A new web document automatic classification algorithm based on Latent Semantic Indexing (LSIWAC), is proposed in this paper. LSIWAC uses the LSI based on Singular Value Decomposition (SVD) to compress the document vector space to lower dimensional space. Using the optimal clustering, LSIWAC can cluster part of web documents. Then, LSIWAC uses the optimal discriminate transform to get feature vector from every clustering's discriminate features. Finally, it uses the conception classification algorithm to classify the rest documents. LSIWAC solves the high dimension problem and improves the precision of web classification.