Automatic construction of navigable concept networks characterizing text databases

In this paper we present a comprehensive approach to conceptual structuring and intelligent navigation of text databases. Given any collection of texts, we first automatically extract a set of index terms describing each text. Next, we use a particular lattice conceptual clustering method to build a network of clustered texts whose nodes are described using the index terms. We argue that the resulting network supports an hybrid navigational approach to text retrieval - implemented into an actual user interface - that combines browsing potentials with good retrieval performance. We present the results of an experiment on subject searching where this approach outperformed a conventional Boolean retrieval system.