Sunday August 6, 2006, schedule
08:00 - 18:00 Conference Registration open
08:30 - 12:15 Tutorials - Morning
- Conducting Interactive IR User Studies
Diane Kelly; David Harper - The Study and Practice of Personal Information Management
William Jones; Jacek Gwizdka - Introduction to Web IR
Ricardo Baeza-Yates; Andrei Broder; Prabhakar Raghaven - Statistical Language Models for IR
ChenXiang Zhai - Machine Learning for IR
Yi Zhang; Rong Jin
12:15 - 13:15 Lunch
13:15 - 17:00 Tutorials - Afternoon
- Conducting Interactive IR User Studies (continued)
Diane Kelly; David Harper - The Study and Practice of Personal Information Management
(continued)
William Jones; Jacek Gwizdka - Introduction to Web Advertising
Andrei Broder; Prabhakar Raghaven - Using the Lemur Toolkit for IR
Trovor Strohman; Paul Ogilvie - XML Information Retrieval
Mounia Lalmas; Ricardo Baeza-Yates
Morning & Afternoon
Conducting Interactive Information Retrieval User Studies – Level: Introductory. One full day.
This tutorial will familiarize participants with major elements of user studies as they are conducted in interactive information retrieval, and provide a foundation for them to conduct these studies successfully. Discussion points include: experimental design, selection of tasks and corpus, identification and articulation of measures, and collection and analysis of data. Two example studies will be presented and analyzed in detail. It concludes with an overview of emerging and future developments. It is appropriate for students and researchers at all levels who have had little formal training in experimental design and user studies.
Dr Diane Kelly is an Assistant Professor at the School of Information and Library Science at the University of North Carolina in Chapel Hill. Kelly holds an undergraduate degree in psychology ( University of Alabama), a graduate certificate in cognitive science, and a master’s and Ph.D. in Information Science (all from Rutgers University).
Professor David J Harper is a Research Professor at The Robert Gordon University, Aberdeen, UK, where he leads the Information Retrieval and Interaction group. Harper holds an undergraduate degree in computing science ( Monash University, Melbourne), a PhD in computing science ( Cambridge, UK), and is a Fellow of the British Computer Society.
The Study and Practice of Personal Information Management – Level: Introductory. One full day.
Personal Information Management (PIM) includes the acquisition, organization, maintenance and retrieval of information by individuals in support of their various roles and activities. This tutorial provides an overview of PIM both as a field of inquiry and as an activity that each of us performs every day. It is designed for a general audience and provides a highly interactive combination of lectures, exercises, and group discussions.
Dr. William Jones is a Research Associate Professor in the Information School, University of Washington. He manages the Keeping Found Things Found (KFTF) project with focus on the use and re-use of integrative structures in support of PIM. He has also published research in human memory, information retrieval and in the general area of HCI.
Dr. Jacek Gwizdka is an Assistant Professor in the Department of Library and Information Science at Rutgers University. His research includes the study of email use and management, as well as work on interaction mechanisms for adding metadata to electronic notebooks and to collections of digital photos.
Morning
Introduction to Web IR – Level: Introductory. Half-day (Web Retrieval 1).
We review the history and main concepts behind searching the Web. This includes the user's needs behind a query and the challenges posed by the Web. We also cover all the algorithmic problems: crawling, distributed indexing, searching, and ranking, in particular link analysis.
Dr. Ricardo Baeza-Yates has a PhD in Computer Science from the University of Waterloo, Canada, in 1989. Presently he is Director of Yahoo! Research Barcelona and Latin America, in Spain and Santiago, Chile, respectively. He is co-author of the book Modern Information Retrieval, from 1999 as well as co-author of the 2nd edition of the Handbook of Algorithms and Data Structures, 1991, both published by Addison-Wesley.
Dr. Andrei Z. Broder is a Yahoo! Research Fellow and VP for Emerging Search Technology. Previously he has been an IBM Distinguished Engineer and the CTO of the Institute for Search and Text Analysis in IBM Research. From 1999 until 2002 he was Vice President for Research and Chief Scientist at the AltaVista Company, and before this he was a senior member of the research staff at Compaq's Systems Research Center in Palo Alto. He obtained his Ph.D. in Computer Science at Stanford University. Broder is co-winner of the Best Paper award at WWW6 (for his work on duplicate elimination of web pages) and at WWW9 (for his work on mapping the web).
Dr. Prabhakar Raghavan is Head of Yahoo! Research, and Consulting Professor of Computer Science at Stanford University. His research interests include semi-structured retrieval, text mining and randomized algorithms. He is Editor-in-chief of the Journal of the ACM and a Fellow of the ACM and of the IEEE. He holds a PhD from the University of California at Berkeley.
Statistical Language Models – Level: Intermediate. Half-day.
