recommender systems nicole and kirstin - women@scsrecommender systems nicole and kirstin . what is a...

Recommender systems

Nicole and Kirstin

What is a recommender system?

• A system tries to predict if a user will like an item.

• The system recommends to a user items that it thinks the user will like.

What would you want recommendations for?

How do you make recommendations?

• Your friend is looking for a new book to read.

• How can a system make recommendations?

Two types of information can inform recommendations.

Similar people have similar tastes.

People like related items.

We liked Harry Potter—you’ll love it!

I like historical fiction!

I like fantasy!

Similar people have similar tastes!

Peggy

Christine

Collaborative Filtering (CF)

People like related items!

Susan

Molly

Content-based filtering (CB)

Let’s do an example together

Peggy

Christine

Brandon

Peggy

Christine

Brandon

Ricky

Collaborative filtering looks at similar users

Peggy

Christine

Brandon

Ricky

Content-based looks at the items themselves

Cartoons

Which do you think works better?

Collaborative filtering: Similar people have similar tastes.

Content-based filtering: People like related items.

We liked Harry Potter—you’ll love it!

I like historical fiction!

I like fantasy!

Should you recommend this?

Christine

Ricky

Sashank

Should you recommend this?

Maria

Sue

Caitlin

What should you recommend?

Nancy

Hannah

Priya

Should you recommend this?

Nancy

Hannah

Priya

How are these items and people related?

Michelle

Katy

Jan

Alice

Anjali

Michelle

Katy

Jan

Alice

Anjali

Alex

Simone

Gina

Training Set

Sashank

Brandon

Maria

Christine

Susan

Jesse

Test Case 1: Michelle

Michelle

Test Case 2: Katy

Katy

Test Case 3: Jan

Jan

How can you improve these systems?

• What were some downfalls of each method?

– Collaborative filtering

• Hard to answer when new person hasn’t seen/read/bought anything that other people have

– Content-based filtering

• Hard to answer when someone doesn’t have a clear profile of interests

• Hybrid approaches combine elements of both collaborative and content-based filtering.

Netflix is mainly content-based

Netflix attempted to get better algorithms…

But the winner turned out to be too complicated to practically use!

Pandora is also content-based

“The Music Genome Project”

Amazon uses both

Where else could recommender systems be helpful?