Archive for the ‘FSTs’ Category

How to get superior text processing in Python with Pynini

Saturday, November 19th, 2016

How to get superior text processing in Python with Pynini by Kyle Gorman and Richard Sproat.

From the post:

It’s hard to beat regular expressions for basic string processing. But for many problems, including some deceptively simple ones, we can get better performance with finite-state transducers (or FSTs). FSTs are simply state machines which, as the name suggests, have a finite number of states. But before we talk about all the things you can do with FSTs, from fast text annotation—with none of the catastrophic worst-case behavior of regular expressions—to simple natural language generation, or even speech recognition, let’s explore what a state machine is, what they have to do with regular expressions.

Reporters, researchers and others will face a 2017 where the rate of information has increased, along with noise from media spasms over the latest taut from president-elect Trump.

Robust text mining/filtering will your daily necessities, if they aren’t already.

Tagging text is the first example. Think about auto-generating graphs from emails with “to:,” “from:,” “date:,” and key terms in the email. Tagging the key terms is essential to that process.

Once tagged, you can slice and dice the text as more information is uncovered.


Build your own finite state transducer

Sunday, June 9th, 2013

Build your own finite state transducer by Michael McCandless.

From the post:

Have you always wanted your very own Lucene finite state transducer (FST) but you couldn’t figure out how to use Lucene’s crazy APIs?

Then today is your lucky day! I just built a simple web application that creates an FST from the input/output strings that you enter.

If you just want a finite state automaton (no outputs) then enter only inputs, such as this example:


Mike’s post: Lucene finite state transducer (FST) summaries the potential for FSTs in Lucene.

HTRT? Be good with your tools. Be very good with your tools.