Abstract: The purpose of this tutorial is to systematically review the recent progress in applying statistical language models to information retrieval with an emphasis on the underlying principles and framework, empirically effective models, and language models developed for non-traditional retrieval tasks. Attendees can expect to learn the major principles and methods of applying statistical language models to IR, the outstanding problems in this area, as well as obtain comprehensive pointers to the research literature.
Dr. ChengXiang Zhai is an Assistant Professor of Computer Science at the University of Illinois at Urbana-Champaign. He received a Ph.D. in Computer Science from Nanjing University in 1990, and a Ph.D. in Language and Information Technologies from Carnegie Mellon University in 2002. His main research interests include information retrieval models, statistical language modeling, and personalized search. He received the 2004 Presidential Early Career Award for Scientists and Engineers (PECASE) and the best paper award of ACM SIGIR 2004."
Machine Learning for IR – Level: Introductory (IR knowledge required). Half-day.
Machine learning has been successfully applied to a number of information retrieval tasks. This tutorial will introduce machine learning techniques and their application to information retrieval. The tutorial is organized into four parts: 1) introduction to statistical inference, machine learning and information retrieval, 2) overview of supervised learning and its application to text classification, 3) overview of unsupervised/semi-supervised learning, and its applications to collaborative filtering and text clustering, 4) open problems and research directions.
Dr. Yi Zhang is an assistant Professor at Baskin School of Engineering in University of California Santa Cruz. Her research focuses on information retrieval, applied machine learning, and natural language processing.
Dr. Rong Jin is an assistant Professor at the Computer and Science Engineering Dept. in Michigan State University. His research focuses on statistical machine learning and its application to information retrieval.
Afternoon
XML Information Retrieval – Level: Introductory . Half-day.
With XML as the evolving standard for structured documents, there is an increasing demand for appropriate XML retrieval methods. The tutorial gives a survey over current activities in the area of XML IR. It introduces the major XML-related standards and their role in IR, and covers structured text models, already investigated before XML, and their relation to XML, as well as indexing and searching algorithms for XML. The tutorial will finish with the issue related to the evaluation of content-oriented XML retrieval, carried out as part of INEX.
Dr. Ricardo Baeza-Yates has a PhD in Computer Science from the University of Waterloo, Canada, in 1989. Presently he is Director of Yahoo! Research Barcelona and Latin America, in Spain and Santiago, Chile, respectively. He is co-author of the book Modern Information Retrieval, from 1999 as well as co-author of the 2nd edition of the Handbook of Algorithms and Data Structures, 1991, both published by Addison-Wesley.
Professor Mounia Lalmas has a PhD in Computer Science from University of Glasgow, in 1996. Presently she is a Professor of Information Retrieval at the Department of Computer Science, at Queen Mary, University of London. Her research focuses on the development and evaluation of intelligent access to interactive heterogeneous and complex information repositories. She is the co-leader of the INEX initiative, with over 50 participating organizations worldwide.
Using the Lemur Toolkit for Information Retrieval – Level: Introductory . Half-day
The Lemur Toolkit has become a popular platform for doing a wide range of Information Retrieval research. This tutorial gives attendees hands-on experience using the toolkit for retrieval experiments including experience with structured queries and documents. Additionally, attendees will learn about the toolkit's broader capabilities and how it can be integrated into larger information access applications. The hands-on portion of the presentation implies to bring laptops running Windows, Linux or Mac OS X. Software will be provided on CD.
Trevor Strohman is a Ph.D. student at the Unversity of Massachusetts, and the principal developer of the Indri portion of the Lemur toolkit.
Paul Ogilvie is a Ph.D. student at Carnegie Mellon University, and the principal developer of the Lemur toolkit's XML components.
Introduction to Web advertising – Level: Introductory . Half-day (Web Retrieval 2)
The tutorial covers the main concepts and challenges of Web search economics. We start with the business models of search engines and Internet advertising. Then we explore the algorithmic challenges of Web search advertisement: context-advertisement matching, and advertising placement based in keyword auctions.
Dr. Andrei Z. Broder is a Yahoo! Research Fellow and VP for Emerging Search Technology. Previously he has been an IBM Distinguished Engineer and the CTO of the Institute for Search and Text Analysis in IBM Research. From 1999 until 2002 he was Vice President for Research and Chief Scientist at the AltaVista Company, and before this he was a senior member of the research staff at Compaq's Systems Research Center in Palo Alto. He obtained his Ph.D. in Computer Science at Stanford University. Broder is co-winner of the Best Paper award at WWW6 (for his work on duplicate elimination of web pages) and at WWW9 (for his work on mapping the web).
Dr. Prabhakar Raghavan is Head of Yahoo! Research, and Consulting Professor of Computer Science at Stanford University. His research interests include semi-structured retrieval, text mining and randomized algorithms. He is Editor-in-chief of the Journal of the ACM and a Fellow of the ACM and of the IEEE. He holds a PhD from the University of California at Berkeley.