The 31st Annual International ACM SIGIR Conference
20-24 July 2008, Singapore



W1: Focused Retrieval: Question Answering, Passage Retrieval, Element Retrieval

Andrew Trotman (University of Otago, New Zealand),
Shlomo Geva (Queensland University of Technology, Australia),
Jaap Kamps (University of Amsterdam, The Netherlands),

Standard document retrieval finds atomic documents, and leaves it to the end-user to locate the relevant information inside the document. Focused retrieval removes this latter task from the end user by providing more direct access to relevant information. That is, focused retrieval addresses information retrieval and not simply document retrieval. Focused retrieval has already been used to extract relevant sections from academic documents, and the application to text book search is obvious.

The purpose of this workshop is to raise issues and promote discussion on focused retrieval - that is, Question Answering, Passage Retrieval, Element Retrieval, and other models. Unexpected synergies have already come to light and we expect the workshop papers and discussions to be lively and highly productive.

W2: Learning to Rank for Information Retrieval

Hang Li (Microsoft Research Asia),
Tie-Yan Liu (Microsoft Research Asia),
ChengXiang Zhai (University of Illinois at Urbana-Champaign),   

The task of "learning to rank" has emerged as an active and growing area of research both in information retrieval and machine learning. The goal is to design and apply methods to automatically learn a function from training data, such that the function can sort objects (e.g., documents) according to their degrees of relevance, preference, or importance as defined in a specific application.

The relevance of this task for IR is without question, because many IR problems are by nature ranking problems. Improved algorithms for learning ranking functions promise improved retrieval quality and less of a need for manual parameter adaptation. In this way, many IR technologies can be potentially enhanced by using learning to rank techniques.

 A workshop entitled Learning to Rank for Information Retrieval will be organized at SIGIR 2008, following a very successful workshop on the same topic at SIGIR 2007 (website:  report:
&dl=&CFID=62683274&CFTOKEN=33141712 ). The main purpose of this workshop is to bring together IR researchers and ML researchers working on or interested in the technologies, and let them to share their latest research results, to express their opinions on the related issues, and to discuss future directions. 

W3: Searching Spontaneous Conversational Speech

Joachim Kohler (Fraunhofer IAIS, Germany),
Martha Larson (University of Amsterdam, The Netherlands),
Franciska de Jong (University of Twente, The Netherlands),
Roeland Ordelman (University of Twente, The Netherlands),
Wessel Kraaij (TNO ICT, The Netherlands),

SSCS 2008 brings together speech and IR researchers. Topics include optimizing search for speech, exploiting evidence beyond the word, access to multilingual/multimedia collections, speech mining, visualization, system design, development and evaluation. Domains of interest encompass conversational broadcast, podcasts, meetings, lectures, discussions, debates, interviews and cultural heritage archives

W4: Analytics for Noisy Unstructured Text Data

Daniel Lopresti (Lehigh University),
Shourya Roy (IBM India Research Lab),
Klaus Schulz (University of Munich),
L. Venkata Subramaniam (IBM India Research Lab),

By its very nature, noisy text warrants moving beyond traditional text analytics techniques. Noise introduces challenges that need special handling, either through new methods or improved versions of existing ones. We welcome original research papers that identify key problems related to noisy text analytics and offer solutions.

W5: Future Challenges in Expertise Retrieval

Krisztian Balog (University of Amsterdam, The Netherlands),
Yong Yu (Apex Knowledge & Data Management Lab, China),

At the TREC Enterprise Track in 2005 the need to study and understand expertise retrieval was recognized through the introduction of an Expert Finding task. The task has generated a lot of interest in the IR community, and rapid progress has been made in terms of modeling, algorithms, and evaluation over the past 3 years. In fact, expertise retrieval has reached the point where it is appropriate to assess progress, bring people from different research communities together, and define a research agenda for the next years.

W6: Aggregated Search

Mounia Lalmas (Queen Mary, University of London),
Vanessa Murdock (Yahoo! Research Barcelona),

Aggregated search assembles information from a variety of sources, placing it in a single interface. The workshop seeks an understanding of the current state-of-the-art in aggregated search. We will discuss issues such as ranking and aggregating results from multiple sources, generating interfaces, and evaluating such systems.

W7: Beyond Binary Relevance: Preferences, Diversity, and Set-Level Judgments

Paul N. Bennett (Microsoft Research),
Ben Carterette (University of Massachusetts Amherst),
Olivier Chapelle (Yahoo! Research),
Thorsten Joachims (Cornell University),

New response types, like preference judgments or usage data, require learning methods, evaluation measures, and collection procedures designed for them. This workshop will address research challenges at the intersection of novel measures of relevance, novel learning methods, and core evaluation issues. We encourage the submission of new research that extends traditional relevance assessment in evaluation, machine learning, collaborative filtering, and user modeling.

W8: Teaching and Learning of Information Retrieval

As of 20 May 2008, this workshop has been cancelled.  All prior registrants who have selected this workshop will be notified by the SIGIR secretariat and an alternative workshop or refund will be issued.

W9: Mobile Information Retrieval

Kap Luk Chan (Nanyang Technological University, Singapore),
Xing Xie (Microsoft Research Asia, China),
Wang-Chien Lee (Penn State University, USA),
Minoru Etoh (NTT DoCoMo, Japan),
Flora S. Tsai (Nanyang Technological University, Singapore),

Mobile Information Retrieval (MobIR’08) is a timely workshop concerned with the indexing and retrieval of textual, audio and visual information such as text, graphics, animation, sound, speech, image, video and their various possible combinations for use in mobile devices with wireless network connectivity. The objective of this workshop is to provide a single forum for researchers and technologists to discuss the state-of-the-art, present their contributions, and set future directions in emerging innovative research for mobile information retrieval.

W10: Information Retrieval in Advertising

Ewa Dominowska (Microsoft),
Eugene Agichtein (Emory University),
James Shanahan (Independent Consultant),
Evgeniy Gabrilovich (Yahoo! Research),

Advertising is a multi-billion dollar industry that has become a significant component of the Web browsing experience. Online advertising systems incorporate many information retrieval techniques by combining content analysis, user interaction models, and commercial constraints. Advances in online advertising have come from integrating several core research areas: information retrieval, data mining, machine learning, and user modeling.

The workshop will serve as an open forum for discussion of new ideas and current research related to information retrieval topics relevant to online advertising. The outcome will be a set of full and short papers covering a variety of topics. The short paper format will allow researchers new to the area to actively participate and explore novel themes. It will also enable researchers without access to extensive empirical data to propose ideas and experiments. We also expect the workshop to help develop a community of researchers interested in this area, and yield future collaboration and exchanges.

Despite its commercial significance, advertising is a rather young field of research. This workshop will help the emerging research community better organize and develop a common perspective. The workshop will serve as a forum for researchers and industry participants to exchange latest ideas and best practices while encouraging future breakthroughs. It will also aid in fostering collaboration between industry and academia.