Automated extraction of Cutting Tool information for various Metal Cutting Operations

نویسندگان

  • Sudhama Kalaga
  • Dr.Toni Kazic
چکیده

In any manufacturing firm, cutting tool selection for a metal removing operation plays a pivotal role. For various operations, different set of cutter tools made of different materials or specification are used. Through this paper, it is aimed at automated extraction of the data of these cutting tools for various metal cutting operations using elements of the Natural Language Processing. We discuss the extraction of useful information from the corpus using natural language tools such as LingPipe and GATE. We generate a code in PERL for the extraction of this sensible useful data.

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تاریخ انتشار 2007