Classification Pruning for Web-request Prediction

نویسندگان

  • Ian Tian Yi Li
  • Qiang Yang
  • Ke Wang
چکیده

N-gram and repeating pattern based prediction rules have been used for next-web request prediction. However, there is no rigorous study of how to select the best rule for a given observation. The longer patter may not be the best pattern, because such patters are also more rare. In this paper, we propose several rule-pruning methods that enable us to build efficient, compact and high-quality classifiers for webrequest prediction.

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تاریخ انتشار 2001