Classification de documents XML à partir d'une représentation linéaire des arbres de ces documents

In this work, we propose a new clustering document representation for semi-structured documents collections. Our approach consists on a representation of XML documents based on their sub-paths, defined according to some criteria (length, root beginning, leaf ending) using the structure only or both the structure and the content. By considering those sub-paths as words, we can use standard methods for vocabulary reduction, and simple clustering methods such as K-means that scale up well. We actually use an implementation of the clustering algorithm known as \textit{dynamic clouds} that can work with distinct groups of independent variables. This is necessary in our model since embedded sub-paths are not independent. For validation and evaluation of our method, two collections are used: the INEX corpus and the INRIA activity reports, and a set of metrics well-known in Information Retrieval.