Speeding Up the Dissimilarity Self-Organizing Maps by Branch and Bound
This paper proposes to apply the branch and bound principle from combinatorial optimization to the Dissimilarity Self-Organizing Map (DSOM), a variant of the SOM that can handle dissimilarity data. A new reference model optimization method is derived from this principle. Its results are strictly identical to those of the original DSOM algorithm by Kohonen and Somervuo, while its running time is reduced by a factor up to 2.5 compared to the one of the previously proposed optimized implementation.
KeywordsExhaustive Search Word List Model Collision Neighborhood Function Prior Structure
Unable to display preview. Download preview PDF.
- 1.Kohonen, T.: Self-Organizing Maps, 3rd edn. (Last edition published in 2001) Springer Series in Information Sciences, vol. 30. Springer, Heidelberg (1995)Google Scholar
- 6.Ambroise, C., Govaert, G.: Analyzing dissimilarity matrices via Kohonen maps. In: Proceedings of 5th Conference of the International Federation of Classification Societies (IFCS 1996), vol. 2, Kobe, Japan, March 1996, pp. 96–99 (1996)Google Scholar
- 7.Rossi, F.: Model collisions in the dissimilarity som. In: Proc. of ESANN 2007, Bruges, Belgium (April 2007)Google Scholar
- 9.Atkinson, K.: Spell checking oriented word lists (SCOWL). Revision 6 (2004), Available at http://wordlist.sourceforge.net/
- 10.Porter, M.F.: An algorithm for suffix stripping. Program 14(3), 130–137 (1980)Google Scholar