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Based on K-nearest neighbor algorithm, this study constructs a clustering model to mine advertising slogans in urban public space through feature extraction and analysis of different advertising slogans, aiming at identifying potential themes and styles of advertising slogans. The experimental results show that the model can effectively classify and aggregate similar advertising slogans. When K value is 5, the model performs best, and the accuracy rate is increased to 0.81, the accuracy rate is 0.84, the recall rate is 0.78, and the F1 score is 0.81, which provides data support for the advertising design and management of urban public space, and improves the advertising communication effect and citizen experience.

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Research on Public Space Slogan Clustering Model Based on K-NN Algorithm

  • 会议论文

  • 发表日期：

    2026年

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  • Hao Zhang

摘要

Based on K-nearest neighbor algorithm, this study constructs a clustering model to mine advertising slogans in urban public space through feature extraction and analysis of different advertising slogans, aiming at identifying potential themes and styles of advertising slogans. The experimental results show that the model can effectively classify and aggregate similar advertising slogans. When K value is 5, the model performs best, and the accuracy rate is increased to 0.81, the accuracy rate is 0.84, the recall rate is 0.78, and the F1 score is 0.81, which provides data support for the advertising design and management of urban public space, and improves the advertising communication effect and citizen experience.