Putting context into search and search into context.

It is very challenging task to understand a short query, especially if that query is considered in isolation. Luckily, queries do magically appear in a search box -- rather, they are issued by real people, trying to accomplish a task, at a given point in time and space, and this "context" can be used to aid query understanding. Traditionally search engines have returned the same results to everyone who asks the same question. However, using a single ranking for everyone, in every context limits how well a search engine can do. In this talk I outline a framework to quantify the "potential for personalization", that can be used to characterize the extent to which different people have the same (or different) intents for a query. I then describe several examples of how we represent and use different kinds of context to improve search quality. Finally I conclude by highlighting some important challenges in developing such systems at Web scale including system optimization, evaluation, transparency and serendipity.