With the development of the times, the gradual integration of Chinese and foreign civilizations and the continuous expansion of people’s living circles, the aesthetic consciousness of the interior space design of Chinese and Western residential buildings is also changing. The purpose of this article is to analyze the aesthetic differences between Chinese and Western cultures based on big data, analyze the clustering algorithms for aesthetic differences between Chinese and Western cultures, and conclude that different clustering algorithms have their own blind spots and misunderstandings for different data calculation processes. Aiming at the spatial distribution characteristics of aesthetic difference data between Chinese and Western cultures, an improved spectral clustering algorithm is proposed to better solve the problem of clustering and mining of aesthetic difference data between Chinese and Western cultures. The experimental results show that the fast clustering algorithm suitable for the aesthetic difference data sets of Chinese and Western cultures, the improved algorithm reduces the time of the traditional spectral clustering algorithm by 2%.