The analysis of multivariate time series about limp angles and
muscle activity during Inline Speed-Skating was done using the with the
Time Series Knowledge Mining. The resulting temporal patterns describe
typical coordination patterns of muscles during repetitive movements.
The pattern descriptions can be used for rehabilitation therapy and
Time Series from Inline
The self-organization of 8.000 US stocks led to a new segmentation
of the market. The knowledge gained from the groups was used to predict
the probability of making profits. The forecasts were successful even
when applied to currently generally falling stocks.
In an analysis of DNA microarray we were able to extract the most
relevant attributes from a set of 4000 genes. The reduction led to 19
genes particulariy well suited for prediction of an illness. This large
decrease in complexity made it possible to perform a more detailed
analysis of the function for those genes. First results indicate new
insights into the growth of cancer for small kids.
U-Matrix Gene data
Customer Relationship Management
The clustering of customer behaviour applied to data from a mobile
phone company produced a novel segmentation of the clients. The
descriptions of the groups helped the company to identify the most
interesting groups, e.g. all customers likely to stop the contract in
the near future.
U-Matrix Mobile phones