188 karma · joined November 6, 2008
The vast majority of people who participate in conference are good people. However, it only takes one person (out of thousands!) who has this kind of personality dysfunction to lead an attack, and women are much much more likely to be the target of their dysfunction.
The challenge with stream analysis is that you are dealing with a continuous stream of data where you can see each element of the stream only one time and must still be able to cluster/classify/analyze it. There are still few algorithms and tools designed explicitly for that purpose.
I'll refine the example for the next time!
We build systems on top of the bitly data. This involves things like algorithms for identifying spam and malware, real-time content recommendations (which you can see in http://news.me), categorical analysis, etc.
We also do a few pure research studies, like this one: http://www.readwriteweb.com/archives/does_your_device_change...
And let me know if you have any questions!
I'm looking forward to seeing you there!
I'm trying to use the model of the unix command line -- each script is useful and simple on its own, but in combination they become incredibly powerful.
The feature set includes sender, recipients, whether I'm the only recipient, time of day, words in the subject, words in the body, and whether I've exchanged messages with the sender recently.
There's also a whitelist.
I'll release the code as soon as I disentangle my personal data from it. Patches welcome. :-)
(I don't have the data to back that up - yet - so it's worded vaguely).
Anecdotally, I know several adult women who are learning to program and kicking ass at it.
I'm sorry that you've found our field to be so inhospitable. That hasn't been my experience at all, though I appreciate your point about making technology hospitable to everyone.