Exploration of Very Large Databases by Self-organizing Maps

  title={Exploration of Very Large Databases by Self-organizing Maps},
  author={Teuvo Kohonen},
This paper describes a data organization system and genuine content-addressable memory called the WEBSOM. It is a two-layer self-organizing map (SOM) architecture where documents become mapped as points on the upper map, in a geometric order that describes the similarity of their contents. By standard browsing tools one can select from the map subsets of documents that are most similar mutually. It is also possible to submit free-form queries about the wanted documents whereby the WEBSOM… CONTINUE READING
Highly Cited
This paper has 118 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 69 extracted citations

Spectral regularization in generalized matrix learning vector quantization

2017 12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization (WSOM) • 2017
View 2 Excerpts

3D Facial Expression Classification Based on Self-Organizing Mapping Network

2013 Seventh International Conference on Internet Computing for Engineering and Science • 2013
View 1 Excerpt

Time Series Clustering in the Field of Agronomy Cluster

Irina Alles, Christian Biemann, Florent Masseglia, Tag der Einreichung, Erklärung zur Master-Thesis
View 2 Excerpts

118 Citations

Citations per Year
Semantic Scholar estimates that this publication has 118 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-4 of 4 references

Similar Papers

Loading similar papers…