----"Our discounts are meant to be one time only, but we can't limit them by customer so every order ends up sold 50% off. Said another way, for every additional $60 average order shipped our variable cost is $89 and we lose of $29. " ----
That's is incredibly odd they where using Magento, which does have the capability to limit promotions to be used once per customer.
If what you want is to only classify the stories in the front page and classify them based on a preset of categories, that's actually pretty simple to do.
I been working on a similar concept for personal project. Here are my recommendations:
- Be sure to remove stopwords from the titles before using the classifier.
- The ankusa gem will help you greatly https://github.com/bmuller/ankusa
Ankusa is a naive bayesian text classifier that will come really handy for the task you are trying to achieve.
Also make sure your training data sets are pretty clean and with little overlapping as possible.
Finally have fun and let us knows how it goes!!
Cheers and let me know if you have more questions or if you want a hand coding this thing.
Thanks for your answer! What I'm thinking of making is basically separating posts into two categories, things that interest me and things that don't. Then, I want to receive emails at intervals I specify. This is so I no longer have the urge to check HN frequently, but still stay up t date.
The actual classification is probably the easy part, the hard part is training the model, which is why I wanted to ask if anyone had done it before. Have you managed to train anything to recognize your tastes, or is it objective categories? How well does it work?
Well, my classifier works based on categories like ruby, programming, php, magento etc.
To train the classifier I grabbed feeds from different reddits and used that as a based data set. What you are trying to achieve sounds more like a recommendation engine rather than a classifier maybe recommendify might come handy https://github.com/paulasmuth/recommendify
You still can use the bayesian classifier, for training it I would recommend the supervised training route, basically start with a small dataset(100 records) and manually classify each of the training examples.
Also you should leave some sort of way to provide feedback to your classifier to improve the results and make corrections
Yeah, I'll have upvotes and downvotes to tell it what I liked or didn't. Unfortunately, I can't see a way to do this without supervised learning (maybe semi-supervised would work), which is why I posted here for ideas (I want to avoid the costly supervision step if someone knows the result won't work).
I suppose you could train the classifier by having it record what you upvote, or which links you click on. Perhaps a Firefox/Chrome extension could do that?
I'm currently using a very simple bookmarklet scheme, one for upvote and one for downvote. It works very well for collecting data, I'll train it later tonight, I think.
Thank you for the link, it looks very extensive, I'll peruse it later on.
Unless you can offer any real alternatives to Magento I have to call bullshit, yes the framework is far from perfect and PHP is not the prettiest language.
But calling Magento "Java written in PHP" without offering alternatives, specific criticism or any backing of the argument is just childish.
I'm building des.sk with tasks management, document editor, calendar (with sharing between teams), contacts and project management. Everything I need to be productive online without going to external services. Seems though students love it too.
But to be honest, crappy insecure site or not you went poking around and even created an extension that bypasses their (crappy) business model.
You made some poor decisions time to deal with the consequences, depending on the state/country he might or might not have a good claim against you.
Seek legal representation