Content-based Document Classification with Highly Compressed Input Data

  title={Content-based Document Classification with Highly Compressed Input Data},
  author={Dieter Merkl},
One of the major obstacles for the application of artificial neural networks to real-world problems is the rather time-consuming task of training. In this paper we will demonstrate that considerable acceleration with equal classification results may be achieved by the utilization of highly compressed input data for a self-organizing map. As the basis for the experiments we use an application in the area of software reuse, namely the structuring of software components. As a result we are able to… CONTINUE READING
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