I’m not sure how many NYC Googlers read this blog, but I encourage you all to attend. I’ve also been able to put a few folks on the guest list. For everyone else, my host assures me that the recorded presentatio…
I’m not sure how many NYC Googlers read this blog, but I encourage you all to attend. I’ve also been able to put a few folks on the guest list. For everyone else, my host assures me that the recorded presentation will be posted on YouTube. And of course I’ll post the slides here at The Noisy Channel, as well as on SlideShare.
Here’s the title and abstract:
We’ve become complacent about relevance. The overwhelming success of web search engines has lulled even information retrieval (IR) researchers to expect only incremental improvements in relevance in the near future. And beyond web search, there are still broad search problems where relevance still feels hopelessly like the pre-Google web.
But even some of the most basic IR questions about relevance are unresolved. We take for granted the very idea that a computer can determine which documents are relevant to a person’s needs. And we still rely on two-word queries (on average) to communicate a user’s information need. But this approach is a contrivance; in reality, we need to think of information-seeking as a problem of optimizing the communication between people and machines.
We can do better. In fact, there are a variety of ongoing efforts to do so, often under the banners of “interactive information retrieval”, “exploratory search”, and “human computer information retrieval”. In this talk, I’ll discuss these initiatives and how they are helping to move “relevance” beyond today’s outdated assumptions.