Speaker: Filip Radlinski, Google
Talk Title: Challenges with Really Understanding Natural Language in Conversational Recommendation
Date: Friday. December 17, 2021 - 1:30 - 2:30 PM EST (North American Eastern Standard Time) via Zoom
Zoom Access: Zoom Link and reach out to Alex Taubman for the passcode.
Abstract: Conversational interaction with recommender systems has become increasingly common, yet the language of the interaction is often still constrained. In this talk, I will describe recent work aimed at increasing the sophistication and naturalness of conversations with state of the art recommenders. Considering three aspects of conversational recommendation, I will describe methods improving the vocabulary understood by systems, as well as the reliability of interpretation of users’ answers to questions asked by a system. Further, I will show how a system employing richer natural language can provide users more control over, and improved understanding of the recommendation process.
Bio:
Filip Radlinski is a Research Scientist at Google, UK. His research focuses on improvements to conversational search and recommendation through better understanding and modeling user interests through natural language, improved transparency of conversational systems, as well as human-centered evaluation and personalization of information retrieval and recommendation tasks. He received his PhD from Cornell University.