In this paper we present a theoretical model for understanding the performance of Latent Semantic Indexing (LSI) search and retrieval applications. Many models for understanding L...
The aim of latent semantic indexing (LSI) is to uncover the relationships between terms, hidden concepts, and documents. LSI uses the matrix factorization technique known as singu...
Latent Semantic Indexing (LSI) is commonly used to match queries to documents in information retrieval applications. LSI has been shown to improve retrieval performance for some, ...
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...
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...