Furniture Style Clustering

Combined with the images of furniture styles selected and processed in Section 4.1, the experts were invited again to score the 108 styles. For common styling terms, 1 point was added; for less common terms, the score was 0.

The accumulated scores for the 108 different styling terms reflect the popularity or market performance of each style. By analyzing the score data, the K-means clustering method was used to effectively classify different styles. K-means is a clustering method based on distance metrics, aiming to minimize the squared distance from each sample point to its cluster center.