Speaker: Jaime Teevan, Principal Researcher at Microsoft Research and affiliate faculty at the University of Washington
Time : Tuesday September 22, 2015 11:00 am-12:00 pm
Location: 3405 Siebel Center
Title: Slow Search: Improving Information Retrieval Using Human Assistance
Abstract: We live in a world where the pace of everything from communication to transportation is getting faster. In recent years a number of “slow movements” have emerged that advocate for reducing speed in exchange for increasing quality. These include the slow food movement, slow parenting, slow travel, and even slow science. We propose the concept of “slow search,” where search engines use additional time to provide a higher quality search experience than is possible given conventional time constraints. While additional time can be used to identify particularly relevant results within the existing search engine framework, it can also be used to create new search artifacts and enable previously unimaginable user experiences. In this talk I focus on how search engines can make use of additional time to employ a resource that is inherently slow: people. Using crowdsourcing and friendsourcing, I will highlight opportunities for search systems to support new search experiences with high quality result content that takes time to identify.
Bio: Jaime Teevan is a Principal Researcher at Microsoft Research and affiliate faculty at the University of Washington. Working at the intersection of human computer interaction, information retrieval, and social media, she studies people’s information seeking activities. Much of her research focuses on the social and temporal context of information use, and she developed the first personalized search algorithm used by Bing. Her accomplishments have been honored with Technology Review (TR35) Young Innovator and Borg Early Career awards. She has published numerous technical articles, including several books and best papers, and given keynotes at CIKM, UMAP and Web Science. Jaime received a Ph.D. from MIT and a B.S. in Computer Science from Yale University.