The Movie Genome

The Movie Genome Project

Is it possible to love The Usual Suspects and hate Se7en? Glance at keywords and genres, and they look nearly identical. Both are Crime thrillers, starring Kevin Spacey, flagged for violence. Of course, one is a witty cons and scams story with a surprise twist, and the other is a disturbing, gory morality tale about a serial killer. But you've got to look inside the movies to see that.

Taste in movies is complex and unique. Yet the usual way of cataloging movies, by titles, people, and genres, flattens all this - as if you'd like a movie just because it's a Drama or stars Vince Vaughn. That's why our team of movie and TV experts created the Movie Genome, an ambitious, ongoing project with the Jinni community to map more aspects of movies, shows, and semi-professional videos than ever before - so that all different viewers can match their personal tastes and moods, and find what they really want to watch next. The Movie Genome powers the search, recommendations, Taste Types and more on Jinni.

How It Works

Inside, the Genome is broadly divided in two: Experience - the mood and tone of the content - and Story - plot elements (One man army, Battle of the sexes), structures (Nonlinear, Story-within-a-story), flags (Violence, Nudity) and more. The Genome also includes many external aspects like awards.

The starting point of the Movie Genome is manual tagging by our team of film professionals. Each title has around fifty genes, among thousands of possibilities. Then, using advanced machine-learning technology, Jinni's system learns from the manual tagging to begin automated tagging. This creates a level of consistency that creative human taggers can't reach - especially important for similarity matches and recommendations, which won't work unless you compare apples to apples and battles to battles as often as possible. Users who vote on genes, as well as the Jinni team, constantly check and improve the machine tagging.

Recommendations

We think the best recommendations use man and machine. A machine can deeply analyze the type of content you like to learn about your unique taste. People can share their personal favorites and opinions about what they've seen (in a way no machine can do, as yet). Jinni isn't a social network, it's a service meant to fit how people experience media - and we've included dialogue about movies and shows as part of that.

Jinni recommends by comparing your Taste Types and the genes of all the titles in our catalogue, figuring in your preferences (movies or TV, in theaters or online) and some other filters. Simplistically, if you have the genes for Gloomy Love Triangles, we'll recommend titles with those dominant genes. As a user, you receive recommendations from Jinni, your Movie Circle, your Neighbors (people Jinni identifies as having taste similar to yours), and your Groups.

Your Taste Types

Jinni assigns a set of genes to each user, drawn from aspects of the content you like. These genes, along with some other measures, are continually adjusted as we learn from your ratings, reviews, and other actions on the website. The Taste Types look at the characteristic attitudes and preferences that attract viewers to different types of movies. Since people usually like a variety of movies, Jinni uses a combination of Taste Types to describe your taste.

Wiki - Coming Soon

Our vision of the Wiki is a constantly evolving dictionary of genes that describes numerous aspects of video, where users can shape the Movie Genome Project by discussing and editing definitions, voting on genes, and more.