Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Using maps as a user interface to a digital library
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Self-Organizing Maps
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Automatic Labeling of Self-Organizing Maps: Making a Treasure-Map Reveal Its Secrets
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
DEXA '98 Proceedings of the 9th International Conference on Database and Expert Systems Applications
DEXA '97 Proceedings of the 8th International Workshop on Database and Expert Systems Applications
DEXA '00 Proceedings of the 11th International Conference on Database and Expert Systems Applications
DEXA '01 Proceedings of the 12th International Conference on Database and Expert Systems Applications
Text clustering based on LSA-HGSOM
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Category labelling for automatic classification scheme generation
FDIA'07 Proceedings of the 1st BCS IRSG conference on Future Directions in Information Access
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While the focus of research concerning electronic document archives still is on information retrieval, the importance of interactive exploration has been realized and is gaining importance. The map metaphor, where documents are organized on a map according to their contents, has proven particularly useful as an interface to such a collection. The self-organizing map has shown to produce stable topically ordered organizations of documents on such a 2-dimensional map display. However, the characteristics of these topical clusters are not being made explicit. In this paper we present the LabelSOM method which takes the applicability of the self-organizing map for document archive organization one step further by automatically labeling the various topical clusters found in the map. This allows the user to get an instant overview of the various topics covered by a document collection.