Posting Act Tagging Using Transformation-Based Learning

نویسندگان

  • Tianhao Wu
  • Faisal M. Khan
  • Todd A. Fisher
  • Lori A. Shuler
  • William M. Pottenger
چکیده

In this article we present the application of transformation-based learning (TBL) [1] to the task of assigning tags to postings in online chat conversations. We define a list of posting tags that have proven useful in chat-conversation analysis. We describe the templates used for posting act tagging in the context of template selection. We extend traditional approaches used in part-of-speech tagging and dialogue act tagging by incorporating regular expressions into our templates. We close with a presentation of results that compare favorably with the application of TBL in dialogue act tagging.

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تاریخ انتشار 2005