# Vector Space Models

A **vector space model** is a computational framework to represent text documents as vectors in a high-dimensional space such that each document is represented as a vector, and each dimension of the vector corresponds to a particular term in the vocabulary.

## Contents

* [Bag-of-Words Model](https://emory.gitbook.io/nlp-essentials/vector-space-models/bag-of-words-model)
* [Term Weighting](https://emory.gitbook.io/nlp-essentials/vector-space-models/term-weighting)
* [Similarity Metrics](https://emory.gitbook.io/nlp-essentials/vector-space-models/document-similarity)
* [Document Classification](https://emory.gitbook.io/nlp-essentials/vector-space-models/document-classification)
* [Homework](https://emory.gitbook.io/nlp-essentials/vector-space-models/homework)