recommender systems nicole and kirstin - women@scsrecommender systems nicole and kirstin . what is a...
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Recommender systems
Nicole and Kirstin
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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.
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What would you want recommendations for?
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How do you make recommendations?
• Your friend is looking for a new book to read.
• How can a system make recommendations?
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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!
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Similar people have similar tastes!
Peggy
Christine
Collaborative Filtering (CF)
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People like related items!
Susan
Molly
Content-based filtering (CB)
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Let’s do an example together
Peggy
Christine
Brandon
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Peggy
Christine
Brandon
Ricky
Collaborative filtering looks at similar users
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Peggy
Christine
Brandon
Ricky
Content-based looks at the items themselves
Cartoons
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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!
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Should you recommend this?
Christine
Ricky
Sashank
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Should you recommend this?
Maria
Sue
Caitlin
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What should you recommend?
Nancy
Hannah
Priya
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Should you recommend this?
Nancy
Hannah
Priya
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How are these items and people related?
Michelle
Katy
Jan
Alice
Anjali
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Michelle
Katy
Jan
Alice
Anjali
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Alex
Simone
Gina
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Training Set
Sashank
Brandon
Maria
Christine
Susan
Jesse
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Test Case 1: Michelle
Michelle
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Test Case 2: Katy
Katy
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Test Case 3: Jan
Jan
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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.
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Netflix is mainly content-based
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Netflix attempted to get better algorithms…
But the winner turned out to be too complicated to practically use!
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Pandora is also content-based
“The Music Genome Project”
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Amazon uses both
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Where else could recommender systems be helpful?