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User adaptive clustering and visualization of document collections.
| Content Provider | CiteSeerX |
|---|---|
| Author | Nürnberger, Andreas Detyniecki, Marcin |
| Abstract | An interesting way of accessing collections of documents is by methods of visualization and clustering. Growing self-organizing maps provide such a solution, by adapting their structure automatically to the structure and size of the underlying database. Unfortunately, the result of the clustering process greatly depends on the definition of the describing features and the employed similarity measure and therefore often does not fulfill the users expectancies. In this paper, we present an approach to improve the obtained clustering by considering user feedback (in the form of drag-and-drop) to adapt the underlying topology of the selforganizing map. 1 |
| File Format | |
| Access Restriction | Open |
| Content Type | Text |
