Mukund Narasimhan, Engineer, Pinterest at MLconf Seattle 2017
Mukund Narasimhan is an engineer at Pinterest where he works on content modeling and recommendations. Prior to Pinterest, he has worked at Google, Facebook, Microsoft and Intel. He has a Ph.D. in Electrical Engineering from the University of Washington and a M.S in Mathematics from Louisiana State University.
Knowledge at Pinterest:
Pinterest is building the world’s largest catalog of ideas. These ideas are embodied in billions of Pins and well over 100 million Users and Boards which, together, form a complex picture of our users and their interests. The goal of the Knowledge team is to leverage our unstructured data (images, videos, and text), and structured data (user curated data, partner generated content, and engagement signals) to model users and their interests so we can help them discover fresh, diverse, and personalized new ideas. In this talk, we go into some detail on the progress we’ve made so far.
where content = Pin description, title of boards contained with the Pin, etc.
Original Word2Vec Inferred User Interests
Container Sentence Pin
Item Word Content: word in content associated with Pin
Context Surrounding words Other content: other words in content associated with Pin
• On the same side: set bit to 1
• On diﬀerent sides: set bit to 0
Result 1: 110
Result 1: 110
Result 2: 101