The core of server cache performance is the cache replacement strategy which directly affects the cache hit ratio. Web cache can solve the problems of network congestion and user access delay and improve server performance. A multi-cache replacement strategy based on spectral clustering is proposed because of the low cache hit ratio of traditional cache replacement algorithms. The strategy uses the circular sliding window mechanism to extract multiple temporal features and access attributes of log files and conducts cluster analysis on the filtered data set through spectral clustering to obtain access prediction results. Multi-cache replacement strategy takes into account the local frequency, global frequency, and resource size of the cache object to eliminate the low-value resources and retain the high-value resources. In comparison with traditional replacement algorithms such as LRU, LFU, RC, and FIFO, the experimental results show that the combination of spectral clustering and multi-cache replacement strategy in this study can effectively improve the cache request hit ratio and byte hit ratio.