Rucommender

Recommendation system written in Rust

Overview

An implementation in Rust of a collaborative filtering recommendations algorithm with a user-user similarity based on implicit ratings on the same items (e.g. both users clicked on the same item).

STATUS: This is project I'm using to learn some Rust and to reinforce my knowledge of recommender systems.

Getting Started

Pre-requisites

Rust and Cargo

Setting up

1. Fork and clone (or download)
2. cargo build

Usage

Inputs

1. CSV of implicit ratings by users on items, e.g.

   user_id,item_id
   1,100
   1,101
   2,100
   2,102
   

Outputs

Depends on command used:

• user->user similarity maps
• user->(item, score) recommendation maps

Examples

To spit out some similarities for a set of activities to make sure everything is working: cargo run --bin similarities < tests/fixtures/dummy/implicit-ratings.csv

To spit out some recommendations for a set of activities to make sure everything is working: cargo run --bin recommendations < tests/fixtures/dummy/implicit-ratings.csv

Tests

cargo test

Getting involved

Community

Ruccommender has a mailing list. Feel free to join it and ask any questions you may have.

Contributing

Contributions welcome. How? Fork and PR, I guess.