Probabilistic topic maps: Navigating through large text collections

Abstract

The visualization of large text databases and document collections is an important step towards more flexible and interactive types of information retrieval. This paper presents a probabilistic approach which combines a statistical, model—based analysis with a topological visualization principle. Our method can be utilized to derive topic maps which represent topical information by characteristic keyword distributions arranged in a two—dimensional spatial layout. Combined with multi-resolution techniques this provides a three-dimensional space for interactive information navigation in large text collections.