Information Retrieval: 8th Russian Summer School, RuSSIR by Pavel Braslavski, Nikolay Karpov, Marcel Worring, Yana

By Pavel Braslavski, Nikolay Karpov, Marcel Worring, Yana Volkovich, Dmitry I. Ignatov

This publication constitutes the completely refereed complaints of the eighth Russian summer season college on info Retrieval, RuSSIR 2014, held in Nizhniy Novgorod, Russia, in August 2014.

The quantity comprises 6 instructional papers, summarizing lectures given on the occasion, and eight revised papers from the college participants.The papers concentrate on numerous elements of data retrieval.

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Extra info for Information Retrieval: 8th Russian Summer School, RuSSIR 2014, Nizhniy, Novgorod, Russia, August 18-22, 2014, Revised Selected Papers

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A crucial difference to learning in a supervised setting is that only feedback for selected actions is observed. , performance while learning. These two characteristics result in the explorationexploitation challenge, because actions with unknown performance have to be explored to learn better solutions. An important benefit of reducing IR problems 32 K. Hofmann document list action at user environment examine document list evaluation measure reward rt retrieval system agent query state st implicit feedback generate implicit feedback Fig.

Interactive exploratory search for multi page search results. In: WWW 2013, pp. 655–666 (2013) 34. : Optimizing search engines using clickthrough data. In: KDD 2002, pp. 133–142 (2002) 35. : Evaluating the accuracy of implicit feedback from clicks and query reformulations in web search.

As these make their way into more and more interactive IR systems, we can expect to discover and solve new challenges. 8 Conclusion In this paper we have presented an overview of techniques for online experimentation for IR. With the increase in web-scale IR systems, controlled experiments have been adapted to deal with the challenges of scale and complexity that these 36 K. Hofmann systems present. As well as moving insights into experimentation methodology into practical settings, new methods for measurement an learning have been developed that can in turn benefit IR research.

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