If SIGIR had an Academic Track, What Would Be In It?

It used to be the case that very little industry research was presented at SIGIR. Now the balance has radically changed -- many accepted papers have industry authors and many rely on industry data sets -- To the extent that a leading academic member of the SIGIR community has light-heartedly proposed the creation of an Academic Track. Behind the levity lies the important question of how a researcher can make a meaningful contribution to the field, in the absence of petabyte-scale sets of documents and massive user-interaction logs. Theoretical contributions can revolutionize thinking, but have greatest impact when applicable in practice, and when empirically validated. In my years at Funnelback and more recently at Microsoft I have been very aware of high-impact but not-well-solved IR problems involving relatively tiny datasets. Many of them are characterized by sparsity of user interaction data and are hence not well-suited to simple machine learning approaches or to large scale A/B testing. My talk will illustrate and attempt to characterize these problems and to suggest fruitful areas for academic research. If time permits, I will mention some areas in which academic research has contributed to current large-scale industry practice.