Clustering Dynamic Web Usage Data

  title={Clustering Dynamic Web Usage Data},
  author={A. D. Silva and Y. Lechevallier and F. Rossi and F. Carvalho},
  • A. D. Silva, Y. Lechevallier, +1 author F. Carvalho
  • Published 2012
  • Mathematics, Computer Science
  • ArXiv
  • Most classification methods are based on the assumption that data conforms to a stationary distribution. The machine learning domain currently suffers from a lack of classification techniques that are able to detect the occurrence of a change in the underlying data distribution. Ignoring possible changes in the underlying concept, also known as concept drift, may degrade the performance of the classification model. Often these changes make the model inconsistent and regular updatings become… CONTINUE READING

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