Feature vectors

Continuing along the thread of labels, it's natural to think of feature vectors. Each label would represent a dimension in the vector. 

Features

• starting time
• ending time
• applicable Sunday
• applicable Monday
• applicable Tuesday
• applicable Wednesday
• applicable Thursday
• applicable Friday
• applicable Saturday
• applicable on holiday
• "no parking" or "no standing" or "no stopping"

11 features so far. Is that too many?

I've also thought about how to best represent the output, or even what it should be. Went through a few iterations before settling on this for now:

• Sunday rules
• 12am - 12:30am - parking allowed
• 12:31am - 1:00am - parking allowed
• (etc)
• 11:31pm - 11:59pm - parking allowed
• Monday rules
• (etc)
• (all other days of the week)

This is a very high dimensional vector. Shouldn't be an issue though. In terms of size it can be represented by a few bytes. And we aren't running any classification on these features (I think). 

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Looked into parsing the times of day from the text. Some light Googling suggested I go with Stanford CoreNLP, some Java code they wrote. I tried to install and use a python wrapper for it, but the test failed. Might try another, might try to fix the problem with the text, might go straight for the real thing.