SenseClusters (http://senseclusters.sourceforge.net) participated in
Senseval-4/Semeval1, in the sense induction task. Additional
information about the task (including the data) can be found here:
http://ixa2.si.ehu.es/semeval-senseinduction/

For this task I used the currently released version of SenseClusters
(0.95) with fairly standard settings. The short summary of my approach
is that I used second order context vectors, bigrams selected using
pmi with a window size of 12, no svd, k-means clustering, and cluster
stopping with the adapted gap statistic.

I did not tune these settings on any data, and in fact, the results I
submitted to the task were based on the second or third run I did,
where the only thing I varied was the frequency cutoff for feature
identification (my initial settings were too high I think, resulting
in few or no features being selected for some words).

More detailed discussion can be found here:

UMND2 : SenseClusters Applied to the Sense Induction Task of
Senseval-4  (Pedersen) - Appears in the Proceedings of SemEval-2007:
4th International Workshop on Semantic Evaluations, June 23-24, 2007,
Prague, Czech Republic.
http://www.d.umn.edu/~tpederse/Pubs/umnd2-sval4.pdf

This paper includes a description of the system as well as some
discussion of unsupervised evaluation techniques for discrimination /
disambiguation systems, which I think remains a very open and
interesting area of work.

Enjoy,
Ted

-- 
Ted Pedersen
http://www.d.umn.edu/~tpederse

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