** Hamed Zamani, Research Scientist MSR AI **
Title: Towards Mixed-Initiative Conversational Search
Abstract: While conversational search has roots in early information retrieval research, recent advances in automatic speech recognition and conversational agents as well as popularity of devices with limited bandwidth interfaces have led to increasing interest in this area. An ideal conversational search system requires to go beyond the typical “query-response” paradigm by supporting mixed-initiative interactions. In this talk, I will review the recent efforts on developing mixed-initiative conversational search systems and draw connections with early work on interactive information retrieval. I will describe methods for generating and evaluating clarifying questions in response to search queries. I will further highlight the connections between conversational search and recommendation, and finish with a discussion on the next steps that require significant progress in the context of mixed-initiative conversational search.
Bio: Hamed is a Researcher at Microsoft AI Research, working on a wide range of information retrieval, natural language processing, and machine learning problems. Prior to Microsoft, he spent four years [masked]) at the Center for Intelligent Information Retrieval (CIIR), University of Massachusetts Amherst (UMass), where he was a Ph.D. Candidate under supervision of W. Bruce Croft. During his Ph.D., he completed three summer internships at Microsoft AI Research (2017, 2019) and Google Research (2016). He received his M.Sc. and B.Sc. degrees from University of Tehran.