I'm organizing a bakeoff, if you want to show off some Mahout skills and do a controlled comparison of Mahout to other people's approaches:
Let's say I have several hundred million documents, which are very short (only a few words). There are several million terms in the vocabulary. What is the fastest way to find the top-k semantically related terms for each term in the vocabulary? If you just want to hear the results, join this group: http://groups.google.com/group/metaoptimize-challenge-announce If you actually want to hack some data, read this blog post: http://metaoptimize.com/blog/2010/11/05/nlp-challenge-find-semantically-related-terms-over-a-large-vocabulary-1m/ It would be really cool to see participation from the Mahout community in a Mahout demo, to get a controlled comparison to other implementations. Best, Joseph
