UTH: SVM-based Semantic Relation Classification using Physical Sizes

نویسندگان

  • Eiji Aramaki
  • Takeshi Imai
  • Kengo Miyo
  • Kazuhiko Ohe
چکیده

Although researchers have shown increasing interest in extracting/classifying semantic relations, most previous studies have basically relied on lexical patterns between terms. This paper proposes a novel way to accomplish the task: a system that captures a physical size of an entity. Experimental results revealed that our proposed method is feasible and prevents the problems inherent in other methods.

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تاریخ انتشار 2007