A New Distance Measure for Model-Based Sequence Clustering Articles uri icon

publication date

  • March 2009

start page

  • 1325

end page

  • 1331

issue

  • 7

volume

  • 31

International Standard Serial Number (ISSN)

  • 0162-8828

Electronic International Standard Serial Number (EISSN)

  • 1939-3539

abstract

  • We review the existing alternatives for defining model-based distances for clustering sequences and propose a new one based on the Kullback-Leibler divergence. This distance is shown to be especially useful in combination with spectral clustering. For improved performance in real-world scenarios, a model selection scheme is also proposed.