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Twss.js

305 点作者 nezzor超过 13 年前

23 条评论

tibbon超过 13 年前
Now I'm just waiting for someone to make a Twitter bot that randomly samples tweets and responds to them with this...
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notb超过 13 年前
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.<p>For example:<p><pre><code> &#62; twss.prob("was on a stiff pole"); 0.016050826334564946 </code></pre> Only 1.6% chance of that's what she said?!?<p>EDIT: Counter example:<p><pre><code> &#62; twss.prob("that's one stiff pole"); 0.9767718880285885</code></pre>
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blahpro超过 13 年前
Related: <a href="http://www.quora.com/How-would-you-programmatically-parse-a-sentence-and-decide-whether-to-answer-thats-what-she-said" rel="nofollow">http://www.quora.com/How-would-you-programmatically-parse-a-...</a>
driverdan超过 13 年前
An interesting (and funny) exercise.<p>For those interested in neural networks and Bayesian classifiers check out the brain.js library: <a href="http://harthur.github.com/brain/" rel="nofollow">http://harthur.github.com/brain/</a><p>It works in both node and the browser.
yuvadam超过 13 年前
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.<p>Interesting problem though, and nice work.<p>[1] - <a href="http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.pdf" rel="nofollow">http://www.cs.washington.edu/homes/brun/pubs/pubs/Kiddon11.p...</a>
adam_albrecht超过 13 年前
Well that open source project left me satisfied and smiling
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TwistedWeasel超过 13 年前
Soon to be implemented in all IRC bots the world over
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bjornsteffanson超过 13 年前
This is probably the first time I've understood node.js.
VolatileVoid超过 13 年前
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!).<p>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...
zeratul超过 13 年前
DanielRapp: in file <i>twss.js/lib/classifier/knn.js</i>, 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 <i>twss</i> and <i>not-twss</i> is highly non-linear; you need to implement cross-validation to find best NN]<p>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?
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donohoe超过 13 年前
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.<p>Anyone?
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phreeza超过 13 年前
Has anyone thrown this on a web server with a simple interface?
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mckoss超过 13 年前
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.
tnorthcutt超过 13 年前
I've seen a Siri proxy TWSS implementation: <a href="http://www.youtube.com/watch?v=p4LamngB070" rel="nofollow">http://www.youtube.com/watch?v=p4LamngB070</a>
jfriedly超过 13 年前
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: <a href="https://github.com/jfriedly/jenni" rel="nofollow">https://github.com/jfriedly/jenni</a><p>Now that I took Stanford's Machine Learning class though, I think I might just duplicate what this guy did for our bot.
Zelphyr超过 13 年前
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.<p>In other words, I'm TOTALLY going to be using this on my next project.
mertd超过 13 年前
The training data is pretty funny. I suppose he collected it from an online TWSS thread.
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radikalus超过 13 年前
Great start -- interesting to watch it go vs the twitter stream. (If you restrict to &#60; 8 word tweets)
loganlinn超过 13 年前
Looks like this could easily be integrated into a script for Hubot
tibbon超过 13 年前
I've never had a script do that for me
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tlrobinson超过 13 年前
What exactly is Node.js specific about this?
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aithleyadeno超过 13 年前
goo.gl/39SLa
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TWSS超过 13 年前
I approve this post.