Figure 1
Flowchart outlining a four-step analytical process: Data Collection (Python Crawler, Jieba Participle, Disjunction, Data Cleaning) → Step 1 Dimensionality Transformation (K-means Clustering, Feature Extraction →Word Vector Embedding, Dimensional Clustering + Naming) → Step 2 Machine Learning Classification (validate dimension representativeness) → Step 3 Calculating Experience Utility → Step 4 Time Series Analysis (ARIMA quantitative testing, violin chart for dynamic trajectory visualization).

Research framework

Source: Authors’ own work

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