Ellen Voorhees defends Cranfield

I was extremely flattered to receive an email from Ellen Voorhees responding to my post about Nick Belkin's keynote. Then I was a little bit scared, since she is a strong advocate of the Cranfield tradition, and I braced myself for her rebuttal.

She pointed me to a talk she gave at the First International Workshop on Adaptive Information Retrieval (AIR) in 2006. I'd paraphrase her argument as follows: Nick and others (including me) are right to push for a paradigm that supports AIR research, but are being naïve regarding what is necessary for such research to deliver effective--and cost-effective--results. It's a strong case, and I'd be the first to concede that the advocates for AIR research have not (at least to my knowledge) produced a plausible abstract task that is amenable to efficient evaluation.

To quote Nick again, it's a grand challenge. And Ellen makes it clear that what we've learned so far is not encouraging.

Multiple-Query Sessions

As Nick Belkin pointed out in his recent ECIR 2008 keynote, a grand challenge for the IR community is to figure out how to bring the user into the evaluation process. A key aspect of this challenge is rethinking system evaluation in terms of sessions rather than queries.

Some recent work in the IR community is very encouraging:

- Work by Ryen White and colleagues at Microsoft Research that mines session data to guide users to popular web destinations. Their paper was awarded Best Paper at SIGIR 2007.

- Work by Nick Craswell and Martin Szummer (also at Microsoft Research, and also presented at SIGIR 2007) that performs random walks on the click graph to use click data effectively as evidence to improve relevance ranking for image search on the web.

- Work by Kalervo Järvelin (at the University of Tampere in Finland) and colleagues on discounted cumulated gain based evaluation of multiple-query IR sessions that was awarded Best Paper at ECIR 2008.

This recent work--and the prominence it has received in the IR community--is refreshing, especially in light of the relative lack of academic work on interactive IR and the demise of the short-lived TREC interactive track. They are first steps, but hopefully IR researchers and practitioners will pick up on them.

Nick Belkin at ECIR '08

Last week, I had the pleasure to attend the 30th European Conference on Information Retrieval, chaired by Iadh Ounis at the University of Glasgow. The conference was outstanding in several respects, not least of which was a keynote address by Nick Belkin, one the world's leading researchers on interactive information retrieval.

Nick's keynote, entitled "Some(what) Grand Challenges for Information Retrieval," was a full frontal attack on the Cranfield evaluation paradigm that has dominated IR research for the past half century. I am hoping to see his keynote published and posted online, but in the meantime here is a choice excerpt:

in accepting the [Gerald Salton] award at the 1997 SIGIR meeting, Tefko Saracevic stressed the significance of integrating research in information seeking behavior with research in IR system models and algorithms, saying: "if we consider that unlike art IR is not there for its own sake, that is, IR systems are researched and built to be used, then IR is far, far more than a branch of computer science, concerned primarily with issues of algorithms, computers, and computing."

...

Nevertheless, we can still see the dominance of the TREC (i.e. Cranfield) evaluation paradigm in most IR research, the inability of this paradigm to accommodate study of people in interaction with information systems (cf. the death of the TREC Interactive Track), and a dearth of research which integrates study of users’ goals, tasks and behaviors with research on models and methods which respond to results of such studies and supports those goals, tasks and behaviors.

This situation is especially striking for several reasons. First, it is clearly the case that IR as practiced is inherently interactive; secondly, it is clearly the case that the new models and associated representation and ranking techniques lead to only incremental (if that) improvement in performance over previous models and techniques, which is generally not statistically significant; and thirdly, that such improvement, as determined in TREC-style evaluation, rarely, if ever, leads to improved performance by human searchers in interactive IR systems.

Nick has long been critical of the IR community's neglect of users and interaction. But this keynote was significant for two reasons. First, the ECIR program committee's decision to invite a keynote speaker from the information science community acknowledges the need for collaboration between these two communities. Second, Nick reciprocated this overture by calling for interdisciplinary efforts to bridge the gap between the formal study of information retrieval and the practical understanding of information behavior. As an avid proponent of HCIR, I am heartily encouraged by steps like these.