latent semantic analysis

Terms from Artificial Intelligence: humans at the heart of algorithms

Page numbers are for draft copy at present; they will be replaced with correct numbers when final book is formatted. Chapter numbers are correct and will not change now.

Latent semantic analysis uses a latent space to find meaning or topics in a collection of texts that may not be those that would be explicitly described in tables of contents, or other human-structured lists. Latent semantic analysis is used in natural language processing and document retrieval. It typically starts with word-count data for each document and then craetes a reduced dimensional latent space. this similarity of between documents in this space can then be used for search or retrieval.

Used in Chap. 13: page 218