Abstract
T. Kohonen and P. Somervuo have shown that self organizing maps (SOMs) are not restricted to numerical data. This paper proposes a symbolic measure that is used to implement a string self organizing map based on SOM algorithm. Such measure between two strings is a new string. Computation over strings is performed using a priority relationship among symbols, in this case, symbolic measure is able to generate new symbols. A complementary operation is defined in order to apply such measure to DNA strands. Finally, an algorithm is proposed in order to be able to implement a string self organizing map. This paper discusses the possibility of defining neural networks to rely on similarity instead of distance and shows examples of such networks for symbol strings.
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de Mingo López, L.F., Blas, N.G., Díaz, M.A. (2009). A String Measure with Symbols Generation: String Self-Organizing Maps. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_15
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DOI: https://doi.org/10.1007/978-3-642-03040-6_15
Publisher Name: Springer, Berlin, Heidelberg
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