Statistical Dependency Analysis with Support Vector Machines

نویسندگان

  • Hiroyasu Yamada
  • Yuji Matsumoto
چکیده

In this paper, we propose a method for analyzing word-word dependencies using deterministic bottom-up manner using Support Vector machines. We experimented with dependency trees converted from Penn treebank data, and achieved over 90% accuracy of word-word dependency. Though the result is little worse than the most up-to-date phrase structure based parsers, it looks satisfactorily accurate considering that our parser uses no information from phrase structures.

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تاریخ انتشار 2003