A neural visualization method for WWW document clusters

Search engines are widely used for retrieving documents on the WWW. Visualization is useful for users to understand the retrieval results. When the retrieved documents are represented as document vectors, neural networks can be employed to visualize them. In this study, we consider the following two requirements for the visualization algorithm. One is that the cluster structure of document vectors is preserved. The other is that the visualization algorithm is fast. For these requirements, we employ basis function networks. Basis functions detect the cluster structure and weight parameters are adjusted by a fast algorithm so that the distance structure of the document vectors is preserved. Experiments show that our method is fast enough as an interface system.