The automatic clustering of text segments into thematically homogeneous groups is a difficult problem. In this paper, we study the performance of a simple probabilistic model, the "monomaniac" model. We first describe the model and the related EM-based estimation procedures; an application of this model to a English corpus of texts imported from the CKM ("Customer Knowledge Management") literature is then presented.