1. That's the way we were thinking about it :)

2. Oh, excellent! We hadn't found that or we'd have used it, and we'll start working with it.

3. Tomorrow I'm going to blog about how we approached the machine learning. Short version; we manually came up with regular expressions to classify a training set based on titles. The idea is that when we experimented with manual annotations on titles, the vast majority of the time we were looking for only a few key words. There's no question that this adds biases and will not be entirely accurate, but manual inspection convinced us it was a good enough approach for our hackathon, and most of the articles we identified with the resulting algorithm would not have been found by the title regex alone.

You can see the table of regular expressions [here](https://github.com/dodger487/analyze_hn/blob/master/topics.c...) and a bunch of (pretty unstructured) analysis code [here](https://github.com/dodger487/analyze_hn/blob/master/hn-analy...).