> For the complete documentation index, see [llms.txt](https://docs.exploratory.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.exploratory.io/statistics/sim.md).

# Cosine Similarity

## Introduction

Calculate cosine similarity of each of the pairs of categories. This is often used as similarity of documents.

## How to Access?

You can access from 'Add' (Plus) button.

![](/files/-M4oNDaJ-SzpC8OiNdjS)

## How to Use?

### Calculate Distances Among Categories

![](/files/-M4oNDaL7CxPGB0mkaUc)

#### Column Selection

Category, dimension and measure are like this.

![](/files/-M4oNDaNPjridRfO5eqE)

Category column is a column that has categories. They are parameterized by measures with the dimensions.

![](/files/-M4oNDaSq8iW09ffLg4h)

In this case, similarities of airline carriers are calculated based on count of flight. Think that each carrier is represented as a vector of flight count in each week day and cosine similarities of them are calculated.

If there are duplicated values, they will be aggregated by "Aggregate with".

### Parameters

* Keep Only Unique Pairs (Optional) - The default is FALSE. Whether the pair of output should be unique. If this is TRUE, a pair appears only once but if it's FALSE, a pair appears twice in swapped order. If you want to filter the pairs by names, it's better to be FALSE.
* Keep Diagonal Pairs (Optional) - The default is FALSE. Whether the output should contain the similarity of documents with itself.