AI Goal Classifier for Behavioral Data Segmentation
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Solution Overview
Problem
Classifying user goals based on subjective extrinsic criteria, such as importance, can be challenging due to the variability in human perceptions and behaviors.
Innovation Solution
An apparatus and method utilizing a processor and memory to receive user goal data, classify it using a trained goal classifier, and generate a goal path divided into waypoints, incorporating machine learning models and fuzzy inference systems to assign and rank user goals based on behavioral parameters and survey data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If subjective extrinsic criteria are used to classify user goals, then the classification reflects human perceptions and behaviors, but the variability in human perceptions makes accurate classification difficult
Solution Approach 1:
The patent introduces an artificial intelligence classifier as an intermediary between subjective human perceptions and objective classification results. The AI model processes behavioral parameters and survey data through learned patterns, mediating the translation of subjective goal importance into structured classifications while reducing variability in human judgment
Solution Approach 2:
The system implements feedback mechanisms where the AI classifier continuously learns from user interactions and goal outcomes. By incorporating feedback loops that refine classification based on actual user behavior patterns and goal achievement data, the system improves classification accuracy while maintaining adaptability to individual human perceptions
2Reliability
If a comprehensive goal classification system is developed using multiple behavioral parameters, then the system can effectively categorize and prioritize goals, but the complexity of the system increases
Solution Approach 1:
The patent segments the goal classification system into distinct functional modules: data collection components that gather behavioral parameters and survey data, an AI classification engine that processes the data, and output components that generate prioritized goal lists. This segmentation allows each module to be optimized independently while maintaining overall system reliability
Solution Approach 2:
The AI classifier is designed as a universal component that handles multiple types of behavioral parameters and survey data through a single integrated model. This multi-functional approach reduces system complexity by eliminating the need for separate classification algorithms for different data types, while maintaining reliable categorization across diverse goal domains
Data Source
AI summary
An apparatus for goal generation is disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive a goal datum related to a user, wherein the goal datum comprises behavioral parameters. The memory additionally instructs the processor to classify the goal datum to a user goal. The classification comprises training a goal classifier using a goal training data. Goal training data contains a plurality of data entries containing a plurality of goal datum inputs correlated to a plurality of goal outputs. The classification also comprises classifying the goal datum to the goal using the goal classifier. The classifier assigns the goal as a function of the classification. A goal path is generated as a function of the classification of the goal datum to a goal, wherein the goal path is divided into waypoints.