Presentation: Recommendations, Bots & Conversational Interfaces

Duration

Duration: 
5:25pm - 6:15pm

Persona:

Abstract

Smaller screens and conversational interfaces are now a reality. Recommendation and personalization are going to be key to make conversation interface a success. Traditionally recommendation systems are very important for web services like Amazon, Netflix, Facebook and LinkedIn for engaging users and discovering new content, products and connections.

This talk first describes how recommendation systems have evolved over time and how bots are emerging as a new form of delivering personalized recommendations. Next the talk will cover why bots are the new apps in conversational mediums such as messaging apps and devices like Amazon Echo. Finally, this talk will conclude with discussion on deep learning revolution that is making leaps and bounds progress in natural language processing and making conversational AI a reality.

Speaker: Mitul Tiwari

Worked on recommender systems such as People You May Know @LinkedIn

Mitul Tiwari is Cofounder and co-CTO of Rupert Labs. His expertise are in building data driven products using data science and big data technologies. Previously he was Engineering Manager and Staff Research Engineer at Search, Network, and Analytics group at LinkedIn, where led technical innovations in large-scale social recommender systems such as “People You May Know” and “Related Searches”. Before that, he worked at Kosmix (now Walmart Labs) as a Lead Member of Technical Staff, where he worked on web-scale document and query categorization, and its application to vertical search, personalized newspaper, and tweets classification. He earned his PhD in Computer Science from the University of Texas at Austin. Earlier he received his under graduation from Indian Institute of Technology, Bombay. His interests include natural language processing, data science, recommender systems, machine learning, and scalable systems. He has co-authored more than twenty publications in top conferences such as KDD, WWW, VLDB, SIGIR, CIKM, and SPAA.

Find Mitul Tiwari at

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