Road-map – or n+1 steps to enlightenment (or loonybind)

This post has been cross posted on Clojurelx

As we expressed in our previous post, we'd like to experiment with Clojure. Let us emphasis again, we are NOT developing a new library, we just believe that using Clojure in linguistic computing might be fruitful. In order to prove this assumption (or refute it), we are going to try some tools out, and summarize and share our experiences as blog posts. Here is our tentative road-map.

Topics

We don't want to cover everything since we are neither omniscient, nor experienced Clojure hackers – so take our words with a grain of salt. We've chosen a few “core” topics interesting to us. Naturally, the topics are divided into two categories; “classics” and “using Java power tools”. Please leave a comment; we'd appreciate your thoughts (even your critique!).

Classics

Algorithms for Computational Linguistics – we stole the title from the great (and open) book by Striegnitz, Blackburn, Erk, Walter, Burchardt and Tsovaltz. We'd like to approach finite state techniques from two perspectives: logical and functional.

Zipf's law – the well-known distribution – is the guinea pig of linguistic statistics. Inspired by the ZipfR package and Incanter, we examine some very basic stats about texts, like word length and frequency and we try out plotting our results.

Java power tools

OpenNLP and the Stanford parser are real power tools. Tagging, chunking and parsing are indispensable when we are working with data.

Latent semantics – using chisel to do LDA analysis with the MALLET package.