Probabilistic Topic Maps: Navigating through Large Text Collections
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.