Getting Started In: Bayesian NLP

This isn't so much a post in the "GSI" series, but just two links that recently came out. Kevin Knight and Philip Resnik both just came out with tutorials for Bayesian NLP. They're both excellent, and almost entirely non-redundant. I highly recommend reading both. And I thank Kevin and Philip from the bottom of my heart, since I'd been toying with the idea of writing such a thing (for a few years!) and they've saved me the effort. I'd probably start with Kevin's and then move on to Philip's (which is more technically meaty), but either order is really fine.

• Bayesian Inference with Tears by Kevin
• Gibbs Sampling for the Uninitiated by Philip

Thanks again to both of them. (And if you haven't read Kevin's previous workbook on SMT -- which promises free beer! -- I highly recommend that, too.)

NetFlix "solved" (the small version)

See the post on Hunch. Maybe that last 1.5% might benefit not from fancy ML, but from fancy (or even stupid) NLP. "But what data do we have to run the NLP on," my friends may ask. How about stuff like this, or if you're adventurous like this? (Had I enough time, I might give it a whirl, but alas...)

p.s., If any of the above links encourage copyright violations, then I'm not actually advocating their use.

3 Small Newses

(Yeah, I know, "news" isn't a count noun.)

1. WhatToSee has been updated with ACL and EMNLP 2007, so figure out what talks you want to go to!
2. Yoav has set up a State Of The Art wiki page (see previous blog post on this topic)... please contribute!
3. The proposal for making CL an open-access journal has been accepted, so we get our 5 minutes of fame -- come by to support (or not). The business meeting is scheduled for 1:30pm on 26 June.
   

Very Sad News

Karen Sparck-Jones passed away this morning. You can find more information about her here and in many other places on the web. I, personally, remember Karen as endlessly enthusiastic and always willing to push me to think about problems in new (and interesting) lights. She's been immensely important in both NLP and IR, and her death is an enormous loss to the field; I have greatly valued her contributions in DUC discussions, among other things. Many will miss her.

I'll leave this discussion with a quote from an email I have from her from only a few weeks ago, since I think it's something we should all think about, whatever our context:

Document collections is a much misumnderstood topic -- you have to think what its for and eg where (in retrieval) you are going to get real queries from. Just assembling some bunch of stuff and saying hey giys, what would you like to do with this is useless.