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data:start [2008/03/07 10:07]
marco |
data:start [2008/03/30 13:05]
schtepf |
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| ===== Ordered by task categories ===== | ===== Ordered by task categories ===== |
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| ==== Task 1: Free Association ==== | ==== Task 1: Free Association ==== |
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| | **NB: On March 29th, we fixed a small (but serious) bug in script ''eval_task3.perl''. If you obtained a copy at an earlier time, please download the most recent version of the package and use it for your evaluation.** |
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| ==== Task 2: Categorization ==== | ==== Task 2: Categorization ==== |
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| You can train your word space on your favorite corpus. However, we also invite you, if this is suitable, to experiment with the [[http://wacky.sslmit.unibo.it|ukWaC]] corpus, so that we will be able to compare different word spaces trained on the same corpus (for information on how to obtain the corpus, write to [[wacky@sslmit.unibo.it|this address]]). ukWaC is a very large (about 2 billion tokens) Web-derived corpus. It is split into sub-sections containing randomly chosen documents. Thus, if your algorithm has problems scaling up to 2 billion tokens, you can train it on one or more sub-sections, that will constitute a document-based random sub-sample of ukWaC. | You can train your word space on your favorite corpus. However, we also invite you, if this is suitable, to experiment with the [[http://wacky.sslmit.unibo.it|ukWaC]] corpus, so that we will be able to compare different word spaces trained on the same corpus (for information on how to obtain the corpus, write to [[wacky@sslmit.unibo.it|this address]]). ukWaC is a very large (about 2 billion tokens) Web-derived corpus. It is split into sub-sections containing randomly chosen documents. Thus, if your algorithm has problems scaling up to 2 billion tokens, you can train it on one or more sub-sections, that will constitute a document-based random sub-sample of ukWaC. |
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