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Three Stories on Aggregated Search

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If you have a question about this talk, please contact Tamara Polajnar.

A result page of a modern search engine is often much more complicated than a simple list of “ten blue links.” In particular, a search engine may combine results from different sources (e.g., web, news, images, structured data), and display these as grouped results to provide a better user experience. Such a system is called an aggregated or federated search system.

In the talk I will touch on three aspects of aggregated search. First, I will talk about aggregated search for queries with a video intent, where multiple sources being aggregated might have results of the same (video) type. Next, I will illustrate new challenges for entity linking and disambiguation that emerge in the setting of aggregated search. And finally, I will talk about evaluating aggregated search. Because search engines evolve over time, their results need to be constantly evaluated. However, one of the most efficient and widely used evaluation methods, interleaving, cannot be directly applied to aggregated search systems, as it ignores the need to group results originating from the same source (vertical results).

The talk is based on joint work with Marc Bron, Aleksandr Chuklin, Katja Hofmann, Damien Lefortier, Daan Odijk, Anne Schuth, Pavel Serdyukov, Jasmijn Van Gorp

This talk is part of the NLIP Seminar Series series.

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