Geographic Area Identification Using User Behavior Data Analysis
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Solution Overview
Problem
Current methods for evaluating geographic areas in urban planning are general and subjective, failing to accurately consider population characteristics, leading to imprecise assessments.
Innovation Solution
A method and apparatus that acquire user information to determine characteristic data, including travel, basic, and preference parameters, using big data processing to analyze user behavior and quantify the value of a geographic area, enabling more precise identification of target areas for city planning and business decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current evaluation methods based on population size, construction state, and social factors are used, then the evaluation process is simple and easy to operate, but the measurement precision and accuracy of geographic area evaluation is insufficient
Solution Approach 1:
The patent changes the evaluation parameters from traditional static factors (population size, construction state, social factors) to dynamic user behavior parameters (travel characteristics, basic characteristics, preference characteristics). This parameter transformation enables more precise geographic area evaluation by capturing actual user patterns and preferences, thereby resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The patent replaces the traditional mechanical evaluation system (based on manual data collection and statistical analysis) with an automated big data processing system. By using computer algorithms to process user behavior data, locate information, and behavior information, the system achieves higher measurement precision while reducing the operational complexity through automation.
2Measurement precision
If user information and big data processing are used to determine characteristic data, then the identification accuracy of target geographic area is improved, but the processing time and computational resources increase
Solution Approach 1:
The patent segments the user information into three distinct characteristic data categories: travel characteristic parameters, basic characteristic parameters, and preference characteristic parameters. This segmentation allows for more efficient processing and analysis, as each category can be handled independently with appropriate algorithms, thereby reducing overall processing time while maintaining high identification accuracy.
Solution Approach 2:
The patent performs preliminary data processing and feature extraction before the main analysis. By pre-processing user information to extract characteristic data in advance, the system reduces the computational burden during the main geographic area identification process, thus decreasing processing time while preserving accuracy.
3Reliability
If traditional evaluation methods are used, then the implementation cost is low, but the reliability of evaluation results is insufficient due to subjective assessment
Solution Approach 1:
The patent incorporates feedback mechanisms by analyzing user behavior information and locating information to continuously refine the evaluation results. The system uses the actual user patterns and preferences as feedback to validate and adjust the geographic area identification, thereby significantly improving the reliability of evaluation results while managing data processing requirements through iterative refinement.
Data Source
AI summary
Embodiments of the disclosure provide a method and apparatus for identifying a target geographic area. In one embodiment, the method comprises acquiring user information associated with a geographic area to be identified; determining characteristic data of the user information; and determining a value parameter of the geographic area to be identified based on the characteristic data.