I’ve been exploring some neural networks for helping Tinderbox automatically classify some notes.
For example, some Tinderbox notes inevitably describe plans you’re making:
- Pick up some wine on the way home
- Return Hamlet On The Holodeck to the library before April 17.
I thought a neural net might be able to sort these planning notes out from all your other notes, and that might be handy. So far, we’re right about 7 times in 8, which isn’t too shabby.
Yesterday, I tried extending this to also recognize notes that review a book, article, play or movie — that offer an opinion or recommendation, or that summarize the work. About ⅓ of the items in this weblog are, in this sense, reviews. I trained the existing net with about 50 extracts from the weblog, and — what do you know — it’s astonishingly good. Plenty of mistakes, but it does the job. Oddly, the classifier seems to have an easier time recognizing reviews than recognizing plans.