Latent Semantic Indexing (LSI) has been shown to be effective in recovering from synonymy and polysemy in text retrieval applications. However, since LSI ignores class labels of t...
Sutanu Chakraborti, Rahman Mukras, Robert Lothian,...
Abstract – The method of latent semantic indexing (LSI) is well known for tackling the synonymy and polysemy problems in information retrieval. However, its performance can be ve...
Non-negative Matrix Factorization (NMF) and Probabilistic Latent Semantic Indexing (PLSI) have been successfully applied to document clustering recently. In this paper, we show th...
Dimension reduction techniques have been successfully applied to face recognition and text information retrieval. The process can be time-consuming when the data set is large. Thi...
Abstract. Latent Semantic Indexing(LSI) has been proved to be effective to capture the semantic structure of document collections. It is widely used in content-based text retrieval...