

A Whiteboard Artifact - mariorz
http://ycombinator.posterous.com/a-whiteboard-artifact

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Nekojoe
I remember hearing about a Xerox research lab that had a whole room where the
walls were all whiteboard.

They had a celling mounted camera that would scan the walls. They also had a
markup language that the camera OCR software would pick up. So for example if
they drew a P in a square, it would print out that wall to the printer. If
they wrote an e-mail address in a square it would e-mail a photo of the
whiteboard to that e-mail address.

This was 7 or 8 years ago. I wonder if they still use this system.

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troels
Link?

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Nekojoe
I heard about it 7 or 8 years ago from people who had been to Xerox Parc and
Cambridge (UK) based Xerox Research Centres.

I can find this research paper online, although it appears to be dated 1995.
It's not exactly what I was told about, but it seems to be an earlier version.

[http://books.google.co.uk/books?id=gjm6FpMUTXgC&pg=PA509...](http://books.google.co.uk/books?id=gjm6FpMUTXgC&pg=PA509&lpg=PA509&dq=Xerox+Whiteboard&source=bl&ots=Rh6AtCrPtN&sig=T7-HqMSPL1mPq1av4D1R2G5xIVk&hl=en&ei=y_x_SqqbKcirjAfa7czwAQ&sa=X&oi=book_result&ct=result&resnum=3)

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snprbob86
This is my first time hearing about DirectedEdge: very cool stuff!

I watched the video and it looks like you guys have a great thing going on.
I'd like to make a suggestion, if I may: prove that this isn't just for
"similar users also bought". Prove that everybody should be doing
recommendations for practically anything.

Here's one idea: call the Reddit guys. Use your recommendation engine to
recommend articles, subreddits, and users I might like based on my up-votes.
Ask them if they would be willing to show "Recommendations Powered by
DirectedEdge.com" on there. Hit it out of the park with one partner and you'll
have other people lining up to use your platform!

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byrneseyeview
Reddit's initial appeal was supposed to be the recommendation engine. But for
me, it never got past being a version of the front page with a different decay
algorithm (even to the point that it included stuff I'd read and/or
downvoted).

So this would be a little like the Yahoo/Bing deal.

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pmjordan
Photographing the whiteboard and emailing the photo(s) to everyone who was at
the meeting is a great tool for remembering what was discussed and decided.
I'm always surprised at how few people do it. If your whiteboard isn't big
enough and you have to erase it halfway through, you do need the presence of
mind to take a picture before rubbing it out. Leave the camera by the eraser.

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wlievens
There's software to clean up these pictures (remove glare, correct
perspective).

I've thought about software that goes further... I'm thinking for instance,
vectorize the image, OCR the text, convert sloppily-drawn lines into actual
arrows. Whiteboard-photo-to-Visio, so to speak. It won't be possible to do
this fully automagically of course, because of bad clarity of writing and
drawing, but a tool could be made that assists the user to do this rapidly.
Not easy, but not undoable either.

Would you think there's actually a business for software that does this? Or is
it just a silly geek "solution looking for a problem"?

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pmjordan
To be perfectly honest, I can't see a use for it. You WANT to have it in
handwriting because it reminds you who wrote what, which helps you remember
what they said while writing it. Sure, you can't really show these things to
outsiders, but I don't think automated tidying would help that much.

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troels
OCR would be useful for allowing you to search.

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tezza
As a method of keeping a whiteboard for posterity, also consider
MagicWhiteBoard :: <http://www.magicwhiteboard.co.uk/>

You do your whiteboarding, and can peel them off and save them for later.

[I do not work for MagicWhiteBoard in any capacity]

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dcminter
I've used this stuff and can heartily recommend it. It's convenient for living
spaces and the like where you might not want (or be allowed by the SO/Landlord
etc) to put up "real" whiteboard.

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caffeine
Directed Edge is pretty cool. So far, though, I think we've been hearing a lot
about their graph database, and not much about how they're actually going to
do recommendations. Personally, I think the latter is the harder problem.

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wheels
To be honest, that's because I'm comfortable dissecting our graph-database
publicly, but less so for our ranking algorithms. There's been far more work
put into the recommendations engine than the graph DB and the beginnings of
the engine predate the DB. The original prototypes worked with our Store
class, which is the DB abstraction that the engine sees, and were purely in-
memory and then there were a number of things that I swapped in to replace the
storage layer, eventually settling on our own DB.

That said, I do have one big blog post half-written on "the problems of sparse
data" that I'll eventually roll out.

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caffeine
That would be very interesting (to me, at least). In particular, I'd be
curious to know how you _test_ your inferences. I guess you could run it on
the NetFlix/GitHub prizes ... but in general, I'm finding that getting
reliable data on which to validate algos is one of the biggest challenges.

In any case, I'd be interested to hear about the math, since there are about
50 different ways of doing this stuff. Even just vague stuff like "We might
use a boltzmann machine".

There's some interesting work done on optimal stimulus selection (MacKay has a
paper on it, and there's one in a neuroscience setting by Paninski). The idea
is that you generate data for which the response will give you maximum
information. So you figure out which edges would be most valuable to your
algo's predictions (using information theory) and then make recommendations
based on hypotheses about those edges, which are later confirmed/denied by
user behavior. This gives you an optimal learning loop.

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gojomo
The vision sounds a lot like Loomia... though it looks like they've come to
focus on content/publishing sites, retail or indeed 'anything' seemed the
earlier focus.

