開催中止のお知らせ
新型コロナウイルスの感染が拡大し，関係する学会イベント等の中止が発表されていることなどを踏まえ，
2020年3月24日に開催を予定しておりました SIGIR 東京支部 2019年度 セミナー 3 を中止することを決定いたしました．
ご参加を予定されていた方には大変申し訳ございませんが，
ご理解くださいますようよろしくお願い申し上げます．
- 日時 / Date
- 2020年3月24日 10:30 - 11:30
- / March 24, 2020 10:30 - 11:30
- 場所 / Venue
- 筑波大学 東京キャンパス 文京校舎 321講義室
- / Room 321, Tokyo Campus, University of Tsukuba
事前登録不要、参加費無料
Task-Based Intelligent Retrieval and Recommendation
- 講演者 / Speaker
- Chirag Shah (University of Washington)
- 概要 / Abstract
-
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.
- 略歴 / Biography
-
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.
