key words:
Bayesian learning
signal '--> concept
making up a grammar:
we start with a grammar where each rule describe one of the sentence of the corpus: so there are the same number of non terminal nodes/symbols as a terminal nodes or words at the corpus.
2 operations:
Merge - > reduce the number of nodes.
Chinking - > increase the number of nodes.
Selecting operations the grammar become more and more open.
The objective is to compare trees analysis, so the accuracy is measure as how near get the tree analysis of the emerge parser compared with the tree of a stablish parser.
(??? not very clear point)
for artificial grammars it give a very good results.
For real data sets not very good.
Full information:
http://turing.science.uva.nl/~jzuidema/teaching/dublin09/
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