Jaime Teevan is a Senior Researcher at Microsoft Research and an Affiliate Assistant Professor 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 honoured with Technology Review (TR35) Young Innovator and Borg Early Career awards.
She has published numerous technical articles, including several books and best papers. She received a Ph.D. from MIT and a B.S. in Computer Science from Yale University.
The Complicated Task of Making Search SimpleInvited Speaker Name: Dr. Jaime Teevan
Affiliation: Microsoft Research and the University of Washington
The interface to most web search engines is simple. A user enters a few words into a search box and receives a long list of results in return. But despite the simplicity of the interaction, people use search engines for many complex tasks; they conduct research, plan trips, entertain themselves, purchase items, and find new jobs, all via web search. The challenge for a search engine is to translate a person's simple, short query into a list of documents that satisfy their different information needs.
It is unlikely that a typical two- or three-word query alone can unambiguously describe a user's underlying informational goal. For example, a web search for "UMAP" returns a wide range of results, including the University of Utah campus map, a journal focused on Undergraduate Mathematics, webpages associated with various chapters of the United Methodist Association of Preschools, and a few results about User Modeling, Adaption, and Personalization. Although each of these results is relevant to someone who issues the query "UMAP," attendees of UMAP 2015 are probably uninterested in most of the content.
However, rich information or context about the user, the corpus, and the task the user is engaged in can enable a search engine to do a better job of finding relevant information, even for simple queries. In the "UMAP" case, if the search engine were aware of the fact that the searcher had previously been to the http://umap2015.com homepage, it could focus its efforts on identifying results related to user modeling. This talk will explore how to build rich models of user interests from search-related behavioral information, and provide examples of how these models can be used to improve the web search experience.
Ed H. Chi is a Research Scientist at Google. Previously, he was the Area Manager and a Principal Scientist at Palo Alto Research Center's Augmented Social Cognition Group. He led the group in understanding how Web2.0 and Social Computing systems help groups of people to remember, think and reason. Ed completed his three degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and has been doing research on user interface software systems since 1993. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press. With 20 patents and over 90 research articles, his most well-known past project is the study of Information Scent --- understanding how users navigate and understand the Web and information environments. He also led a group of researchers at PARC to understand the underlying mechanisms in online social systems such as Wikipedia and social tagging sites. He has also worked on information visualization, computational molecular biology, ubicomp, and recommendation/search engines, and has won awards for both teaching and research. In his spare time, Ed is an avid Taekwondo martial artist, photographer, and snowboarder.
User Modeling and the Blurring of the Boundary Between Interactive Search and RecommendationInvited Speaker Name: Dr. Ed H. Chi
Affiliation: Google Research
Search and recommendation engines have become more personalized and social as well as more interactive. No longer just offering ten blue links, search engines have increasingly been integrated with task and item recommenders directly, for example, to offer news, movie, music, and dining suggestions. And vice versa, recommendation systems have increasingly become more search-like by offering capabilities that enable users to tune and direct recommendation results instantly.
As the two sets of technologies evolve toward each other, there is increasingly a blurring of the boundary between these two approaches to interactive information seeking. This blurring has resulted in both critical re-thinking about not just how to architect the systems by merging and sharing backend components common to both types of systems, but also how to structure the user interactions and experiences.
Importantly, the nexus at the center of these boundaries is the critical component of User Modeling and Personalization, which is critical to the movement toward personal assistants and personalized proactive recommenders. Recent advances such as tensor factorization promise to greatly improve user model and recommendations.
In this talk, I will illustrate this blurring boundary with systems we have built over the last decade, as well as discuss the lessons we learned from evaluating these systems.
Dr Eoin O'Dell is an Associate Professor of Law and Chair of the Fellows in Trinity College Dublin. He researches and publishes primarily in the fields of freedom of expression, and private and commercial law - and especially where they overlap in IP, IT and cyberlaw. He has been been President of the Irish Association of Law Teachers, a Member of the Council and Executive of the Society of Legal Scholars in the UK and Ireland, and Editor of the Dublin University Law Journal. He was a member of the group which advised the Department of Justice on the Defamation Act, 2009; he was a member of the Advisory Group on a European Civil Code which advised the EU Commission on common principles of European private law; and he is a member of the Statute Law Revision Committee advising the Department of Public Service and Reform on the process of revising the Irish Statute Book. He was Chair of the Copyright Review Group which presented its final report to the Minister for Jobs, Enterprise and Innovation in October 2013. He blogs at http://www.cearta.ie and tweets @cearta
Privacy Paradigm – Towards a Creative Commons for PrivacyInvited Speaker Name: Dr. Eoin O'Dell
Affiliation: School of Law, Trinity College Dublin
Online privacy is in decline. This talk will examine what we can do about it, not only from regulation by the Irish Data Protection Commissioners (which is now the governing data protection body for companies such as Twitter) to individual court cases, but also from protecting our own privacy to respecting the privacy of others. In the latter context, this talk will tease out what a Privacy Paradigm, a Creative Commons for Privacy, might look like and what it could do.
Where Creative Commons provide standard-form copyright licences, Privacy Paradigm would provide standard-form privacy policies. And where the Creative Commons licences reflect general principles of copyright law, the Privacy Paradigm privacy policies would reflect general principles of privacy law. Hence, Privacy Paradigm would provide a means by which content and service providers could signal not only that they respect your privacy when you use their website but also how (if at all) their site processes personal data.
This talk will discuss the evolving privacy landscape in the context of user modelling and personalisation, advocating the potential of Privacy Paradigm as a mechanism to inform users of how their personal information will be processed and used.