We present an incremental algorithm for building a neighborhood graph from a set of documents. This algorithm is based on a population of artificial agents that imitate the way real ants build structures with self-assembly behaviors. We show that our method outperforms standard algorithms for building such neighborhood graphs (up to 2230 times faster on the tested databases with equal quality) and how the user may interactively explore the graph. Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Clustering General Terms Algorithms Keywords Web, documents, graph, interactive visualization, clustering, artificial ants