Visual divisive hierarchical clustering using k-means

نویسندگان

  • Matic Perovšek
  • Nada Lavrač
  • Bojan Cestnik
چکیده

This paper presents a browser-based semi-automatic taxonomy construction tool Vd-chuck which is able to incorporate text and data mining algorithms into a userfriendly interface. The presented system is browserbased. Its unsupervised learning for concept suggestion and different visualization techniques assist the user with textual and numerical data analysis. We tested the Vdchuck system on a real-world domain: a corpus of documents taken from Slovenian Language technologies conferences. The results show that with our system similar taxonomies as with other taxonomy editors can be constructed.

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تاریخ انتشار 2012