Twss.js (opens in new tab)

Now I'm just waiting for someone to make a Twitter bot that randomly samples tweets and responds to them with this...

I think your negative sample set is a little biased. Since all the phrases start with verbs like "was in the car" or "went to the park", these kinds of phrases are given lower probabilities.

For example:

    > twss.prob("was on a stiff pole");
    0.016050826334564946

Only 1.6% chance of that's what she said?!?

EDIT: Counter example:

    > twss.prob("that's one stiff pole");
    0.9767718880285885

Related: http://www.quora.com/How-would-you-programmatically-parse-a-...

An interesting (and funny) exercise.

For those interested in neural networks and Bayesian classifiers check out the brain.js library: http://harthur.github.com/brain/

It works in both node and the browser.

A while back I was interested in implementing a much less naive algorithm for classifying TWSS expressions, based on this [1] paper. Never actually got around to finishing the work.

Interesting problem though, and nice work.

[1] - http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.p...

Well that open source project left me satisfied and smiling

Soon to be implemented in all IRC bots the world over

This is probably the first time I've understood node.js.

I was wondering if anyone knew of a place where I could learn about this stuff in general. I know nothing about unigrams, bigrams, trigrams, tf-idf, Bayesian filtering, etc. Maths - while not awful - is not my strongest point, but I think I could grok a well-written tutorial to this stuff (with code examples!).

I was hoping/wondering if anyone knew of sites I could start learning about this from? I find this very interesting, and I'm sure it could be highly useful and applicable to many different types of problems...

DanielRapp: in file twss.js/lib/classifier/knn.js, number of NN should be odd to prevent ties [EDIT: also, NN should be large enough to prevent over-fitting; small NN would mean that the difference (decision boundary) between twss and not-twss is highly non-linear; you need to implement cross-validation to find best NN]

Note to self: machine learning using node.js; what's the speed of calculations, what's the memory management in node.js, can I find pure JS implementation of SVM?

I'm still looking for a classifier that will take a phrase, determine if and what the "In Soviet Russia X Y you" response would be.

Anyone?

Has anyone thrown this on a web server with a simple interface?

MRI's have shown that humans are able to do this because of a dedicated site in the brain called "Scott's region". Once activated, this linguistic region is constantly searching for linguistic cues, surfacing signals to our conscious thoughts when the cues are strong enough.

I've seen a Siri proxy TWSS implementation: http://www.youtube.com/watch?v=p4LamngB070

We made our IRC bot respond to TWSS jokes, but ours was just a dumb match from a set of few thousand jokes that we scraped from offline. You can look at the code at: https://github.com/jfriedly/jenni

Now that I took Stanford's Machine Learning class though, I think I might just duplicate what this guy did for our bot.

While it seems on the surface like a waste of time (albeit amusing one), I actually expect this is a great project to learn from because of its use of Bayesian classifiers.

In other words, I'm TOTALLY going to be using this on my next project.

The training data is pretty funny. I suppose he collected it from an online TWSS thread.

Great start -- interesting to watch it go vs the twitter stream. (If you restrict to < 8 word tweets)

Looks like this could easily be integrated into a script for Hubot

I've never had a script do that for me

What exactly is Node.js specific about this?

goo.gl/39SLa

I approve this post.