Latent Semantic Analysis is a mathematical technique that uses Singular Value Decomposition ...

LDA is a Bayesian topic model that uncovers the latent structure of text. Instead ...

A document embedding is a fixed-length vector representation of an entire text — whether ...

A Sequence-to-Sequence (Seq2Seq) model is a neural network architecture designed to transform one sequence ...

Text classification is built on a pipeline of preprocessing, feature extraction, modeling, and evaluation. The most ...

Information Extraction transforms unstructured text into structured forms, enabling downstream reasoning. It includes:

Machine Translation is the process of converting text in one language into another while preserving meaning, ...

Text summarization aims to condense content while preserving meaning. Two broad categories exist:

Semantics focuses on how words and sentences convey meaning. But treating queries as static strings often ...

Traditional search models emphasize semantic similarity at the sentence or ...