goal parameters to ensure they remain achievable and personalized. This feedback loop enables the system to automatically tailor goals to individual user capabilities and aspirations, maintaining high personalization while reducing the time users spend on goal determination through automated analysis and recommendation.
Solution Approach 2:
The patent performs preliminary analysis of user characteristics, body parameters, and goal preferences before final goal setting. The system pre-processes user data, identifies relevant parameters, and generates preliminary goal recommendations that users can review and confirm. This preliminary action reduces the time required for final goal determination by having the system perform the complex analysis work in advance, while still maintaining personalization through user-specific data processing and customized recommendation generation.
Data Source
AI summary
A goal management system receives input of a qualitative first goal related to a body of a user (step S111), identifies a quantitative second goal related to the body of the user from the first goal thus received (step S112 to step S117), and presents the second goal thus identified (step S118). The first goal is converted into the quantitative goal for at least one of a plurality of feature amounts related to the body, thereby identifying the second goal including at least one goal obtained by such conversion. The first goal is converted into the quantitative goal for each feature amount corresponding to a meaning obtained by linguistic analysis. When there are a plurality of meanings obtained by linguistic analysis of the first goal, the first goal is converted into the quantitative goal for each feature amount on the basis of a range of each feature amount per meaning. This makes it possible to indicate a quantitative goal related to the body without receiving input of a goal that is a quantitative numerical value related to the body.