By Rainer Schmidt, Tina Waligora (auth.), Petra Perner (eds.)
The commercial convention on facts Mining ICDM-Leipzig was once the 6th occasion in a sequence of annual occasions which began in 2000. we're happy to notice that the subject facts mining with designated emphasis on real-world functions has been followed via such a lot of researchers around the world into their learn paintings. We acquired 156 papers from 19 diverse international locations. the most themes are facts mining in drugs and advertising and marketing, net mining, mining of pictures and indications, theoretical facets of knowledge mining, and facets of knowledge mining that package a sequence of other information mining functions similar to intrusion detection, wisdom administration, production strategy regulate, time-series mining and felony investigations. this system Committee labored difficult so that it will decide upon the simplest papers. The reputation fee used to be 30%. these types of chosen papers are released during this lawsuits quantity as lengthy papers as much as 15 pages. additionally we put in a discussion board the place paintings in growth was once provided. those papers are gathered in a unique poster complaints quantity and exhibit once again the potentials and fascinating advancements of knowledge mining for various functions. 3 new workshops were tested in reference to ICDM: (1) Mass information research on photos and signs, MDA 2006; (2) facts Mining for all times Sciences, DMLS 2006; and (3) information Mining in advertising and marketing, DMM 2006. those workshops are constructing new subject matters for info mining lower than the point of the certain program. we're happy to work out what percentage attention-grabbing advancements are happening in those fields.
Read or Download Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining: 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 14-15, 2006. Proceedings PDF
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Additional resources for Advances in Data Mining. Applications in Medicine, Web Mining, Marketing, Image and Signal Mining: 6th Industrial Conference on Data Mining, ICDM 2006, Leipzig, Germany, July 14-15, 2006. Proceedings
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The sequence space size for a multispecies gene is generally a huge number and the gene length after alignment is relatively a small number. The finite sample effect problem will be more dangerous under such a situation because the relative frequency based approximation of the probability distribution of all sites in the huge sequence space is no longer reasonable. We develop a data mining approach to estimate the multispecies gene entropy in this work. The idea is to employ a self-organizing map (SOM) to mine a set of homologous genes to compute their prototypes.
For a multispecies gene x with n aligned nucleotides of m species ( m ≥ 2 ), it is a m × n dimension character matrix where each row is a gene sequence of a species and each column is called a site or character. Aligned homologous genes are employed to infer the species phylogenies of a set of organisms in phylogenetics. It is interesting to investigate phylogenetically informative genes in the species phylogeny reconstruction from the point view of the gene entropy. The gene entropy of a single-species gene is same as the definition of the DNA entropy.