Clustered Latent Semantic Indexing (CLSI)
Ali Baran Sari · 2004
The document retrieval method using latent semantic indexing (LSI) technique with truncated singular value decomposition (SVD) has been intensively studied in recent years. The SVD reduces the noise contained in the original representation of the term-document matrix and improves the information retrieval accuracy. However, SVD is mostly useful for small homogeneous data collections which means for large inhomogeneous data collection its performance is not good. To solve this problem we can first partition this large data collection into smaller ones with a document clustering algorithm and then apply the SVD.