# What is the difference between Latent and Explicit Semantic Analysis

I'm not quite sure what "latent" refers to in this context.

''Our semantic analysis is explicit in the sense that we manipulate
manifest concepts grounded in human cognition, rather than
'latent concepts' used by Latent Semantic Analysis''.


What does that mean in simple terms?

I had a look at the related Wikipedia articles, ( Latent (wikipedia.org/wiki/Latent_semantic_analysis), Explicit wikipedia.org/wiki/Explicit_semantic_analysis) ), and I wasn't able to make heads or tails of it.

Perhaps someone with a better appreciate of the nuance involved here might be able to provide me with a clear indication of the similarities and differences, the pros and cons between these two methods for accessing document/text fragment relatedness to a particular concept.

 The name "explicit semantic analysis" contrasts with latent semantic analysis (LSA), because the use of a knowledge base makes it possible to assign human-readable labels to the concepts that make up the vector space.[3][1] 
References cited by Wikipedia for the quote above:  [1] Ofer Egozi, Shaul Markovitch and Evgeniy Gabrilovich (2011). "Concept-Based Information Retrieval using Explicit Semantic Analysis" (PDF). ACM Transactions on Information Systems 29 (2). Retrieved January 3, 2015.   [3] Gabrilovich, Evgeniy; Markovitch, Shaul (2007). Computing semantic relatedness using Wikipedia-based Explicit Semantic Analysis (PDF). Proc. 20th Int'l Joint Conf. on Artificial Intelligence (IJCAI). pp. 1606–1611.