I’m still waiting for Google to post a video of the talk to YouTube, but in the meantime here are the slides for your enjoyment. I’ve included speaker notes designed to make the talk completely self-contained, but you’ll need to download the PowerPoint file from SlideShare to see those.
I’d like to add that my hosts at Google NYC were very gracious, particularly considering that my material was more than a little critical of their approach to sea…
I’m still waiting for Google to post a video of the talk to YouTube, but in the meantime here are the slides for your enjoyment. I’ve included speaker notes designed to make the talk completely self-contained, but you’ll need to download the PowerPoint file from SlideShare to see those.
I’d like to add that my hosts at Google NYC were very gracious, particularly considering that my material was more than a little critical of their approach to search and information retrieval.
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 In this talk, I’ll discuss these initiatives and how they are helping to move “relevance” beyond today’s outdated assumptions.
