Abstract
Clustering methods are used in pattern recognition to obtain natural groups from a data set in the framework of unsupervised learning as well as for obtaining clusters of data from a known class. In sets of strings, the concept of set median string can be extended to the (set)k-medians problem. The solution of the k-medians problem can be viewed as a clustering method, where each cluster is generated by each of the k strings of that solution. A concept which is related to set median string is the (generalized) median string, which is an NP-Hard problem. However, different algorithms have been proposed to find approximations to the (generalized) median string. We propose extending the (generalized) median string problem to k strings, resulting in the generalizedk-medians problem, which can also be viewed as a clustering technique. This new technique is applied to a corpus of chromosomes represented by strings and compared to the conventional k-medians technique.
Work partially supported by the Spanish CICYT under grant TIC2000-1703-C03-01 and by the Valencian OCYT under grant CTIDIA/2002/80.
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Martínez-Hinarejos, C.D., Juan, A., Casacuberta, F. (2003). Generalized k-Medians Clustering for Strings. In: Perales, F.J., Campilho, A.J.C., de la Blanca, N.P., Sanfeliu, A. (eds) Pattern Recognition and Image Analysis. IbPRIA 2003. Lecture Notes in Computer Science, vol 2652. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-44871-6_59
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DOI: https://doi.org/10.1007/978-3-540-44871-6_59
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