

Ask HN: Built a news stories classification engine ... now what? - baham

For the past 2 months, I have been working on a news stories classification engine. I believe to have reached a stable stage and the application can be viewed at http://babeligg.com/.
I have so far approached it as a technical challenge. Right now I have two interrogations which I submit to the HN community:
* Is it possible to run some test suite to independently confirm that the performance are superior?
* How can such tool/API be monetized?<p>Thanks.
======
thetrumanshow
To answer your first question, you should simply benchmark against the average
Mechanical Turk worker's ability to classify links. Build a set of tests from
the workers and every time you update your algorithm, you'll need to run
against the dataset to see if you've improved anything.

For the second question, your product would be most valuable as an aid to
contextual advertising (what ads should I display?), and its possible that you
could charge per 1K requests. I have a need for this myself, so I would be
happy to be a beta-tester.

------
sidmitra
I haven't looked at it in detail yet. But first thoughts, lose the name. It's
highly forgettable and ugly on the tongue.

EDIT: For a second i was confused, was i supposed to enter some words or a
URL. So i tried random words, hoping it would give me stories classified
accordingly. Tried "django", and some others. It classifies everything into
sports.

Seems to do a decent jobs with some random URLs i threw at it. Seems to get
startup news into the Business category, which is fine.

Gets technical articles wrong, but those are tough: eg.
<http://blog.doughellmann.com/2007/07/pymotw-subprocess.html>

------
mahmud
_Is it possible to run some test suite to independently confirm that the
performance are superior?_

Just think harder about that question. It raises all sorts of philosophical
questions about machine, intelligence, language and meaning.

Of course, there ARE benchmarks, at least one bundled with each classifier
tool ;-) but there couldn't be _one_ ideal benchmark, no.

This might give you a start though:

[http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4...](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.38.4841)

------
yread
Would be nice to have some examples ready where it shines

