Visual Explanation of Mathematics in Latent Semantic Analysis
Yukari Shirota, Basabi Chakraborty · 2015
Latent Semantic Analysis (LSA) is a widely used method in text mining fields to extract the latent concept. The mathematical technique behind LSA is Singular Value Decomposition (SVD) in which the key concept is the eigen values. It is difficult to understand the underlying mathematics for general people, not proficient in mathematics. One reason might be that the linear algebra textbooks available in the market are not written for non - mathematics majors. We have proposed a visualization of the mathematical process behind LSA to make it easily understandable to people, novice in mathematics. In this paper, we proposed visualization of the eigen values and eigenvectors.