[openasocket]

I think the solution is providing results with more structure than just a list of options. Being able to return something like "here's the list of pho places, but they aren't very good. We also have some ramen places here that are pretty good if you are interested." I think just having some sort of explanation why I've gotten a bunch of ramen places in my results would go a long way. At least giving some sort of explanation of the results could help a lot with that frustration. You could go even further and add some level of interactivity, allow the user to respond with "sure, show me the ramen results," or "no, show me the pho results anyway" would be the ideal.

The difficulty is that a lot of these sorts of queries, especially when machine learning is involved, are pretty opaque. You can find some set of results that meet the maximization of some metric in your feature space, but it's hard to explain why a particular result shows up there without resorting to a bunch of equations.

[jon_richards]

What do we want?

Context-aware natural language processing!

When do we want it?

When do we want what?