ECIR 2008 Tutorials
This tutorial gives a clear and detailed overview of advanced language modeling approaches and tools, including the use of document priors, translation models, relevance models, parsimonious models and expectation maximization training. Expert search will be used as a case study to explain the consequences of modeling assumptions. For more details, you can access http://www.cs.utwente.nl/ hiemstra/ecir2008.
Djoerd Hiemstra is assistant professor at the University of Twente. He wrote a Ph.D. thesis on language models for information retrieval and contributed to over 90 research papers in the field of IR. His research interests include formal models of information retrieval, XML retrieval and multimedia retrieval.
Search and Discovery in User-Generated Text Content
Maarten de Rijke and Wouter Weerkamp
ISLA, University of Amsterdam, The Netherlands
We increasingly live our lives online: Blogs, forums, commenting tools, and many other sharing sites offer possibilities to users to make any information available online. For the first time in history, we are able to collect huge amounts of usergenerated content (UGC) within “a blink of an eye”. The rapidly increasing amount of UGC poses challenges to the IR community, but also offers many previously unthinkable possibilities. In this tutorial we discuss different aspects of accessing (i.e., searching, tracking, and analyzing) UGC. Our focus will be on textual content, and most of the methods that we will consider for ranking UGC (by relevancy, quality, opinionatedness) are based on language modeling. For more details, you can access http://ecir2008.dcs.gla.ac.uk/tutorial_sd.html.
Maarten de Rijke is professor of information processing and internet at the Intelligent Systems Lab Amsterdam (ISLA) of the University of Amsterdam. His group has been researching search and discovery tools for UGC for a number of years now, with numerous publications and various demonstrators as tangible outcomes. Wouter Weerkamp is a PhD student at ISLA, working on language modeling and intelligent access to UGC.
Researching and Building IR Applications Using Terrier
Craig Macdonald and Ben He
University of Glasgow, UK
This tutorial introduces the main design of an IR system, and uses the Terrier platform as an example of how one should be built. We detail the architecture and data structures of Terrier, as well as the weighting models included, and describe, with examples, how Terrier can be used to perform experiments and extended to facilitate new research and applications. For more details, you can access http://ecir2008.dcs.gla.ac.uk/tutorial_rb.html.
Craig Macdonald is a PhD research student at the University of Glasgow. His research interests includes Information Retrieval in Enterprise, Web and Blog settings, and has over 20 publications with research based on the Terrier platform. He has been a co-ordinator of the Blog track at TREC since 2006, and is a developer of the Terrier platform.
Ben He is a post-doctoral research assistant at the University of Glasgow. His research interests are centered around document weighting models, and particularly concerned about document length normalisation and query expansion. He has been a developer of the Terrier platform since its initial development and has more than 20 publications performed with Terrier.