@inproceedings{bouchet_tree-kernel_2009,
	address = {Leipzig, Germany},
	title = {Tree-kernel and Feature Vector Methods for Formal Semantic Requests Classification},
	isbn = {978-3-940501-04-2},
	abstract = {In this paper, we're interested in the classification of natural language requests converted into a formal representation, where the classes represent the conversational activity of those requests. This study is based on a corpus of requests collected using an assisting conversational agent, in which we identified four different classes (control, chat, direct and indirect assistance requests). The objective would be to take over from the rule-based system when it fails. First representing formal requests as a tree, we show it is possible to adapt tree kernel methods to our problematic. A second approach consisting in ignoring the request structure to focus on its components (i.e. considering it as a feature vector) gives better results a priori. We finally consider combining several of the previous classifiers, thus reaching a performance rate of 76.1\%, which could be enough for using it as a complementary system.},
	booktitle = {Machine Learning and Data Mining in Pattern Recognition},
	publisher = {{IBaI} Publishing},
	author = {François Bouchet and {Jean-Paul} Sansonnet},
	editor = {Petra Perner},
	month = jul,
	year = {2009},
	pages = {126--140}
}