When a watchful mentor emailed me a link to
Attensity over the
weekend, I was encouraged, finding, from a quick glance at their web site, that
some of the same data-mining they market, as their hallmark, matches up with a few
of the configurations defining a project I have underway.
Attensity claims to process data and analyze that which is otherwise difficult
to discern. Their software churns away like some kind of high-powered
heuristic meaning-cruncher–a processor of mass quantities of text into readable
metadata.
NORA (non-obvious relationship awareness) for large-scale discourse.
So I sent them an email inquiring about the whole plot,
all-the-while-recalling that the only other text parser I looked up asked $2k
per year for software licensing. Did I mention I’m a grad student?
Well, I did mention that in the email to Attensity, the email inquiring about
their project. And I heard back today–a polite note, something about
serving the US Intelligence community and a starting fee of $50,000. And
something about wishing me the best in my quest. Thanks. But no
thank-you.
The
proliferation of textual analysis apps self-identifying as the devices built
to root out terrorism piques my interest. Perhaps because of the sheer
volume of text to be analyzed for particular patterns (suspicious patterns!
watch the parentheticals, Attensity!), mass-discourse text parsers are up and
coming. And so unbelievably over-priced that they’re no use whatsoever to
the project I’m working on.
Well, remember that the gummit (and not Al Gore) was responsible for the development of the Internet�at least that’s the word around the campfire. So maybe this technology, too, will one day be used for some purpose other than to terrorize terrorists (she said, hopefully). Meanwhile, save your pesos.
Alternatively, all this might mean that your grad school experiences could lead you to truly lucrative employment (she said, with her tongue definitely in her cheek).
Gummit? Gummite? Don’t know that one. I’ll continue to save my change but more likely for Ph.’s college days than my own software extravagancies. And lucrative employ is no trade-off for fulfilling employ, right? I’d have never left KC if I was trying to worry hard about money (just as I was contemplating selling blood to travel to SF for CCCC).
I thought it was the gummint, myself. But it sounds like there are two different issues you’re looking at, Derek: one, the harvesting of the information, and two, the filtering of it. It strikes me that (1) is the hard part: after all, regarding (2), I’ve got colleagues who are putting together Perl translators for Old English, and Anne Herrington and Charlie Moran wrote recently in CE about computerized essay evaluators. If you’ve got an algorithm for making sense — well, what are you looking for, exactly? Ever since reading Anne and Charlie’s article, I’ve waited for the Slashdot post offering information about reverse-engineering the algorithm that “reads” and “evaluates” student essays and how to game it.
So I guess I’m asking: is it the volume that’s your concern, or is it the patterns?
Anyway. Not quite sure how to read your last parenthetical — I’m hoping that you will, in fact, be at CCCC, yes?
Yeah, I’ll be at CCCC. I hope we have a chance to get together. I have your Friday morning session penciled in, but maybe we can meet up before then. I’m coming in on Wednesday mid-day and leaving out on Saturday mid-day. I’d like to hear more about the Perl scripts. I was on the verge of applying one to the current project, but I went with something simpler. I’m not turning it toward student writing, and I’m interested in both volume and pattern to some degree, but also a few other questions/devices/methods.