advisor: prof. steven weber ganesh iyer, goutam murlidhar ... · model and computation quality of...
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Ganesh Iyer, Goutam Murlidhar, Hadrien RenoldAdvisor: Prof. Steven Weber
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“.. often I feel I just want to get it
over with and end up with
something I don't really love.”
“I feel bad when I spend all day
shopping but didn't find
anything I like”
“.. need confidence or other
opinions in what I'm getting for
myself”
“I need to consider what I
already own”
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strategic choice
a user needs information on what she already owns
a user needs to know what goes well together
a user needs to know what they would or wouldn’t regret buying
query an eventual candidate
evaluate a clothing item in isolation
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Optimize your clothing purchases
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the anti-search
conventional
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locking an item
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How versatile is this item I am about to buy?
How versatile is this item with the general idea of
my wardrobe?
I own something similar already; what are the
other things that go with it?
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generating outfits
● large scale dataset of user interactions with the inventory
● extract image features
● extract items relationship
● learn abstract concept of style
● define outfits:
○ Men: 'Pants', 'Shirts', 'Shoes'
○ Women: ‘Accessories', ''Shoes', 'Dresses' OR
○ Women: ‘Accessories', 'Pants', 'Tops & Tees', 'Shoes'
● integrates into merchants’ inventories
McAuley, Julian, et al. "Image-based recommendations on styles and substitutes." Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval. ACM, 2015
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feedback on the outfits
● How do we get feedback on algorithm performance
● Splitting between liked outfits and outfits from the algorithm
● How to prevent cycling through only liked outfits
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challenges
Data cleaning and potentially flawed outfits
Quality of images and UXModel and computation
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conclusion + future vision
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fin