Automatic Construction and Refinement of a Class Hierarchy over Semi-Structured Data

In many applications, it becomes crucial to help users to access to a huge amount of data by clustering them in a small number of classes described at an appropriate level of abstraction. In this paper, we present an approach based on the use of two languages of description of classes for the automatic clustering of semistructured data. The rst language of classes has a high power of abstraction and guides the construction of a lattice of classes covering the whole set of the data. The second language of classes, more expressive and more precise, is the basis for the re nement of a part of the lattice that the user wants to focus on. Our approach has been implemented and experimented on real data in the setting of the GAEL project 1 which aims at building exible electronic catalogs organized as a hierarchy of classes of products. Our experiments have been conducted on real data coming from the C/Net (http://www.cnet.com) electronic catalog of computer products.