# Kithra: People like you liked these

> Item-item CF, the approach Amazon scaled: cosine/Pearson similarity over a ratings matrix, then a k-nearest similarity-weighted prediction. No training - just similarity and a weighted mean. 13 tests, including the full “fan of Inception → Interstellar” scenario and an honest cold-start.

Kithra is a recommendation engine built on item-item collaborative filtering, the approach Amazon scaled to production. The signature technique computes cosine or Pearson similarity over a ratings matrix and then makes a k-nearest, similarity-weighted prediction - no training, just similarity and a weighted mean - tested with the full "fan of Inception leads to Interstellar" scenario and an honest cold-start case. It is a from-scratch, dependency-light build you can download and run locally.

## About the app

Collaborative filtering

## What to take away

- Item-item CF, the approach Amazon scaled: cosine/Pearson similarity over a ratings matrix, then a k-nearest similarity-weighted prediction. No training - just similarity and a weighted mean. 13 tests, including the full “fan of Inception → Interstellar” scenario and an honest cold-start.
- Download: Kithra (ZIP)

## Tags

Free software, Kithra

## Read the full write-up

/downloads/kithra.zip

## We build this for clients

https://dfieldsolutions.com/en/services/full-stack

## More from the lab

- https://dfieldsolutions.com/en/lab/sylex.md — Sylex: Make sense of the slashes
- https://dfieldsolutions.com/en/lab/kindra.md — Kindra: Miss a beat, not the rhythm
- https://dfieldsolutions.com/en/lab/voxara.md — Voxara: Argue better. Lose gracefully
- https://dfieldsolutions.com/en/lab/wraithward.md — Wraithward: Spot the bait before you bite

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Source: https://dfieldsolutions.com/en/lab/kithra
DField Solutions — Torony köz 5-1.a, 2120 Dunakeszi, Hungary — +36 20 722 0002 — dezso@dfieldsolutions.com
Booking: see https://dfieldsolutions.com/en/contact