Emerging as this year’s winner from a very strong field of nominations we are pleased to announce that the Microsoft BCS/BCS IRSG Karen Spärck Jones Award 2019 is to be awarded to:
Dr. Chirag Shah
Associate Professor in the Information School (iSchool) at the University of Washington
Task-Based Intelligent Retrieval and Recommendation
While the act of looking for information happens within a context of a task from the user side, most search and recommendation systems focus on user actions (‘what’), ignoring the nature of the task that covers the process (‘how’) and user intent (‘why’). For long, scholars have argued that IR systems should help users accomplish their tasks and not just fulfill a search request. But just as keywords have been good enough approximators for information need, satisfying a set of search requests has been deemed to be good enough to address the task. However, with changing user behaviors and search modalities, specifically found in conversational interfaces, the challenge and opportunity to focus on task have become critically important and central to IR. In this talk, I will discuss some of the key ideas and recent works — both theoretical and empirical — to study and support aspects of task. I will show how we could derive user’s search path or strategy and intentions, and how they could be instrumental in not only creating more personalized search and recommendation solutions, but also solving problems not possible otherwise. Finally, I will extend this to the realm of intelligent assistants with our recent work in a new area called Information Fostering, where our knowledge of the user and the task can help us address another classical problem in IR — people don’t know what they don’t know.
Chirag Shah is an Associate Professor in Information School (iSchool) at University of Washington (UW) in Seattle. Before UW, he was a faculty at Rutgers University. His research interests include studies of interactive information retrieval/seeking, trying to understand the task a person is doing and providing proactive recommendations. Dr. Shah received his MS in Computer Science from University of Massachusetts (UMass) at Amherst, and PhD in Information Science from University of North Carolina (UNC) at Chapel Hill. He directs the InfoSeeking Lab where he investigates issues related to information seeking, human-computer interaction (HCI), and fairness in machine learning, supported by grants from National Science Foundation (NSF), National Institute of Health (NIH), Institute of Museum and Library Services (IMLS), Amazon, Google, and Yahoo.