A second
<term>
model
</term>
then attempts to improve upon this initial
<term>
ranking
</term>
, using additional
<term>
features
</term>
of the
<term>
tree
</term>
as evidence .
#8071A second model then attempts to improve upon this initial ranking, using additional features of thetree as evidence.
other,10-4-J05-1003,ak
The strength of our approach is that it allows a
<term>
tree
</term>
to be represented as an arbitrary set of
<term>
features
</term>
, without concerns about how these
<term>
features
</term>
interact or overlap and without the need to define a
<term>
derivation
</term>
or a
<term>
generative model
</term>
which takes these
<term>
features
</term>
into account .
#8085The strength of our approach is that it allows atree to be represented as an arbitrary set of features, without concerns about how these features interact or overlap and without the need to define a derivation or a generative model which takes these features into account.
lr,8-6-J05-1003,ak
We apply the
<term>
boosting method
</term>
to parsing the
<term>
Wall Street Journal treebank
</term>
.
#8159We apply the boosting method to parsing theWall Street Journal treebank.