The exponential growth of data demands scalable infrastructures capable of indexing and searching rich content such as text, music, and images. A promising direction is to combine...
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...
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...
In Latent Semantic Indexing (LSI), a collection of documents is often pre-processed to form a sparse term-document matrix, followed by a computation of a low-rank approximation to...
Latent Semantic Indexing (LSI) is an effective method to discover the underlying semantic structure of data. It has numerous applications in information retrieval and data mining....